docs: describe grilling as round-by-round everywhere

The round-by-round rework left the wrappers and callers still promising
a one-question-at-a-time interview. Sync grill-me, grill-with-docs and
triage (docs + skill step), plus grilling's Codex short_description and
the loop-me draft.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

.changeset/graduate-to-questionnaire.md

@@ -0,0 +1,9 @@
+---
+"mattpocock-skills": minor
+---
+
+Graduate **`to-questionnaire`** out of `in-progress/` into the **Productivity** bucket, so it ships in the plugin. It turns a decision you can't answer alone into a Markdown questionnaire for the one person who can — filled in async, or worked through together in a meeting.
+
+Its defining move is that it grills you about the **send**, not the subject: a normal grilling session interrogates the topic, which is exactly what you can't answer here, so the interview asks only who the questionnaire is going to and what you need back, then aims every question at the gap between the two.
+
+Now wired as a promoted skill — plugin entry, top-level + Productivity READMEs under **User-invoked**, a docs page at `docs/productivity/to-questionnaire.md`, and a Standalone route in `ask-matt` framing it as the inverse of `/grill-me` (mine someone else, not yourself).

.changeset/grilling-question-format.md

@@ -0,0 +1,5 @@
+---
+"mattpocock-skills": patch
+---
+
+Pin the question format in **`grilling`**. Every question in a round is now emitted in one fixed shape — `❓ **Q1** - **<title>**`, then the body (prose or multiple choices), then the recommendation on its own `➡️` line. A round reads as a scannable numbered list with each recommendation visually separated from the question, so you can answer by number instead of quoting questions back.

.changeset/grilling-rounds-docs-sync.md

@@ -0,0 +1,5 @@
+---
+"mattpocock-skills": patch
+---
+
+Sync the skills and docs that still described grilling as a **one-question-at-a-time** interview. Since the round-by-round rework, `grill-me`, `grill-with-docs` and `triage` all run the frontier a round at a time — their pages, `triage`'s grill step and `grilling`'s Codex `short_description` now say so. The opt-out for the old rhythm (a line in your global `CLAUDE.md`) is unchanged.

.changeset/writing-for-agents-environment-cache.md

@@ -0,0 +1,5 @@
+---
+"mattpocock-skills": minor
+---
+
+Extend **`writing-for-agents`**' pruning section with a new leading word: **cache**. Single source of truth now reaches past the document into the environment — `package.json` scripts, config files, directory layout, `--help` output are themselves authoritative, so a doc that restates them is a cache of a lookup, earning its load only when the lookup is expensive. The positive target: cache what the agent cannot find by looking (unwritten conventions, the reason behind a choice, gotchas no config confesses), and leave one-file, one-command lookups to the environment, where they cannot go stale.

.changeset/writing-for-agents-rename.md

@@ -0,0 +1,5 @@
+---
+"mattpocock-skills": minor
+---
+
+**Breaking:** rename **`writing-great-skills`** → **`writing-for-agents`** and restructure it. The reference now covers any document an agent consumes — skills, `AGENTS.md` / `CLAUDE.md`, docs reached by a pointer — not just skills. `GLOSSARY.md` is merged into `SKILL.md` (one authoritative treatment per term; the `_Avoid_` synonym lists and the standalone Predictability definition are gone); the skill-only mechanics (frontmatter, model- vs user-invoked, router skills, the invocation cut of splitting) are disclosed to a new `SKILL-MECHANICS.md`. The skill is now **model-invoked**: it fires when creating or editing skills or modifying `AGENTS.md`/`CLAUDE.md`. `ask-matt`'s pointer updated. Reinstall under the new name; the old name is gone (no alias).

.claude-plugin/plugin.json

@@ -40,6 +40,7 @@
     "./skills/productivity/grilling",
     "./skills/productivity/handoff",
     "./skills/productivity/teach",
-    "./skills/productivity/writing-great-skills"
+    "./skills/productivity/to-questionnaire",
+    "./skills/productivity/writing-for-agents"
   ]
 }

README.md

@@ -206,7 +206,8 @@ General workflow tools, not code-specific.
 - **[grill-me](./skills/productivity/grill-me/SKILL.md)** — Get relentlessly interviewed about a plan or design until every branch of the decision tree is resolved.
 - **[handoff](./skills/productivity/handoff/SKILL.md)** — Compact the current conversation into a handoff document so another agent can continue the work.
 - **[teach](./skills/productivity/teach/SKILL.md)** — Teach the user a new skill or concept over multiple sessions, using the current directory as a stateful teaching workspace.
-- **[writing-great-skills](./skills/productivity/writing-great-skills/SKILL.md)** — Reference for writing and editing skills well: the vocabulary and principles that make a skill predictable.
+- **[to-questionnaire](./skills/productivity/to-questionnaire/SKILL.md)** — Turn a decision you can't answer alone into a Markdown questionnaire for the one person who can — filled in async, or together over a meeting. It grills you about the send (who it's for, what you need back), not the subject.
+- **[writing-for-agents](./skills/productivity/writing-for-agents/SKILL.md)** — Writing documents for agents: skills, AGENTS.md/CLAUDE.md, and any doc an agent reaches by a pointer.
 
 **Model-invoked**
 

docs/engineering/grill-with-docs.md

@@ -12,7 +12,7 @@ npx skills update grill-with-docs
 
 ## What it does
 
-`grill-with-docs` interviews you relentlessly about a plan or design, one question at a time, until you and the agent reach a shared understanding — and it writes the vocabulary and decisions down as you go.
+`grill-with-docs` interviews you relentlessly about a plan or design, a round of questions at a time, until you and the agent reach a shared understanding — and it writes the vocabulary and decisions down as you go.
 
 The grilling **leaves a paper trail**. A plain interview sharpens your thinking and then evaporates when the session ends; this one captures each term the moment it's resolved into a `CONTEXT.md` glossary, and records the hard, one-way decisions as ADRs. The alignment survives the conversation instead of living only in your head.
 
@@ -28,13 +28,13 @@ This skill is stateful — it writes into your repo as it grills. Resolved terms
 
 ## The grill
 
-The engine is a **grill**: a relentless, one-question-at-a-time walk down the decision tree, resolving dependencies between decisions before moving on, with a recommended answer offered for every question. Questions the codebase can answer are answered by reading the codebase, not by asking you.
+The engine is a **grill**: a relentless, round-by-round walk down the decision tree. Each round asks the whole **frontier** — every decision whose prerequisites are already settled — and waits, so dependencies between decisions are resolved before the questions that hang off them are asked, with a recommended answer offered for every question. Questions the codebase can answer are answered by reading the codebase, not by asking you.
 
 What makes this variant its own skill is where the answers go. As the grill runs, fuzzy language gets sharpened into canonical terms and written to the glossary inline — not batched at the end. The glossary stays a glossary: pure vocabulary, no implementation details, no spec. ADRs are offered sparingly, only when a decision is hard to reverse, surprising without context, and the result of a real trade-off. Most sessions produce a sharper glossary and few or no ADRs, and that's the intended shape.
 
 ## It's working if
 
-- It asks one question at a time and waits, rather than dumping a questionnaire.
+- It asks a round of independent questions and waits, rather than dumping the whole questionnaire at you.
 - Terms get written to `CONTEXT.md` the moment they resolve, in your project's own words.
 - It reaches into the codebase to answer its own questions where it can.
 - ADRs stay rare — you're not asked to rubber-stamp reversible choices.

docs/engineering/triage.md

@@ -43,4 +43,4 @@ The step that separates `triage` from ad-hoc labelling is verification. It repro
 
 ## Where it fits
 
-`triage` is the **periodic maintenance** pass over your issue tracker — run it whenever reports pile up, to keep the queue sorted and the `ready-for-agent` column trustworthy. It sits at the front of the tracker, upstream of the build chain: the briefs it writes are what [tdd](https://aihero.dev/skills-tdd) later picks up to implement. When a request needs sharpening it leans on [grilling](https://aihero.dev/skills-grilling) and [domain-modeling](https://aihero.dev/skills-domain-modeling) to grill it into shape one question at a time. Its close neighbour is [to-spec](https://aihero.dev/skills-to-spec), which populates the tracker from a fresh conversation where `triage` processes what's already there. When you're unsure which skill or flow fits, [ask-matt](https://aihero.dev/skills-ask-matt) routes you.
+`triage` is the **periodic maintenance** pass over your issue tracker — run it whenever reports pile up, to keep the queue sorted and the `ready-for-agent` column trustworthy. It sits at the front of the tracker, upstream of the build chain: the briefs it writes are what [tdd](https://aihero.dev/skills-tdd) later picks up to implement. When a request needs sharpening it leans on [grilling](https://aihero.dev/skills-grilling) and [domain-modeling](https://aihero.dev/skills-domain-modeling) to grill it into shape a round of questions at a time. Its close neighbour is [to-spec](https://aihero.dev/skills-to-spec), which populates the tracker from a fresh conversation where `triage` processes what's already there. When you're unsure which skill or flow fits, [ask-matt](https://aihero.dev/skills-ask-matt) routes you.

docs/productivity/grill-me.md

@@ -14,7 +14,7 @@ npx skills update grill-me
 
 `grill-me` runs a relentless interview about a plan or design, walking every branch of the decision tree until you and the agent reach a **shared understanding**.
 
