skill-write

name	skill-write
description	Use when your write a document or any piece of skill in free form.

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 was writing for?

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 skill (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 skill 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.

Every leading word should be placed in GLOSSARY.md near a skill corpus.

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.