create-agent-skill
Skill1 starsChanged 3 months agoMITView on GitHub
Create or improve concise Codex agent skills from a workflow, domain requirement, SOP, tool integration, or repeated task. Use when the user asks to write, review, optimize, package, validate, or document an Agent Skill / Codex skill / SKILL.md, including deciding scripts, references, assets, metadata, trigger descriptions, progressive disclosure, examples, and validation steps.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- nledford/engineering-review-boardtheir own version, first seen Nov 3, 2026
- oocx/tfplan2mdtheir own version, first seen Oct 8, 2026
- xelandernt/skillstheir own version, first seen Jun 22, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- oocx/tfplan2md★ 174same name
- nledford/engineering-review-board★ 11same name
- xelandernt/skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository22 other files it gives its agents.
- analysis-skillSkill
- auto-testcase-generatorSkill
- create-skillSkill
- development-systemSkill
- domain-modelingSkill
- figma-rest-syncSkill
- grill-systemSkill
- grill-with-docsSkill
- rag-change-impactSkill
- rag-downstream-handoffSkill
- rag-governanceSkill
- rag-intakeSkill
- rag-querySkill
- rag-schemaSkill
- rag-structure-fidelitySkill
- rag-systemSkill
- researchSkill
- session-handoffSkill
- skill-packagerSkill
- task-understanding-routerSkill
- ui-testSkill
- write-requirements-prdSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
30 rules. 0 are common, 18 are distinctive, and 12 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
18
Distinctive
This author's own choices. Worth a look.
12
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 10
Create skills as small operational playbooks for another Codex agent.
- Distinctive: line 17
Write concise frontmatter and body instructions.
- Distinctive: line 23
Before writing files, answer these questions:
- Very specific: line 34
If the user has not chosen a location, create personal skills under $CODEX_HOME/skills.
- Distinctive: line 38
Use the smallest structure that supports the job:
- Distinctive: line 63
Do not add README, changelog, installation guide, long tutorial notes, or evaluation reports unless the user explicitly asks.
- Distinctive: line 79
Use lowercase letters, digits, and hyphens.
- Distinctive: line 80
Keep the name short and action-oriented.
- Very specific: line 81
Put trigger conditions in description, because only metadata is available before the skill loads.
- Distinctive: line 82
Do not rely on a body section named "When to use".
- Very specific: line 83
Avoid extra frontmatter fields such as version, tags, author, compatibility, or nested metadata unless the local platform explicitly …
- Very specific: line 87
Use imperative instructions.
- Distinctive: line 91
Decision rules: when to choose scripts, references, assets, or fallback paths.
- Distinctive: line 93
Escalation and safety: when to ask the user, avoid live changes, or protect secrets.
- Distinctive: line 95
Prefer concrete examples and short checklists.
- Distinctive: line 99
Treat context as limited:
- Very specific: line 101
Keep SKILL.md focused on the core workflow.
- Very specific: line 102
Put long schemas, rubrics, examples, and provider-specific details in references/.
- Distinctive: line 104
Keep references one level deep.
- Very specific: line 105
Avoid duplicating the same content in SKILL.md and references.
- Very specific: line 107
Read references/skill-quality-rubric.md when reviewing or hardening a skill.
- Distinctive: line 113
Use plain instructions when the task is flexible and judgment-heavy.
- Very specific: line 114
Add references/ when the agent needs detailed domain knowledge or multiple variants.
- Very specific: line 115
Add scripts/ when the same fragile logic would otherwise be rewritten repeatedly.
- Very specific: line 116
Add assets/ when outputs need templates, sample files, icons, or boilerplate.
- Distinctive: line 122
After creating or changing a skill:
- Distinctive: line 124
Run the local skill validator when available, for example:
- Distinctive: line 135
no secrets, credentials, or project-private data are embedded.
- Distinctive: line 143
Do not leak the intended answer into the test prompt.
- Distinctive: line 147
When reviewing an existing skill, prioritize:
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Create Agent Skill
Operating Rules
Create skills as small operational playbooks for another Codex agent. Prefer essential procedural knowledge over broad explanations. Keep SKILL.md lean, and move detailed examples, scoring rubrics, or variant-specific guidance into references/.