-It asks **one question at a time** and waits. It never dumps a batch of questions at you — that is bewildering — and where a question can be answered by reading the codebase, it goes and reads rather than asking. Each question comes with the agent's own recommended answer, so you are reacting to a proposal, not staring at a blank prompt.
+It asks in **rounds** and waits. A round is the whole **frontier** — every decision whose prerequisites are already settled — put to you as one numbered list, so you're never asked something that hinges on an answer the agent hasn't heard yet. Where a question can be answered by reading the codebase, it goes and reads rather than asking. Each question comes with the agent's own recommended answer, so you are reacting to a proposal, not staring at a blank prompt.
 
 ## When to reach for it
 
@@ -24,7 +24,7 @@ Reach for it before you build, when a plan feels roughly right but you can sense
 
 ## The decision tree
 
-The session walks the plan as a tree of decisions, resolving dependencies between them one by one — a parent decision settled before the choices that hang off it. The point is not to reach agreement quickly; it is to make every implicit call explicit, so nothing important is left silently assumed. You come out the other side with a plan whose branches have all been visited.
+The session walks the plan as a tree of decisions, settling a parent decision before the choices that hang off it. Your answers reshape the tree and push the frontier outward, so the next round asks whatever they unblocked. The point is not to reach agreement quickly; it is to make every implicit call explicit, so nothing important is left silently assumed. You come out the other side with a plan whose branches have all been visited.
 
 `grill-me` is **stateless**: it writes nothing and leaves no workspace behind. It runs anywhere, and the only artifact is the sharpened understanding in the conversation itself. That is the deliberate contrast with [grill-with-docs](https://aihero.dev/skills-grill-with-docs), which captures the same interview as durable ADRs and a glossary.
 

docs/productivity/grilling.md

@@ -14,7 +14,7 @@ npx skills update grilling
 
 `grilling` is the relentless interview that stress-tests a plan or design before you build it. It maps the plan as a **design tree** — every decision branches into the decisions that hang off it — and works that tree in **rounds** until you and the agent share the same understanding.
 
-Each round asks the whole **frontier**: every decision whose prerequisites are already settled — the questions it can put to you *now* without guessing at answers it hasn't heard yet. Your answers reshape the tree, pushing the frontier outward, and the next round asks whatever that unblocks. Thirteen questions land in a handful of rounds instead of thirteen. Every question comes with the agent's own recommended answer; any *fact* the environment can settle it dispatches to a background sub-agent rather than asking you — and it doesn't block on that research, only the questions downstream of it wait. It won't act on the plan until you confirm the shared understanding has been reached.
+Each round asks the whole **frontier**: every decision whose prerequisites are already settled — the questions it can put to you *now* without guessing at answers it hasn't heard yet. Your answers reshape the tree, pushing the frontier outward, and the next round asks whatever that unblocks. Thirteen questions land in a handful of rounds instead of thirteen. Every question arrives in a fixed shape — numbered and titled behind a `❓` (`❓ **Q1** - **Storage backend**`), then the body, then the agent's recommendation on its own `➡️` line — so a round reads as a scannable list and you can answer it by number rather than by quoting it back; any *fact* the environment can settle it dispatches to a background sub-agent rather than asking you — and it doesn't block on that research, only the questions downstream of it wait. It won't act on the plan until you confirm the shared understanding has been reached.
 
 ### Prefer one question at a time?
 

docs/productivity/to-questionnaire.md

@@ -0,0 +1,46 @@
+Quickstart:
+
+```bash
+npx skills add mattpocock/skills --skill=to-questionnaire
+```
+
+```bash
+npx skills update to-questionnaire
+```
+
+[Source](https://github.com/mattpocock/skills/tree/main/skills/productivity/to-questionnaire)
+
+## What it does
+
+`to-questionnaire` turns a decision you can't settle on your own into a **questionnaire** — a Markdown document you hand to the one person who holds what you're missing, to fill in async or work through together in a meeting.
+
+It grills you about the **send**, never the subject. A normal grilling session interrogates the topic, which is exactly what you can't answer here — that's why you're writing to someone else. So the interview asks only the two things you can always answer: who this is going to, and what you need back from them. The questions in the document are then aimed at the **gap** between the two.
+
+## When to reach for it
+
+You invoke this by typing `/to-questionnaire` — the agent won't reach for it on its own.
+
+Reach for this when a decision is blocked on knowledge that lives in someone else's head — a client, a domain expert, a colleague on another team — and you want a document that pulls it out of them in one pass. When the knowledge is in *your* head and just needs sharpening, use [grill-me](https://aihero.dev/skills-grill-me) instead; when it's in the codebase, use [grill-with-docs](https://aihero.dev/skills-grill-with-docs).
+
+## The send, not the subject
+
+The interview is two exchanges, and it stops there:
+
+- **Who is it going to?** Their role, expertise, and relationship to you. This fixes the tone and how much context the document has to carry — an outside client needs orienting; a teammate does not.
+- **What do you need back?** The concrete decisions or facts you can't resolve alone. This becomes the checklist the finished questionnaire is measured against: every item you named has a question aimed at it.
+
+Everything after that is drafting. The output is written to `to-questionnaire-<slug>.md` in the current directory.
+
+## The document
+
+It's a **discovery questionnaire**: you lack the context, the recipient holds it. That framing drives its shape — a purpose line and the decision riding on it, a short context section for a recipient who wasn't in your head, and questions ordered **most-important-first**, because async means you may only get one pass. Each question is one idea, never compound, with an answer stub beneath it and a *why this matters* line only where the question could be misread. It closes with a catch-all: anything we didn't ask that we should know?
+
+## It's working if
+
+- It asks you about the recipient and the deliverable, then stops asking — no interrogation of the topic itself.
+- Every item you named as "what I need back" is traceable to a question in the file.
+- The questions read as aimed at what the *recipient* knows, not as your own open questions copied down.
+
+## Where it fits
+
+`to-questionnaire` is a reach-for-it-anytime standalone — it sits at the boundary of your own knowledge, where the next step is another person rather than another skill. Its neighbour is [grill-me](https://aihero.dev/skills-grill-me), because the two split on where the answers live: grilling mines you, a questionnaire mines someone else. What comes back typically feeds the main flow at [grill-with-docs](https://aihero.dev/skills-grill-with-docs) or [to-spec](https://aihero.dev/skills-to-spec). When you're unsure which skill fits the moment, [ask-matt](https://aihero.dev/skills-ask-matt) routes you.

