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writing-great-skills

Reference for writing and editing skills well: the principles that make a skill predictable.

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SKILL.md
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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; 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.

The craft

Editing a skill's body — how to order information, when to split it into references, what to prune, which words to lead with — is in references/craft.md. Read it before restructuring a skill.

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.
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YoizenSA/dev-ai-workflow

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

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