writing-great-skills
Serves as a reference for writing and editing agent skills well. Helps create clear and effective descriptions.
What it does
This skill helps create instructions (called 'skills') for AI assistants, ensuring they are clear and easy to understand. It teaches how to write descriptions and organize information so the AI works predictably.
When to use it
- ✓When creating a new instruction for the AI.
- ✓When reviewing existing instructions to improve them.
- ✓When the AI is not behaving as expected.
Example of what to ask your AI
“How can I write a good instruction for the AI?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The skill works by explaining the principles of writing and organizing instructions. It details how to describe what the instruction does and how to structure information so the AI follows a clear and consistent process.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill writing-great-skillsOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/writing-great-skills/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
When to Use
Use when this workflow matches the user request: Reference for writing and editing skills well — the vocabulary and principles that make a skill predictable.
_Source: mattpocock/skills (MIT)._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; thedescriptionbecomes 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:
- 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. - 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. - External reference — reference pushed out of
SKILL.mdinto a separate file, reached by a context pointer, loaded only when the pointer fires. (Spans disclosed reference — a sibling file likeGLOSSARY.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.
…
FAQ
What does 'predictability' mean?
Predictability means the AI follows the same process each time the instruction is used, even if the final output might vary slightly.
What's the difference between 'model-invoked' and 'user-invoked'?
'Model-invoked' allows the AI to call the instruction on its own, while 'user-invoked' can only be called by typing its name.
Why is organizing information important?
Organizing information helps the AI find what it needs quickly and follow the correct steps, making its work more reliable.
Details
Original description by the author
Reference for writing and editing skills well — the vocabulary and principles that make a skill predictable.
Popularity
- GitHub stars
- 48k
- Ranking position
- #4596
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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