docs/productivity/writing-for-agents.md

@@ -0,0 +1,42 @@
+Quickstart:
+
+```bash
+npx skills add mattpocock/skills --skill=writing-for-agents
+```
+
+```bash
+npx skills update writing-for-agents
+```
+
+[Source](https://github.com/mattpocock/skills/tree/main/skills/productivity/writing-for-agents)
+
+## What it does
+
+`writing-for-agents` is the reference you write agent-facing documents against — skills, `AGENTS.md` / `CLAUDE.md`, and any doc an agent reaches by a pointer. The packaging differs; the writing does not: the same levers make each one predictable, so the agent takes the same *process* every run rather than producing the same output.
+
+Formerly `writing-great-skills`. The rename tracks what the reference always was underneath: almost none of it is skill-specific. The universal core — context pointers, the two loads, the information hierarchy, completion criteria, leading words, pruning — applies to any document an agent consumes; the genuinely skill-only mechanics (frontmatter, the model- vs user-invoked choice, router skills) are disclosed to a linked `SKILL-MECHANICS.md` you read only when the document you're writing is a skill.
+
+## When to reach for it
+
+The agent reaches for it on its own whenever you're creating or editing a skill, or modifying `AGENTS.md` or `CLAUDE.md` — and you can still type `/writing-for-agents` to pull it up directly.
+
+## The two loads
+
+The concept the whole reference turns on is a pair of budgets every document and pointer spends:
+
+- **Context load** — the cost of always-loaded material on the agent's window: an `AGENTS.md` line, a skill description, anything sitting in context every turn whether or not it fires.
+- **Cognitive load** — the cost on the human: which documents exist and when to reach for each. You are the index. Not a cost to minimise — it's the price of human agency.
+
+Once you're thinking in these two loads, most authoring decisions — split or don't, inline or disclose, point or push — become the same trade made in different places.
+
+## The other levers
+
+- **Context pointers** — the reference held in context that names out-of-context material and encodes when to reach it. A skill description and an `AGENTS.md` line pointing at a doc are the same object; the pointer's *wording*, not its target, decides when and how reliably the agent reaches through it.
+- **Information hierarchy** — the ladder from in-file step, to in-file reference, to disclosed reference behind a pointer. **Progressive disclosure** is the move down that ladder so the top stays legible; **co-location** decides what sits beside each piece once placed.
+- **Completion criteria** — the clarity and demand of each step's done-condition, and the **legwork** it drives; the defence against **premature completion**.
+- **Leading words** — a compact concept already in the model's pretraining (*tight*, *red*, *tracer bullet*) that the agent thinks with while running the document; hunt restatements a single word can retire.
+- **Pruning** — single source of truth, relevance, and the no-op test applied sentence by sentence, against **sediment** and **sprawl**. Single source of truth reaches past the document into the environment: a doc restating what's already in `package.json`, a config file, or `--help` output is a **cache** of a lookup that was never expensive, and it's the copy that goes stale. Cache what the agent can't find by looking — the unwritten convention, the reason behind a choice.
+
+## Where it fits
+
+This is a reach-for-it-anytime standalone reference — the meta-skill you consult while building the rest of the set, not a step in a chain. When you're unsure which skill or flow fits a task, [ask-matt](https://aihero.dev/skills-ask-matt) routes you over the whole set.

docs/productivity/writing-great-skills.md

@@ -1,45 +0,0 @@
-Quickstart:
-
-```bash
-npx skills add mattpocock/skills --skill=writing-great-skills
-```
-
-```bash
-npx skills update writing-great-skills
-```
-
-[Source](https://github.com/mattpocock/skills/tree/main/skills/productivity/writing-great-skills)
-
-## What it does
-
-`writing-great-skills` is the reference you write and edit skills against — the shared vocabulary and principles that make a skill predictable.
-
-A skill's job is to wrangle determinism out of a stochastic system, so the goal is not the same *output* every run but the same *process*. **Predictability** is the root virtue, and every design choice is judged against it — not against how clever, complete, or exhaustive the skill reads.
-
-## When to reach for it
-
-You invoke this by typing `/writing-great-skills` — the agent won't reach for it on its own.
-
-Reach for it whenever you're authoring a new skill or editing an existing one and want it to behave the same way every time: deciding invocation mode, writing a description, choosing what lives in `SKILL.md` versus a linked file, or diagnosing why a skill misfires.
-
-## Cognitive load
-
-The concept the whole reference turns on is **cognitive load** — and its counterpart, **context load**. Every skill spends one or the other:
-
-- A **model-invoked** skill keeps a description in the window every turn, so it costs **context load** but fires on its own.
-- A **user-invoked** skill strips that description; it costs zero context load, but now *you* are the index that has to remember it exists — that's **cognitive load**.
-
-Most of these skills are user-invoked, which is why cognitive load is the pressure the whole system is built to manage: when user-invoked skills multiply past what you can hold in your head, the cure is a **router skill** that names the others and when to reach for each. Once you're thinking in these two loads, most authoring decisions — split or don't, inline or disclose, model- or user-invoked — become the same trade made in different places.
-
-## The other levers
-
-The rest of the reference is the toolkit for spending those loads well:
-
-- **Leading words** — a compact concept already in the model's pretraining (_tight_, _red_, _tracer bullet_) that the agent thinks with while running the skill. It anchors execution *and* invocation in the fewest tokens; hunt restatements that a single word can retire.
-- **Information hierarchy** — the ladder from in-skill step, to in-skill reference, to external reference behind a **context pointer**. **Progressive disclosure** is the move down that ladder so the top stays legible.
-- **Pruning** — single source of truth, relevance, and the no-op test applied sentence by sentence, against **sediment** and **sprawl**.
-- **Failure modes** — **premature completion**, **duplication**, **sediment**, **sprawl**, **no-op** — to diagnose a skill that isn't behaving.
-
-## Where it fits
-
-This is a reach-for-it-anytime standalone reference — the meta-skill you consult while building the rest of the set, not a step in a chain. Its natural neighbour is any router you maintain, because a router is the direct cure for the cognitive load that user-invoked skills pile up; when you're unsure which skill or flow fits a task, [ask-matt](https://aihero.dev/skills-ask-matt) routes you over the whole set.

skills/engineering/ask-matt/SKILL.md

@@ -70,8 +70,9 @@ Off the main flow entirely.
 - **`/grill-me`** — the same relentless interview as `/grill-with-docs`, but for when you have **no codebase**. Stateless: it saves nothing locally, builds no `CONTEXT.md`. Reach for it to sharpen any plan or design that doesn't live in a repo.
 - **`/prototype`** — a small, throwaway program that answers one design question: does this state model feel right, or what should this UI look like. Throwaway from day one — keep the answer, delete the code. It's the detour in step 2 of the main flow, but reach for it any time a design question is hard to settle on paper.
 - **`/research`** — delegate reading legwork to a **background agent**: it investigates a question against **primary sources**, then leaves a cited Markdown file in the repo. Keep working while it reads. The file it produces is something to take *into* the main flow at `/grill-with-docs` — research feeds the thinking, it doesn't replace it.
+- **`/to-questionnaire`** — when the thing blocking you isn't in your head or the codebase but in **someone else's**, this writes them a questionnaire to fill in. It's the inverse of `/grill-me`: instead of interviewing you about the subject, it interviews you about the **send** — who it's going to, what you need back — and aims the questions at the gap. What comes back is material for `/grill-with-docs` or `/to-spec`.
 - **`/teach`** — learn a concept over multiple sessions, using the current directory as a stateful workspace.
-- **`/writing-great-skills`** — reference for writing and editing skills well.
+- **`/writing-for-agents`** — reference for writing documents agents consume: skills, AGENTS.md, pointed-at docs.
 
 ## Precondition
 

skills/engineering/triage/SKILL.md

@@ -73,7 +73,7 @@ Show counts and a one-line summary per item. Let the maintainer pick.
 
 3. **Verify the claim.** Before any grilling, check that the claim holds up. For a bug, reproduce it from the reporter's steps. For a PR, confirm the diff does what it claims — check it out, run the relevant tests or commands. Report what happened: confirmed (with code path), failed, or insufficient detail (a strong `needs-info` signal). A confirmed verification makes a much stronger agent brief.
 
-4. **Grill (if needed).** If the request needs fleshing out, run the `/grilling` and `/domain-modeling` skills together — grill it into shape one question at a time, sharpening domain terms and updating `CONTEXT.md`/ADRs inline as decisions land.
+4. **Grill (if needed).** If the request needs fleshing out, run the `/grilling` and `/domain-modeling` skills together — grill it into shape a round of questions at a time, sharpening domain terms and updating `CONTEXT.md`/ADRs inline as decisions land.
 
 5. **Apply the outcome:**
    - `ready-for-agent` — post an agent brief comment ([AGENT-BRIEF.md](AGENT-BRIEF.md)).

skills/engineering/wayfinder/SKILL.md

@@ -14,7 +14,7 @@ Wayfinder is **planning** by default: each ticket resolves a decision, and the m
 
 ## Refer by name
 
-Every map and ticket is an issue, so it has a **name** — its title. In everything the human reads — narration, the map's Decisions-so-far — refer to it by that name, never by a bare id, number, or slug. A wall of `#42, #43, #44` is illegible; names read at a glance. The id and URL don't vanish — a name wraps its link — but they ride *inside* the name, never stand in for it.
+Every map and ticket is an issue, so it has a **name** — its title. In everything the human reads — narration, the map's Decisions-so-far — refer to it by that name, never by a bare id, number, or slug. A wall of `#42, #43, #44` is illegible; names read at a glance. The id and URL don't vanish — a name wraps its link — but they ride _inside_ the name, never stand in for it.
 
