| name | write-skills |
| description | Create or revise agent skills. Use when adding a new skill file, renaming a skill, simplifying an existing skill, improving trigger descriptions, or deciding what belongs in a skill versus references, scripts, assets, or ordinary docs. |
Write Skills
A skill is not documentation. It is compressed operational memory for an
agent that already knows how to code and reason. Its job is
predictability — the agent taking the same process every run, not
producing the same output. Put only the context that changes what the agent
will do.
First Principles
-
Trigger from the description. The frontmatter description is the
only part read before the skill loads. Say what the skill does and the
concrete situations that should trigger it. Do not hide trigger rules in
the body.
-
Spend tokens like they are scarce. Assume the agent is already good at
general reasoning. Keep only non-obvious workflow, domain constraints,
tool choices, failure modes, and validation rules. Delete background,
motivation, and generic advice.
-
Write procedures, not essays. Prefer imperative rules, decision
points, and small examples. A good skill changes behavior in the next
turn; it does not merely explain the topic.
-
Use progressive disclosure. Keep the main skill file short. Push long
schemas, examples, provider docs, or variant-specific guidance out into
linked references/ files, reached by a pointer that fires only when
needed. Put repeatable fragile operations in scripts/. Put reusable
output material in assets/.
-
Validate by use. A skill is good when a fresh agent applies it
correctly on a realistic task. After editing, read it as if you had no
conversation history and remove anything that would not affect action.
-
Examples document the PROBLEM, not the solution. An example earns its
tokens by teaching the agent to recognise a recurring problem — the smell,
the symptom, how you knew it was wrong. That is durable. The fix you happened
to apply is not: code changes, and a baked-in solution goes stale, or worse
prescribes a move that won't fit next time. Write the failure mode and its
tell; let the agent derive the fix fresh against the current code. "A
directional question gated on a centroid distance read wrong from every
bearing" teaches; "so we keyed it on FRONT_ARC" rots. When in doubt, state
what was broken and how you spotted it, and stop there.
Leading Words
A leading word is a compact concept already in the model's pretraining
that the agent thinks with while running the skill (e.g. fog of war,
tracer bullets, red, tight). One word recruits priors the model
already holds and anchors a whole region of behavior in the fewest tokens.
- It anchors execution in the body (same word → same behavior every
time) and invocation in the description (when that word also lives in
the user's prompts, docs, and code, the skill fires more reliably).
- Hunt for restatements that a leading word retires. "fast, deterministic,
low-overhead" → a tight loop. "a loop you believe in" → the loop goes
red. You win twice: fewer tokens and a sharper hook.
- A weak leading word is a no-op (
be thorough when the agent already is).
The fix is a stronger word (relentless), not more sentences.
Invocation
Choose how the skill is reached; each choice spends a different cost.
- Model-invoked (default): keep a
description so the agent can fire it
on its own and other skills can reach it. Costs context load — the
description sits in the window every turn. Write rich trigger phrasing.
- User-invoked: set
disable-model-invocation: true. Only the user
typing its name can invoke it; zero context load, but the user must
remember it exists. The description becomes a human-facing one-liner.
Pick model-invocation only when the agent or another skill must reach it
unprompted. When user-invoked skills pile up past memory, add a router
skill that names the others and when to reach for each.
Description
The description does two jobs: state what the skill is, and list the
distinct situations (branches) that trigger it.
- Front-load the leading word — invocation work happens here.
- One trigger per branch. Synonyms that rename one branch are duplication;
collapse them and keep only genuinely distinct branches.
- Cut identity already in the body. Keep triggers plus any "when another
skill needs…" reach clause.
Information Hierarchy
A skill is steps and reference, mixed freely. Rank each piece by how
immediately the agent needs it:
- In-skill step — an ordered action in
SKILL.md. Each ends on a
completion criterion: 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.
- In-skill reference — a definition or rule consulted on demand. A flat
peer-set of rules is fine, not a smell.
- External reference — pushed out of
SKILL.md into a linked file,
loaded only when its pointer fires.
Keep a concept's definition, rules, and caveats under one heading
(co-location) so reading one part brings its neighbors. Push too little
down and the top bloats; push too much down and you hide what the agent needs.
When to Split
Each cut spends a cost, so split only when it earns it:
- By invocation — split off a model-invoked skill when a distinct
leading word should trigger it alone, or another skill must reach it. You
pay context load for the new always-loaded description.
- By sequence — split a run of steps when the steps still ahead tempt
the agent to rush the one in front of it. Hiding later steps forces more
work on the current one.
Failure Modes
Diagnose a misbehaving skill against these:
- Premature completion — ending a step before it's done. Fix the
completion criterion first (cheap); only split to hide later steps if the
criterion is irreducibly fuzzy and you see the rush.
- Duplication — the same meaning in two places. Keep a single source
of truth.
- Sediment — stale layers that accumulate because adding feels safe.
Prune deliberately.
- War story — a lesson written as the play-by-play of the change that
taught it: function names, tuned values, one bug's trajectory. Those
specifics date fast and bury the transferable rule. State the principle and
the smell to watch for; let the codebase hold the mechanics. One concrete
touchstone grounds it; a paragraph of them drowns it.
- Implementation index — a skill that points at today's source files, line
numbers, current literals, or exact internal functions when its job is really
to teach judgment. Those locators rot and make agents chase old mechanics.
Keep durable principles, symptoms, acceptance criteria, and reference assets
in the skill; put task-specific implementation notes in the active spec. If
code location matters, tell the agent to find the current owner in the
codebase.
- Sprawl — too long even when every line is live. Cure with the ladder:
disclose reference behind pointers, split by branch or sequence.
- No-op — a line the model already obeys by default. Test each sentence
in isolation; when it fails, delete the whole sentence, don't trim words.
Shape
Use this structure unless there is a strong reason not to:
---
name: short-verb-phrase
description: What this does. Use when ...
---
# Skill Title
One short paragraph defining the job.
## Workflow
1. Do the first load-bearing thing.
2. Make the key decision.
3. Produce or verify the artifact.
## Rules
- Keep the constraints that prevent common mistakes.
- Link only the references that should be loaded conditionally.
Edit Pass
When creating or revising a skill:
- Name it with lowercase hyphen-case; keep the folder name identical.
- Make the description specific enough to trigger without the body.
- Remove any "when to use" section from the body.
- Remove stale history, attribution, placeholders, and setup notes.
- Remove file paths, line numbers, current constants, and implementation knobs
unless the skill is explicitly a code-navigation runbook. Prefer durable
principles plus a directive to inspect the current code.
- Prefer one strong rule over several overlapping bullets.
- Refactor restatements into a leading word where one fits.
- Keep examples tiny and realistic.
- Add no README, changelog, or auxiliary docs unless they are actual
references the skill tells the agent when to read.
- Run the skill validator when available.
Done
The skill is done when its metadata triggers correctly, its body is short
enough to read in one pass, and a fresh agent can follow it without asking
why the skill exists.