Use this order:
- Clarify the skill objective, triggers, inputs, outputs, success criteria, and safety boundaries.
- Decide whether the skill needs only
SKILL.mdor alsoreferences/,scripts/, orassets/. - Initialize or update the skill folder.
- Write concise frontmatter and body instructions.
- Validate the skill structure.
- Forward-test or simulate realistic usage when the skill is nontrivial.
Skill Design Checklist
Before writing files, answer these questions:
- What repeated task will this skill make more reliable?
- What user wording should trigger it?
- What should the agent produce or change?
- Which steps must be followed exactly?
- Which decisions can be left to the agent?
- What external tools, APIs, credentials, files, or permissions are needed?
- What evidence proves the skill worked?
- What should the skill refuse, avoid, or ask before doing?
If the user has not chosen a location, create personal skills under $CODEX_HOME/skills; when unset, use ~/.codex/skills.
File Structure
Use the smallest structure that supports the job:
skill-name/
SKILL.md
agents/openai.yaml
references/
scripts/
assets/Required:
SKILL.md: YAML frontmatter plus concise Markdown instructions.
Recommended:
agents/openai.yaml: UI metadata.
Optional:
references/: detailed guides loaded only when needed.scripts/: deterministic commands, validators, generators, converters, or wrappers.assets/: templates, icons, sample files, or boilerplate copied into outputs.
Do not add README, changelog, installation guide, long tutorial notes, or evaluation reports unless the user explicitly asks. They create noise and are not part of the operating skill.
Frontmatter
Use only:
---
name: skill-name
description: What the skill does and exactly when to use it.
---Rules:
namemust match the folder name.- Use lowercase letters, digits, and hyphens.
- Keep the name short and action-oriented.
- Put trigger conditions in
description, because only metadata is available before the skill loads. - Do not rely on a body section named "When to use"; the body is loaded too late for triggering.
- Avoid extra frontmatter fields such as
version,tags,author,compatibility, or nested metadata unless the local platform explicitly requires them.
Body Pattern
Use imperative instructions. A strong SKILL.md body usually contains:
- Operating rules: non-negotiable behavior.
- Workflow: ordered steps the agent should follow.
- Decision rules: when to choose scripts, references, assets, or fallback paths.
- Validation: commands or checks that prove the skill is usable.
- Escalation and safety: when to ask the user, avoid live changes, or protect secrets.
Prefer concrete examples and short checklists. Remove background theory unless it changes execution.
Progressive Disclosure
Treat context as limited:
- Keep
SKILL.mdfocused on the core workflow. - Put long schemas, rubrics, examples, and provider-specific details in
references/. - Link each reference from
SKILL.mdand say when to read it. - Keep references one level deep.
- Avoid duplicating the same content in
SKILL.mdand references.
Read references/skill-quality-rubric.md when reviewing or hardening a skill.
Resource Selection
Choose resources by execution risk:
- Use plain instructions when the task is flexible and judgment-heavy.
- Add
references/when the agent needs detailed domain knowledge or multiple variants. - Add
scripts/when the same fragile logic would otherwise be rewritten repeatedly. - Add
assets/when outputs need templates, sample files, icons, or boilerplate.
Scripts must be runnable and validated. If a script depends on external tools or credentials, document those assumptions in the skill body.
Validation
After creating or changing a skill:
- Run the local skill validator when available, for example:
python path/to/quick_validate.py path/to/skill-folder- Inspect
SKILL.mdfor:- frontmatter has only
nameanddescription; - description includes use cases and trigger wording;
- body is procedural, not a tutorial;
- references are discoverable and not duplicated;
- no secrets, credentials, or project-private data are embedded.
- frontmatter has only
- For nontrivial skills, forward-test with a realistic user request:
Use $skill-name to complete [realistic task].Do not leak the intended answer into the test prompt.
Review Heuristics
When reviewing an existing skill, prioritize:
- trigger accuracy;
- unnecessary context or duplicated content;
- missing validation;
- brittle steps that should be scripts;
- hidden assumptions about tools, permissions, environment, or credentials;
- resources that are never referenced;
- outputs that cannot be verified.
Return findings first, then a compact change plan.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