 ## The Map
 
@@ -72,12 +72,12 @@ The answer isn't part of the body — it's recorded on resolution (see [Work thr
 
 ## Ticket Types
 
-Every ticket is either **HITL** — human in the loop, worked *with* a human who speaks for themselves — or **AFK**, driven by the agent alone. A HITL ticket only resolves through that live exchange; the agent never stands in for the human's side of it (a grilling agent that answers its own questions has broken this).
+Every ticket is either **HITL** — human in the loop, worked _with_ a human who speaks for themselves — or **AFK**, driven by the agent alone. A HITL ticket only resolves through that live exchange; the agent never stands in for the human's side of it (a grilling agent that answers its own questions has broken this).
 
 - **Research** (AFK): Reading documentation, third-party APIs, or local resources like knowledge bases to surface a fact a decision waits on. Resolved by a `/research` **subagent**. Use when knowledge outside the current working directory is required.
 - **Prototype** (HITL): Raise the fidelity of the discussion by making a cheap, rough, concrete artifact to react to — an outline, a rough take, a stub, or UI/logic code via the /prototype skill. Links the prototype as an asset. Use when "how should it look" or "how should it behave" is the key question.
-- **Grilling** (HITL): Conversation via the /grilling and /domain-modeling skills, one question at a time. The default case.
-- **Task** (HITL or AFK): Manual work that must happen before a *decision* can be made — nothing to decide, prototype, or research, but the discussion is blocked until it's done. Signing up for a service so its API can be judged, provisioning access, moving data so its shape can be seen. This is the one type that *does* rather than decides — and it earns its place by unblocking a decision, not by delivering the destination. The agent drives it alone where it can (AFK); otherwise it hands the human a precise checklist (HITL). Resolved when the work is done; the answer records what was done and any resulting facts (credentials location, new URLs, row counts) later tickets depend on.
+- **Grilling** (HITL): Conversation. The default case. Always invoke the /grilling and /domain-modeling skills.
+- **Task** (HITL or AFK): Manual work that must happen before a _decision_ can be made — nothing to decide, prototype, or research, but the discussion is blocked until it's done. Signing up for a service so its API can be judged, provisioning access, moving data so its shape can be seen. This is the one type that _does_ rather than decides — and it earns its place by unblocking a decision, not by delivering the destination. The agent drives it alone where it can (AFK); otherwise it hands the human a precise checklist (HITL). Resolved when the work is done; the answer records what was done and any resulting facts (credentials location, new URLs, row counts) later tickets depend on.
 
 ## Fog of war
 

skills/in-progress/README.md

@@ -9,4 +9,3 @@ Skills that are still being developed. They're not ready to ship — expect roug
 - **[writing-shape](./writing-shape/SKILL.md)** — Take a markdown file of raw material and shape it into an article paragraph by paragraph, arguing format choices at each step.
 - **[claude-handoff](./claude-handoff/SKILL.md)** — Hand the current conversation off to a fresh background agent that picks up the work immediately, seeded with a handoff summary via `claude --bg`. User-invoked.
 - **[setup-ts-deep-modules](./setup-ts-deep-modules/SKILL.md)** — Wire dependency-cruiser into a TypeScript repo so each package is a deep module — implementation hidden in subfolders, reachable only through its entry-point files, tests exercising it through those. User-invoked.
-- **[to-questionnaire](./to-questionnaire/SKILL.md)** — Turn a decision you can't fully answer into a Markdown questionnaire for someone else to fill in async, or over a meeting. It grills you about the send (who it's for, what you need back), not the subject. User-invoked.

skills/in-progress/loop-me/SKILL.md

@@ -5,7 +5,7 @@ disable-model-invocation: true
 argument-hint: "A workflow to design, or nothing to go find one"
 ---
 
-Run a stateful `/grilling` session whose only output is **workflow** specs. Use the grilling discipline — relentless, one question at a time, a recommended answer attached to each — aimed at the vocabulary and goal below. Create, edit, and delete specs as the grilling resolves things.
+Run a stateful `/grilling` session whose only output is **workflow** specs. Use the grilling discipline — relentless, a round of questions at a time, a recommended answer attached to each — aimed at the vocabulary and goal below. Create, edit, and delete specs as the grilling resolves things.
 
 ## The loop lens
 

skills/productivity/README.md

@@ -9,7 +9,8 @@ Reachable only when you type them (Claude Code: `disable-model-invocation: true`
 - **[grill-me](./grill-me/SKILL.md)** — Get relentlessly interviewed about a plan or design until every branch of the decision tree is resolved.
 - **[handoff](./handoff/SKILL.md)** — Compact the current conversation into a handoff document so another agent can continue the work.
 - **[teach](./teach/SKILL.md)** — Teach the user a new skill or concept over multiple sessions, using the current directory as a stateful teaching workspace.
-- **[writing-great-skills](./writing-great-skills/SKILL.md)** — Reference for writing and editing skills well: the vocabulary and principles that make a skill predictable.
+- **[to-questionnaire](./to-questionnaire/SKILL.md)** — Turn a decision you can't answer alone into a Markdown questionnaire for the one person who can — filled in async, or together over a meeting.
+- **[writing-for-agents](./writing-for-agents/SKILL.md)** — Writing documents for agents: skills, AGENTS.md/CLAUDE.md, and any doc an agent reaches by a pointer.
 
 ## Model-invoked
 

skills/productivity/grilling/SKILL.md

@@ -7,6 +7,14 @@ Interview the user relentlessly until you reach a shared understanding. Map this
 
 Work the tree in **rounds**. The **frontier** is every decision whose prerequisites are already settled — the questions you can ask _now_ without guessing at answers you haven't heard yet. Ask the whole frontier in one round: number each question and give your recommended answer. Then wait for the user's answers before the next round.
 
+Each question should be formatted like so:
+
+```
+❓ **Q1** - **<question title>**: <question body, might be multiple paragraphs, including multiple choices>
+
+➡️ <your recommended answer>
+```
+
 Each round the user answers reshapes the tree — settled decisions push the frontier outward and unblock questions that depended on them. Recompute the frontier and ask the next round. A question whose answer depends on another question still open in this round belongs to a _later_ round, not this one.
 
 Finding _facts_ is your job, never the user's. When a frontier question needs a fact from the environment (filesystem, tools, etc.), dispatch a sub-agent to find it — don't ask the user for anything you could look up yourself. Don't block on it: a running exploration is an unsettled prerequisite, so only the questions downstream of it wait for the sub-agent to report — ask the rest of the frontier now. The _decisions_ are the user's — put each to them and wait.

skills/productivity/grilling/agents/openai.yaml

@@ -1,3 +1,3 @@
 interface:
   display_name: "Grilling"
-  short_description: "Stress-test thinking one question at a time"
+  short_description: "Stress-test thinking a round of questions at a time"

skills/productivity/writing-for-agents/SKILL-MECHANICS.md

@@ -0,0 +1,22 @@
+# Skill mechanics
+
+The skill-specific branch of [`writing-for-agents`](SKILL.md): what changes when the document is a skill — frontmatter, the invocation choice, and router skills. Everything else about writing it is the universal reference in `SKILL.md`.
+
+## Invocation
+
+Two choices, trading the two loads:
+
+- A **model-invoked** skill keeps a `description`, so the agent can fire it autonomously — and other skills can reach it. You can still type its name: model-invocation always _includes_ user reach; a description only ever adds agent discovery, never removes the human's. The description is the skill's top-level context pointer, forced to stay loaded at all times — permanent context load in exchange for discoverability. A model-invoked skill whose content is all reference is also one home for shared reference: another skill can invoke it, so reference needed by several skills lives in one place. Mechanics: omit `disable-model-invocation`, and write a model-facing description carrying the trigger branches (the pointer-writing rules in `SKILL.md` apply in full).
+- A **user-invoked** skill strips the description from the agent's reach: only the human typing its name can invoke it, and no other skill can. Zero context load, but it spends cognitive load — you are the index that must remember it exists. Mechanics: set `disable-model-invocation: true`; the `description` becomes human-facing — a one-line summary, trigger lists stripped.
+
+Pick model-invocation only when the agent must reach the skill on its own, or another skill must. If it only ever fires by hand, make it user-invoked and pay no context load.
+
+Shared reference that two user-invoked skills both need can live in neither — with no descriptions, neither can fire the other. Push it to a plain file outside the skill system: external reference any skill can point at.
+
+## Splitting by invocation
+
+The invocation cut of splitting (the sequence cut lives in `SKILL.md`): split off a model-invoked skill when you have a distinct leading word that should trigger it on its own — a trigger word you actually use in your prompts — or another skill must reach it. You pay context load for the new always-loaded description, so that independent reach has to be worth it.
+
+## Router skills
+
+When user-invoked skills multiply past what you can remember, that piled-up cognitive load is cured by a **router skill**: one user-invoked skill that names the others and when to reach for each, so the human has one skill to remember instead of many. It can only hint, never fire them: user-invoked skills have no description, so nothing but the human can reach them.

