skill-creator

name	skill-creator
description	Use this skill to create, revise, package, evaluate, or optimize GitHub Copilot skills and reusable SKILL.md-based agent instructions. Use it whenever the user wants a new Copilot skill, edits to an existing skill, eval/test prompts, skill benchmarking, skill packaging, trigger-description optimization, or reusable agent instructions.
license	Apache-2.0
allowed-tools	Bash(python3 scripts/quick_validate.py:*) Bash(python3 scripts/package_skill.py:*) Bash(python3 scripts/run_eval.py:*) Bash(python3 scripts/run_harness_eval.py:*) Bash(python3 scripts/run_loop.py:*) Bash(python3 scripts/improve_description.py:*) Bash(python3 scripts/aggregate_benchmark.py:*) Bash(python3 scripts/generate_report.py:*) Bash(python3 eval-viewer/generate_review.py:*)

Skill Creator

Use this file as the operating checklist after the skill has loaded. Attribution and modification notes are in LICENSE.txt and NOTICE.md.

First principles

A skill is a folder with a required SKILL.md file and optional bundled resources:

skill-name/
├── SKILL.md
├── scripts/
├── references/
├── assets/
└── evals/

Frontmatter must include name and description. Keep name lowercase kebab-case and matching the folder. Keep description specific because Copilot uses it for trigger decisions, but do not repeat that description in the body. Quote or block-scalar descriptions that contain YAML-sensitive punctuation such as : .

Keep SKILL.md lean. Move long explanations to references/, deterministic helpers to scripts/, templates or examples to assets/, and objective eval prompts or fixtures to evals/. Body and reference files should assume they are already loaded or intentionally opened: explain how to proceed, not why the skill or reference should be used.

Workflow

1. Capture intent from the conversation before asking questions: task, trigger conditions, expected output, dependencies, near misses, and whether objective evals are useful.
2. Draft or revise SKILL.md with clear imperatives, concise workflow steps, and only the context the agent needs after the skill has loaded.
3. Add or maintain evals/evals.json for objective behaviors such as file transforms, fixed workflows, code generation, benchmark comparisons, and trigger-sensitive descriptions.
4. Prefer bundled scripts when repeated deterministic work appears in eval transcripts. Use narrowly scoped allowed-tools entries such as Bash(python3 scripts/validate.py:*), and make sure every command shown in the workflow is covered by allowed-tools or a bundled helper.
5. Validate, run the smallest useful eval set, review failures across cases, then revise for general behavior rather than overfitting one prompt.
6. Package only after validation and eval review are satisfactory.

Evals and optimization

• Use scripts/run_harness_eval.py for Copilot task-output evals.
• Use scripts/run_eval.py for Copilot trigger-description evals.
• Use scripts/run_loop.py only after the trigger eval set is approved; apply a proposed description only after checking that it remains accurate.
• Grade task runs against eval_metadata.json assertions. Programmatic checks are best when practical; otherwise use agents/grader.md.
• If an eval prompt says a file is provided, include that fixture in evals/files/ and list it in evals/evals.json; otherwise write the prompt so it is runnable without input files.

Read references/workflows.md for exact Copilot eval commands, output layout, aggregation, and review-page generation.

Safety and quality

• Avoid surprising behavior, credential collection, data exfiltration, exploit code, or anything inconsistent with the user's stated intent.
• Do not hard-code machine-specific install paths or copy bundled scripts elsewhere.
• Keep baselines honest: Copilot cannot fully disable personal skills via a public flag, so prefer unique working-copy skill names when strict baselines matter.

Packaging

python3 scripts/quick_validate.py /path/to/my-skill
python3 scripts/package_skill.py /path/to/my-skill /path/to/dist

The packager creates a .skill zip archive and excludes root evals/, __pycache__, node_modules, .DS_Store, and *.pyc.

Reference files

• references/workflows.md — commands for task evals, trigger evals, description optimization, aggregation, and reports.
• references/schemas.md — JSON schemas.
• agents/grader.md — grade assertions against outputs.
• agents/comparator.md — blind A/B comparison instructions.
• agents/analyzer.md — benchmark pattern analysis and post-hoc comparison analysis.
• eval-viewer/generate_review.py — static/server review page generator.