make-skill
Create, review, or fix Agent Skills for GitHub Copilot. Use when asked to create, scaffold, improve, or repair a SKILL.md and its paired harness evaluation.
- Installs
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/dotnet/efcore --skill make-skill- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads make-skill automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Create Or Fix A Skill
Produce concise, stable task guidance that adds knowledge an agent cannot reliably infer from source alone, together with a paired evaluation that proves the guidance changes behavior.
Choose The Right Primitive
- Use a skill for a task-specific workflow or body of knowledge loaded on demand.
- Use file instructions for background guidance scoped to paths.
- Use a custom agent when context isolation or distinct tool restrictions are required.
- Prefer an existing skill over creating an overlapping one.
Workflow
- Read the relevant implementation, tests, repository instructions, and neighboring customizations.
- Identify repeated mistakes or non-obvious invariants. Do not turn source inventories, line counts, or facts easily rediscovered from code into skill content.
- Create
.agents/skills/<name>/SKILL.md. The frontmatternamemust exactly match the directory; the description must state what the skill does and when natural user requests should trigger it. - Mark background domain guidance
user-invocable: false. Keep user-invocable workflows focused on an outcome a user would deliberately request. - Write actionable guidance with observable validation. Explain why edge cases matter; avoid generic engineering advice already present in repository instructions.
- Create
eng/harness-evaluation/skills/<name>/eval.yamland followeng/harness-evaluation/README.md. - Lint the customization and inspect both control and treatment artifacts before accepting it.
Paired Evaluation
- The eval root
agent_environment.skillscontains only the target skill. Stimulus inputs belong under each stimulus'sagent_environment.files. - The runner removes the root skill for control and separately verifies treatment activation. Do not add a
skill-invocationgrader and do not tell the agent to invoke the skill in the shared prompt. - Prompts may identify fixtures, proposed code, fixed IDs, and output paths, but must not reveal the expected diagnosis, owning mechanism, or regression-test design.
- Stage self-contained source snapshots rather than diffs or commit references; fixture context must not require fetching a repository revision.
- Use deterministic graders for observable artifacts, a narrow semantic rubric for behavior, and a
token-budgetgrader. Define bounded turns, tokens, and duration plus a committed scoring threshold. - The task must exercise guidance distinctive to the skill. A control that consistently matches treatment means the skill or eval is not useful enough.
Validation
- Frontmatter parses and the name matches the directory.
- The skill is concise, stable, and does not duplicate root or scoped instructions.
- File references are relative and exist.
- Validation steps are observable and task-specific.
- The paired eval targets only the skill, has complete bounded grading, and uses a solution-neutral prompt.
npm run lintand the harness inventory tests pass.
Common Pitfalls
| Pitfall | Correction |
|---|---|
| Copying implementation inventories into the skill | Keep only non-obvious invariants and routing decisions |
| Exact line counts or volatile metrics | Remove them; point to stable symbols or behavior |
| Generic test-folder guidance | Describe the distinctive test shape or omit it |
| Eval prompt tells the agent what to find | Move expected facts into the hidden rubric |
| Eval root contains repository fixtures | Keep only the target skill at root; stage fixtures per stimulus |
| Prompt instructs skill invocation | Let the treatment-only runner gate enforce activation |
| Initial scaffold launches multi-model review | First produce and lint the requested artifacts; run expensive behavioral validation separately |
FAQ
What does the make-skill skill do?
Create, review, or fix Agent Skills for GitHub Copilot. Use when asked to create, scaffold, improve, or repair a SKILL.md and its paired harness evaluation.
How do I install make-skill?
Run npx skills add https://github.com/dotnet/efcore --skill make-skill in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/make-skill/ (personal) or .claude/skills/make-skill/ (project).
Which AI agents can use make-skill?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is make-skill safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains make-skill?
It is published by dotnet in dotnet/efcore. It has 46 recorded installs.
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