skills/productivity/writing-for-agents/SKILL.md

@@ -0,0 +1,81 @@
+---
+name: writing-for-agents
+description: Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.
+---
+
+Reference for writing any document an agent consumes — a skill, an `AGENTS.md` / `CLAUDE.md`, a doc reached by a pointer. The packaging differs; the writing does not: the same levers make each one predictable — the agent taking the same _process_ every run, not producing the same output.
+
+When the document you're writing is a skill, read [`SKILL-MECHANICS.md`](SKILL-MECHANICS.md) for frontmatter, invocation choice, and router skills.
+
+## Context pointers
+
+A **context pointer** is a reference held in the agent's context that names some out-of-context material and encodes the condition for reaching it. A skill's description is one; a line in `AGENTS.md` naming a doc is the same object. The pointer's _wording_, not its target, decides when the agent reaches the material — and how reliably. A must-have target behind a weakly worded pointer is a variance bug: sharpen the wording first, and inline the material only if sharpening fails.
+
+A pointer does two jobs — state what the material is, and list the **branches** that should trigger reaching it (a branch is a distinct case the document handles, so different runs take different paths through it). Every word of an always-loaded pointer costs on every turn, so it earns even harder pruning than the body:
+
+- **Front-load the leading word** — the pointer is where it does its triggering work.
+- **One trigger per branch.** Synonyms that rename a single branch are one branch written twice; collapse them and keep only genuinely distinct branches.
+- **Cut identity the body already carries.**
+
+## The two loads
+
+Every document and pointer you add spends one of two budgets:
+
+- **Context load** — the cost of always-loaded material on the agent's window: an `AGENTS.md` line, a skill description, anything sitting in context every turn, spending tokens and attention whether or not it fires.
+- **Cognitive load** — the cost on the human: which documents exist and when to reach for each. The human is the index. Not a cost to minimise — it is the price of human agency; spend it where human judgement matters, remove it where it does not.
+
+Material reached only through a pointer escapes context load at the price of the pointer's own line; material with no pointer at all rides entirely on cognitive load.
+
+## Information hierarchy
+
+A document is built from two content types — **steps** (the ordered actions the agent performs) and **reference** (definitions, rules, facts consulted on demand) — that mix freely: all steps (a recipe), all reference (a review's rules, this skill), or both. The core decision is where each piece sits on the **information hierarchy**, a ladder ranked by how immediately the agent needs the material:
+
+1. **In-file step** — the primary tier: what the agent does, in order.
+2. **In-file reference** — consulted on demand. Often a legitimately flat peer-set (every rule of a review on one rung) — a fine arrangement, not a smell.
+3. **Disclosed reference** — pushed out into a separate file, reached by a context pointer, loaded only when the pointer fires. Spans a sibling file in the same folder through fully external reference that lives anywhere and any document can point at.
+
+Push too little down and the top bloats; push too much and you hide material the agent actually needs. That tension is the whole decision.
+
+**Progressive disclosure** is the move down the ladder — out of the main file and behind a pointer — so the top stays legible. Not primarily a token optimisation: it is how the hierarchy is protected. Branching is the cleanest disclosure test: inline what every branch needs, and push behind a pointer what only some branches reach. When a document has steps, in-file reference that should be disclosed buries them and turns attending to them into a coin-flip — a variance lever, not just a legibility one.
+
+**Co-location** is the within-file companion: where the ladder decides _how far down_ a piece sits, co-location decides _what sits beside it_ once there. Keep a concept's definition, rules, and caveats under one heading rather than scattered, so reading one part brings its neighbours with it. The test: the document should read like documentation written for the agent — grouped material reads that way; scattered material does not. (Distinct from duplication: that repeats one meaning in two places; scattering fragments one meaning across many.)
+
+**Sprawl** is the failure mode here: a document simply too long, even when every line is live and unique. Attention thins across the excess, and every extra line is one more to keep relevant. The cure is the ladder: disclose reference behind pointers, and split by branch or sequence so each path carries only what it needs.
+
+## Steps and completion criteria
+
+Every step ends on a **completion criterion** — the condition that tells the agent the work is done. Two properties make it a lever:
+
+- **Clarity** — can the agent tell done from not-done? A vague bound ("understanding reached") invites **premature completion**: ending the step before it is genuinely done, attention slipping to _being done_. The visible steps still ahead — the **post-completion steps** — supply the pull; the criterion's clarity is the resistance. Defend in order: **sharpen the bound first** (local and cheap); only if it is irreducibly fuzzy _and_ you observe the rush, hide the later steps by splitting the sequence — and hiding only works across a real context boundary (a hand-off or a subagent dispatch; an inline call leaves the later steps in context and clears nothing).
+- **Demand** — how much it requires. "Every modified model accounted for" forces thorough work where "produce a change list" does not. Demand drives **legwork** — the digging the agent does within the work, latent in the wording rather than written as its own step — and it is not step-bound: "every rule applied" binds a body of flat reference just as "every step done" binds a sequence, which is how an all-reference document still carries an exhaustiveness bar.
+
+The strongest criteria are both checkable and exhaustive.
+
+## When to split
+
+Splitting one document into two spends one of the two loads, so split only when the cut earns it:
+
+- **By sequence** — split a run of steps where the post-completion steps tempt the agent to rush the one in front of it. Keeping them out of view drives more legwork on the current task. Beware the reverse: merging sequences exposes each step's later steps to what follows, inviting premature completion.
+- **By invocation** — skill-specific: see [`SKILL-MECHANICS.md`](SKILL-MECHANICS.md).
+
+## Leading words
+
+A **leading word** is a compact concept already living in the model's pretraining that the agent thinks with while running the document (_lesson_, _fog of war_, _tracer bullets_). Repeated as a token, never as a sentence, it accumulates a distributed definition and anchors a whole region of behaviour in the fewest tokens, by recruiting priors the model already holds. Coining your own works if you define it clearly, but a made-up word recruits no priors — you pay in definition tokens what a pretrained word gives free; reach for an existing word first.
+
+It anchors twice. In the body, _execution_: the agent reaches for the same behaviour every time the word appears, and inside flat reference it focuses attention on a class of thing to look for. In a pointer, _invocation_: when the same word lives in your prompts, your docs, and your codebase, the agent links that shared language to the material and reaches it more reliably.
+
+Hunt for opportunities to refactor with leading words. A triad spelled out at three sites, a pointer spending a sentence to gesture at one idea — each is a passage begging to collapse into a single token:
+
+- "fast, deterministic, low-overhead" → _tight_ (a _tight_ loop).
+- "a loop you believe in" → _red_ — a fuzzy gate becomes a binary observable state (the loop goes _red_ on the bug, or it doesn't).
+
+You win twice: fewer tokens, and a sharper hook for the agent to hang its thinking on. Assume every document is carrying restatements that leading words retire — go find them.
+
+**Negation** is the failure mode beside this lever: steering by prohibition drags the forbidden behaviour into context and makes it _more_ available, not less. _Don't think of an elephant_, and the elephant is all there is; the negation is a weak modifier the strongly-activated concept overruns, so the ban half-reads as an instruction to do the thing. Prompt the **positive** — state the target behaviour ("write one-line comments") so the banned one is never spoken. A prohibition earns its place only as a hard guardrail you cannot phrase positively; even then, pair it with the positive target so attention lands on what to do.
+
+## Pruning
+
+- Keep each meaning in a **single source of truth**: one authoritative place, so changing the behaviour is a one-place edit. **Duplication** — the same meaning in more than one place — costs maintenance and tokens, and inflates a meaning's prominence on the ladder past its real rank. (The accidental inverse of a leading word, which repeats a token on purpose, never the meaning.)
+- The **environment** is a source of truth too — `package.json` scripts, config files, the directory layout, `--help` output — and a document that restates it is a **cache**: a copy of a lookup, earning its load only when the lookup is expensive. Cache what the agent cannot find by looking: the unwritten convention, the reason behind a choice, the gotcha no config confesses. Leave the one-file, one-command lookups to the environment, where they cannot go stale.
+- Check every line for **relevance**: does it still bear on what the document does? A line loses relevance by never bearing on the task (mere exposition, or a branch that should be disclosed) or by going stale as the behaviour or world it describes changes. Shorter documents are easier to keep relevant. Without a pruning discipline the default fate is **sediment**: stale layers that settle because adding feels safe and removing feels risky, until you must core down through them to find what is still live.
+- Hunt **no-ops** sentence by sentence: an instruction the model already obeys by default pays load to say nothing. The test — does it change behaviour versus the default? — is model-relative, not reader-relative: two people disagreeing about a no-op disagree about the default, and settle it by running the document, not by debate. When a sentence fails, delete the whole sentence rather than trim words from it. The test also grades leading words: a word too weak to beat the default (_be thorough_ when the agent is already thorough-ish) is a no-op, and the fix is a stronger word (_relentless_), not a different technique.

skills/productivity/writing-great-skills/GLOSSARY.md

@@ -1,201 +0,0 @@
-# Glossary — Building Great Skills
-
-The domain model for what makes a skill great. A skill exists to wrangle determinism out of a stochastic system; the root virtue is **Predictability**, and every term below is a lever on it. This is the disclosed reference for [`writing-great-skills`](SKILL.md).
-
-The terms are grouped by axis: **Invocation** (how a skill is reached), **Information Hierarchy** (how its content is arranged), **Steering** (how the agent's runtime behaviour is shaped), and **Pruning** (how it is kept lean). Each **failure mode** lives beside the lever that cures it, tagged _failure mode_.
-
-**Bold terms** in any definition are themselves defined in this glossary; find them by their heading.
-
-## Predictability
-
-The degree to which a skill makes the agent behave the same _way_ on every run — the same process, not the same output (a brainstorming skill should _predictably_ diverge; its tokens vary, its behaviour doesn't). The root virtue every other term serves — cost and maintainability are symptoms of it, not rivals.
-
-_Avoid_: consistency, reliability, robustness, output-determinism
-
-## Invocation
-
-How a skill is reached — and the two loads you pay for the choice.
-
-### Model-Invoked
-
-A skill that keeps its **description** field, so the agent can see it and fire it autonomously — and the human can still type its name, so model-invocation always _includes_ user reach. There is no model-only state: a description only ever _adds_ agent discovery, never removes the human's. Pays a permanent **context load** on every turn in exchange for that discoverability. Reachable by other skills, because the description that makes it agent-discoverable makes it invocable. A model-invoked skill whose content is all **reference** is also one home for shared reference: another skill can invoke it, so reference needed by several skills lives in one place. Pick model-invocation only when the agent must reach the skill on its own; if it never fires except by hand, drop the description and pay no context load.
-
-_Avoid_: ability, tool, capability
-
-### User-Invoked
-
-A skill with its **description** stripped — invisible to the agent and reachable only by the human typing its name (user-_only_, where **model-invoked** is user-_and-agent_). Trades agent-discoverability for zero **context load**. Because it has no description, nothing but the human can reach it: no other skill can fire it.
-
-_Avoid_: procedure, workflow, command
-
-### Description
-
-The skill's machine-readable trigger, and the one **context pointer** a **model-invoked** skill is forced to keep loaded at all times. Its mere presence _is_ the invocation axis: keep it and the skill is model-invoked (and reachable by other skills); delete it and the skill is **user-invoked**, reachable only by the human. The source of a model-invoked skill's **context load**.
-
-_Avoid_: frontmatter, summary
-
-### Context Pointer
-
-A reference held in the agent's context that names some out-of-context material and encodes the condition for reaching it. The **description** is the top-level context pointer (context window → skill); pointers to disclosed files are the same object one level down. Its wording, not the target, decides _when_ the agent reaches — and _how reliably_. A must-have target behind a weakly worded pointer is a variance bug: fix the wording first, and inline the material only if sharpening fails.
-
-_Avoid_: link, reference, import
-
-### Context Load
-
-The cost a **model-invoked** skill imposes on the agent's context window — its **description**, always loaded, spending both tokens and attention. What **user-invoked** skills escape by having no description, and the brake on splitting into more model-invoked skills.
-
-_Avoid_: token cost, context bloat
-
-### Cognitive Load
-
-The cost a **user-invoked** skill imposes on the human — what they must hold in their head: which skills exist and when to reach for each (the human is the index). What **model-invocation** removes by being agent-discoverable, and the brake on splitting into more user-invoked skills. Not a cost to minimise: it is the price of human agency, the reason some skills stay user-invoked. Spend it where human judgement matters; remove it where it does not.
-
-_Avoid_: human index, burden, overhead
-
-### Router Skill
-
-A **user-invoked** skill whose job is to point at your other user-invoked skills — naming each and when to reach for it — so the human has one skill to remember instead of many. It can only hint, never fire them: user-invoked skills have no **description**, so nothing but the human can reach them. The cure for **cognitive load** when user-invoked skills multiply.
-
-_Avoid_: dispatcher, menu, registry, index, router procedure
-
-### Granularity
-
-How finely you divide skills. Finer division spends one of the two loads: more **model-invoked** skills spend **context load** (more descriptions crowding the window and competing for attention); more **user-invoked** skills spend **cognitive load** (more for the human to remember and reach for). Two cuts guide the division. By **invocation**, split off a model-invoked skill where you have a distinct **leading word** to trigger it — a trigger word you actually use in your prompts. By **sequence**, split a run of **steps** where a step's **post-completion steps** need hiding, since isolating it in its own context clears what follows. Beware the reverse: merging sequences exposes each step's post-completion steps to what follows, inviting premature completion.
-
-_Avoid_: chunking, modularity
-
-## Information Hierarchy
-
-How a skill's content is arranged, and how far down the ladder each piece sits.
-
-### Information Hierarchy
-
-A skill's content ranked by how immediately the agent needs it — a single ladder, produced by two cuts: in-file or behind a pointer, and step or reference. The rungs:
-
-- **Steps** — in-file, primary
-- **Reference**, in-file — secondary
-- **Reference**, disclosed — behind a **context pointer**
-
-A skill with no **steps** uses just the bottom two rungs — often a legitimately flat peer-set (e.g. every rule of a review on one rung), which is a fine arrangement, not a smell. The hierarchy is independent of invocation: a skill can be model- or user-invoked whether it is all steps, all reference, or both. When a skill has steps, in-file reference that should be disclosed buries them and turns attending to them into a coin-flip — a variance lever, not just a legibility one. Keep the top of the ladder legible; push down it whatever you can.
-
-_Avoid_: structure, organization, layout
-
-### Steps
-
-The ordered actions the agent performs — when a skill has them, the primary tier of its content, and the part that earns its place in SKILL.md. Not every skill has steps: a skill can be all steps (`tdd`), all **reference** (a review), or both, independent of invocation. Every step ends on a **completion criterion**, clear or vague.
-
-_Avoid_: workflow, instructions, choreography
-
-### Reference
-
-Material the agent refers to on demand — definitions, facts, parameters, examples, conditional instructions. When a skill has **steps** it is secondary to them; when a skill has none it is the entire content; or it lives outside any skill entirely — see **External Reference**. Reached via **context pointers**, and the prime candidate for **progressive disclosure**.
-
-_Avoid_: supporting material, docs, background
-
-### External Reference
-
-**Reference** that lives outside the skill system — a plain file, no **description**, no **steps**, not invocable — that any skill can point at. The home for shared reference that needn't fire on its own, and the only shared home two **user-invoked** skills can use, since neither has a description and so neither can fire the other.
-
-_Avoid_: doc, resource, knowledge base
-
-### Progressive Disclosure
-
-Moving **reference** down the ladder — out of SKILL.md and behind a **context pointer** — so the top stays legible. Not primarily a token optimisation; it is how the **information hierarchy** is protected. Licensed by **branching**: disclose what only some branches need, inline what every path needs, and if a pointer fires unreliably on must-have material, sharpen its wording, and pull it back inline only if that fails.
-
-_Avoid_: lazy loading, chunking
-
-### Co-location
-
-Keeping the material an agent needs at once in one place — a concept's definition, rules, and caveats under a single heading, not scattered across the file — so reading one part brings its neighbours with it. The within-file companion to the **Information Hierarchy**: the hierarchy ranks _how far down_ a piece sits; co-location decides _what sits beside it_ once there. There is no formula for the right format of a body of **reference**; the test is that a skill should read like documentation written for the agent, and grouped material reads that way where scattered material does not. Distinct from **Duplication**: that repeats one meaning in two places, where scattering fragments a single meaning across many.
-
-_Avoid_: grouping, clustering, cohesion
-
-### Sprawl
-
-_Failure mode._ A skill that is simply too long — too many lines in SKILL.md — independent of whether they are stale or repeated. Even an all-live, all-unique skill can sprawl. It costs readability (the agent wades through more before it can act, and attention thins across the excess), maintainability (every extra line is one more to keep **relevant**), and tokens. The cure is the **information hierarchy**: push **reference** down behind **context pointers**, and split by **branch** or sequence so each path carries only what it needs. Distinct from **sediment** (length from stale accumulation) and **duplication** (length from repeated meaning) — sprawl is length itself, whatever its cause.
-
-_Avoid_: bloat, length, size, verbosity
-
-## Steering
-
-The levers that shape the agent's runtime behaviour toward **Predictability**.
-
-### Branch
-
-A distinct way a skill can be invoked — a case the skill handles — so different runs take different paths through it. A skill with many steps may carry many branches; a linear one has none.
-
-_Avoid_: path, case, fork
-
-### Leading Word
-
-A compact concept — also called a _Leitwort_ — already living in the model's pretraining, that the agent thinks with while running the skill. It encodes a behavioural principle in the fewest possible tokens by invoking priors the model already holds (e.g. _lesson_, _proximal zone of development_, _fog of war_, _tracer bullets_). Repeated as a token, never as a sentence, it accumulates a distributed definition across the skill and anchors a whole region of behaviour. Coining your own works if you define it clearly, but a made-up word recruits no priors — you pay in definition tokens what a pretrained word gives free. Reach for an existing word first.
-
-A leading word serves **predictability** twice. In the body it anchors **execution** — the agent reaches for the same behaviour every time the concept appears, and inside flat reference it focuses attention on a class of thing to look for, recruiting the right checks each run. In the **description** it anchors **invocation** — and not only within the skill: when the same word lives in your prompts, your docs, and your codebase, the agent links that shared language to the skill and fires it more reliably. Word a description with the leading words you actually use when you want the skill.
-
-_Avoid_: keyword, term, motif
-
-### Completion Criterion
-
-The condition that tells the agent a unit of work is done — the target it judges against. Two properties make it a lever, not just a quality. Its **clarity** (can the agent tell done from not-done?) resists **premature completion** — a vague bound ("understanding reached") lets the agent declare done and slip to the next step; this axis needs _steps_ to bite, since premature completion is a between-steps failure. Its **demand** (how much it requires) sets **legwork** — "every modified model accounted for" forces thorough work where "produce a change list" does not — and this axis is _not_ step-bound: it can bind a body of flat reference too, which is how a skill with no steps still carries an exhaustiveness bar ("every rule applied"). The strongest criteria are both checkable and exhaustive.
-
-_Avoid_: done condition, exit condition, stopping rule
-
-### Legwork
-
-The work an agent does behind the scenes within a single step — reading files, exploring the codebase, making changes, digging up what it needs rather than offloading to the user. It lives below the step structure: never written as its own step, latent in the wording, controlled by the agent rather than the skill. The within-step counterpart to **post-completion steps**' across-step pull. Raised by a **leading word** (_comprehensive_, _thorough_) or a **completion criterion** that demands the work be exhaustive — including the demand axis applied to flat reference, which is what drives a skill of flat reference to cover all its rungs. Goes thin either when that demand is missing or when **premature completion** cuts the step short.
-
-_Avoid_: scope, effort, diligence, coverage
-
-### Post-Completion Steps
-
-The **steps** that follow the current step. Visible, they pull the agent forward into **premature completion** — the more it sees, the stronger the tug; the defence is to hide them by splitting the sequence of steps into two.
-
-_Avoid_: horizon, fog of war, lookahead
-
-### Premature Completion
-
-_Failure mode._ Ending the current step before it is genuinely done, because the agent's attention slips to being done rather than to the work. A between-steps failure: it needs **steps** to occur — a skill with no steps that quits early isn't premature completion but thin **legwork** under an unmet demand. A tug-of-war between two forces: visible **post-completion steps** (the pull forward) and the **completion criterion**'s clarity (the resistance — a sharp, checkable bar holds; a vague one gives way). Fuzziness is the necessary condition: a sharp bound resists the pull no matter how many later steps are visible, so a step that never rushes needs no defending. Two levers hold a step that does, but reach for them in order: **sharpen the bound first** — it is local and cheap. Only when the criterion is irreducibly fuzzy _and_ you actually observe the rush do you **hide the later steps** — and hiding only works across a real context boundary (a user-invoked hand-off or a subagent dispatch; an inline model-invoked call leaves the later steps in context and clears nothing). One cause of thin legwork, but distinct from it: legwork can be thin even when a step runs to full completion.
-
-_Avoid_: premature closure, the rush, rushing, shortcutting
-
-### Negation
-
-_Failure mode._ Steering by prohibition — telling the agent what _not_ to do — which drags the forbidden behaviour into context and makes it _more_ available, not less. _Don't think of an elephant_, and the elephant is all there is; _never write verbose comments_, and verbosity is the pattern the agent has just read. The negation is a weak modifier the strongly-activated concept overruns, so the ban half-reads as an instruction to do the thing. Its **leading word** is the _elephant_: whatever a prohibition names into the frame. Cure: prompt the **positive** — describe the target behaviour ("write one-line comments") so the banned one is never spoken. A prohibition earns its place only as a hard guardrail on a behaviour you cannot phrase positively; even then, pair it with the positive target so attention lands on what to do.
-
-_Avoid_: ironic rebound, don't-prompting, the pink elephant
-
-## Pruning
-
-Keeping a skill lean — each remedy paired with the failure it cures.
-
-### Single Source of Truth
-
-The desired state where each meaning lives in exactly one authoritative place, so a change to the skill's behaviour is a change in one place. **Duplication** is its violation.
-
-_Avoid_: home, canonical location
-
-### Duplication
-
-_Failure mode._ The same meaning given more than one **single source of truth**. It costs maintenance (change one place, you must change the others), costs tokens, and inflates prominence — repeating a meaning weights it on the ladder past its real rank. The accidental inverse of a **leading word**, which raises attention on purpose by repeating a token, never the meaning.
-
-_Avoid_: repetition, redundancy
-
-### Relevance
-
-Whether a line still bears on what the skill does — the lens for what to keep. A line loses relevance either by never bearing on the task (mere exposition, or a **branch** that should be disclosed) or by going stale: drifting out of date as the behaviour or world it describes changes. Shorter skills are easier to keep relevant, because each line is cheaper to check. Distinct from **no-op**: relevance asks whether a line bears on the task, not whether it changes behaviour.
-
-_Avoid_: load-bearing, staleness, freshness
-
-### Sediment
-
-_Failure mode._ Layers of old content that settle in a skill and are never cleared, because adding feels safe and removing feels risky — so stale and irrelevant lines accumulate and you must core down through them to find what is still live. The default fate of any skill without a pruning discipline; the slow erosion of **relevance**, as opposed to **duplication**'s repeated meaning.
-
-_Avoid_: accretion, bloat, cruft, rot
-
-### No-Op
-
-_Failure mode._ An instruction that changes nothing because the model already does it by default — you pay load to tell the agent what it would do anyway. The test: does a line change behaviour versus the default? A line can be perfectly **relevant** and still be a no-op. The same priors that make a **leading word** free make a no-op worthless.
-
-A leading word is a _technique_; No-Op is a _verdict_ on a line — and they cross. A leading word too weak to beat the default is a no-op (_be thorough_ when the agent is already thorough-ish), and the fix is a stronger word that passes the verdict (_relentless_), not a different technique. So the No-Op test — does it change behaviour versus the default? — is also how you grade whether a leading word is earning its repetitions. This is model-relative, not reader-relative: two people disagreeing over whether a line is a no-op disagree about the default, and settle it by running the skill, not by debate.
-
-_Avoid_: redundant instruction, restating the obvious, belaboring

skills/productivity/writing-great-skills/SKILL.md

@@ -1,83 +0,0 @@
----
-name: writing-great-skills
-description: Reference for writing and editing skills well — the vocabulary and principles that make a skill predictable.
-disable-model-invocation: true
----
-
-A skill exists to wrangle determinism out of a stochastic system. **Predictability** — the agent taking the same _process_ every run, not producing the same output — is the root virtue; every lever below serves it.
-
-**Bold terms** are defined in [`GLOSSARY.md`](GLOSSARY.md); look them up there for the full meaning.
-
-## Invocation
-
-Two choices, trading different costs:
-
-- A **model-invoked** skill keeps a **description**, so the agent can fire it autonomously _and_ other skills can reach it (you can still type its name too). It contributes to **context load** — the description sits in the window every turn. Mechanics: omit `disable-model-invocation`, and write a model-facing description with rich trigger phrasing ("Use when the user wants…, mentions…").
-- A **user-invoked** skill strips the description from the agent's reach: only you, typing its name, can invoke it — and no other skill can. Zero context load, but it spends **cognitive load**: _you_ are the index that must remember it exists. Mechanics: set `disable-model-invocation: true`; the `description` becomes human-facing — a one-line summary, trigger lists stripped.
-
-Pick model-invocation only when the agent must reach the skill on its own, or another skill must. If it only ever fires by hand, make it user-invoked and pay no context load.
-
-When user-invoked skills multiply past what you can remember, that piled-up cognitive load is cured by a **router skill**: one user-invoked skill that names the others and when to reach for each.
-
-## Writing the description
-
-A model-invoked **description** does two jobs — state what the skill is, and list the **branches** that should trigger it. Every word increases **context load**, so a description earns even harder pruning than the body:
-
-- **Front-load the skill's leading word** — the description is where it does its invocation work.
-- **One trigger per branch.** Synonyms that rename a single branch are **duplication** — "build features using TDD … asks for test-first development" is one branch written twice. Collapse them; keep only genuinely distinct branches.
-- **Cut identity that's already in the body.** Keep the description to triggers, plus any "when another skill needs…" reach clause.
-
-## Information hierarchy
-
-A skill is built from two content types — **steps** and **reference** — that mix freely: a skill can be all steps, all reference, or both. The core decision is which to use and where each sits on the **information hierarchy**, a ladder ranked by how immediately the agent needs the material:
-
-1. **In-skill step** — an ordered action in `SKILL.md`, the primary tier: what the agent does, in order. Each step ends on a **completion criterion**, the condition that tells the agent the work is done. Make it _checkable_ (can the agent tell done from not-done?) and, where it matters, _exhaustive_ ("every modified model accounted for", not "produce a change list") — a vague criterion invites **premature completion**.
-2. **In-skill reference** — a definition, rule, or fact in `SKILL.md`, consulted on demand. Often a legitimately flat peer-set (every rule of a review on one rung) — a fine arrangement, not a smell. _This skill is all reference._
-3. **External reference** — reference pushed out of `SKILL.md` into a separate file, reached by a **context pointer**, loaded only when the pointer fires. (Spans _disclosed_ reference — a sibling file like `GLOSSARY.md`, still part of the skill — through fully **external reference** that lives outside the skill system and any skill can point at.)
-
-A demanding completion criterion drives thorough **legwork** — the digging the agent does within the work — whether the skill has steps or not, since "every rule applied" binds flat reference just as "every step done" binds a sequence.
-
-Push too little down and the top bloats; push too much and you hide material the agent actually needs. That tension is the whole decision.
-
-**Progressive disclosure** is the move down the ladder — out of `SKILL.md` into a linked file — so the top stays legible. Mechanics: a linked `.md` file in the skill folder, named for what it holds (this skill discloses its full definitions to `GLOSSARY.md`). Some skills are used in more than one way, and each distinct way is a **branch** — different runs taking different paths through the skill. Branching is the cleanest disclosure test: inline what every branch needs, and push behind a pointer what only some branches reach. A **context pointer**'s _wording_, not its target, decides when and how reliably the agent reaches the material.
-
-Where the ladder decides _how far down_ a piece sits, **co-location** decides _what sits beside it_ once there: keep a concept's definition, rules, and caveats under one heading rather than scattered, so reading one part brings its neighbours with it.
-
-## When to split
-
-**Granularity** is how finely you divide skills, and each cut spends one of the two loads, so split only when the cut earns it. Two cuts:
-
-- **By invocation** — split off a **model-invoked** skill when you have a distinct **leading word** that should trigger it on its own, or another skill must reach it. You pay **context load** for the new always-loaded **description**, so that independent reach has to be worth it.
-- **By sequence** — split a run of **steps** when the steps still ahead (a step's **post-completion steps**) tempt the agent to rush the one in front of it (**premature completion**). Keeping them out of view encourages the agent to do more **legwork** on the current task.
-
-## Pruning
-
-Keep each meaning in a **single source of truth**: one authoritative place, so changing the behaviour is a one-place edit.
-
-Check every line for **relevance**: does it still bear on what the skill does?
-
-Then hunt **no-ops** sentence by sentence, not just line by line: run the no-op test on each sentence in isolation, and when one fails, delete the whole sentence rather than trim words from it. Be aggressive — most prose that fails should go, not be rewritten.
-
-## Leading words
-
-A **leading word** is a compact concept already living in the model's pretraining that the agent thinks with while running the skill (e.g. _lesson_, _fog of war_, _tracer bullets_). Repeated throughout the text (though not necessarily - a strong leading word might only be needed once), it accumulates a distributed definition and anchors a whole region of behaviour in the fewest tokens, by recruiting priors the model already holds.
-
-It serves predictability twice. In the body it anchors _execution_: the agent reaches for the same behaviour every time the word appears. In the description it anchors _invocation_: when the same word lives in your prompts, docs, and code, the agent links that shared language to the skill and fires it more reliably.
-
-Hunt for opportunities to refactor skills to use leading words. A triad spelled out at three sites (**duplication**), a description spending a sentence to gesture at one idea — each is a passage begging to **collapse** into a single token. Examples include:
-
-- "fast, deterministic, low-overhead" -> _tight_ — one quality restated across a phase — into a single pretrained word (a _tight_ loop).
-- "a loop you believe in" -> _red_ — converts a fuzzy gate into a binary observable state (the loop goes _red_ on the bug, or it doesn't).
-
-You win twice over: fewer tokens, _and_ a sharper hook for the agent to hang its thinking on. Assume every skill is carrying restatements that leading words retire — go find them.
-
-## Failure modes
-
-Use these to diagnose issues the user may be having with the skill.
-
-- **Premature completion** — ending a step before it's genuinely done, attention slipping to _being done_. Defence, in order: sharpen the completion criterion first (cheap, local); only if it is irreducibly fuzzy _and_ you observe the rush, hide the post-completion steps by splitting (the sequence cut).
-- **Duplication** — the same meaning in more than one place. Costs maintenance and tokens, and inflates a meaning's prominence on the ladder past its real rank.
-- **Sediment** — stale layers that settle because adding feels safe and removing feels risky. The default fate of any skill without a pruning discipline.
-- **Sprawl** — a skill simply too long, even when every line is live and unique. Hurts readability and maintainability and wastes tokens. The cure is the ladder: disclose **reference** behind pointers, and split by **branch** or sequence so each path carries only what it needs.
-- **No-op** — a line the model already obeys by default, so you pay load to say nothing. The test: does it change behaviour versus the default? A weak leading word (_be thorough_ when the agent is already thorough-ish) is a no-op; the fix is a stronger word (_relentless_), not a different technique.
-- **Negation** — steering by prohibition backfires: _don't think of an elephant_ names the elephant and makes it more available, not less. Prompt the **positive** — state the target behaviour so the banned one is never spoken; keep a prohibition only as a hard guardrail you can't phrase positively, and even then pair it with what to do instead.