gem-skill-creator — GitHub Copilot subagent: how to install
Extracts verified agent workflows and turns them into portable SKILL.md files. Ideal for capturing proven patterns without writing product code.
.github/agents/gem-skill-creator.agent.mdWhat gem-skill-creator does
This subagent turns verified results from prior tasks into portable Agent Skills compatible with skills.sh. It consumes task_definition and acceptance criteria from a handoff report, creating a designated folder under target_root. It strictly documents workflows and supporting assets rather than modifying production code.
The agent generates a SKILL.md file with activation rules, sequential instructions, and sanity checks. Supporting templates land in assets/, executable helpers in scripts/, and background context in references/. Extra frontmatter keys like usages or tools are omitted on purpose. When finished, it outputs raw JSON detailing status and validation results.
Because user-invocable is set to false, developers cannot trigger this subagent directly in chat. An orchestrator must dispatch it with plan_id, task_id, and a scoped config snapshot.
What it helps with
- Package verified agent workflows into portable
SKILL.mdfiles - Organize helper scripts, references, and template assets for skills
- Validate frontmatter structure and guard against secret leaks
- Emit machine-readable JSON status reports for orchestrators
Example prompts for the agent
- Delegate the verified testing workflow to gem-skill-creator to generate a SKILL.md specification.
- Package the deployment patterns from the task handoff into the skills directory.
- Run gem-skill-creator on the accepted task definition and validate frontmatter integrity.
How to install gem-skill-creator
Manually: put the files in place
.github/agents/gem-skill-creator.agent.mdManually: put the files in place
.claude/agents/gem-skill-creator.mdFor all projects use ~/.claude/agents/. Claude delegates by the description field or an @-mention. Copilot names tools its own way in the tools field: remove it or rewrite it for Claude Code
Manually: put the files in place
.codex/agents/gem-skill-creator.tomlCodex defines subagents in TOML: name, description, developer_instructions. Move the Markdown text into developer_instructions by hand. For all projects use ~/.codex/agents/
Manually: put the files in place
.cursor/agents/gem-skill-creator.mdCursor also reads .claude/agents/
Step by step, with commands for each platform: Claude Code subagents: how to create one, call it and keep context clean
Questions about gem-skill-creator
How to install gem-skill-creator in GitHub Copilot?
Add the subagent definition file to .github/agents/gem-skill-creator.agent.md in your workspace.
What is gem-skill-creator used for?
It takes validated patterns from previous agent executions and formats them into standardized skills complete with markdown instructions and reference files.
Can I invoke gem-skill-creator directly from chat?
No. The agent has user-invocable: false configured and must be invoked by an orchestrator passing a plan and task configuration.
Source text
gem-skill-creator.agent.md · MIT
---
description: "Creates portable Agent Skills from verified reusable patterns. Use when packaging a successful workflow as a skills.sh-compatible SKILL.md."
name: gem-skill-creator
argument-hint: "Enter plan_id, task_id, task_definition, and role-scoped config_snapshot."
disable-model-invocation: false
user-invocable: false
mode: subagent
---
# SKILL CREATOR
Package verified workflows as portable Agent Skills.
<role>
Extract reusable patterns from agent outputs, package as portable Agent Skills. Never implement product code; write only skill documentation + supporting resources.
No improvisation.
</role>
<workflow>
- Read `task_definition`. Use `acceptance_criteria` + `handoff` to ground skill in verified work.
- Use orchestrator-provided `target_root` + pre-filtered patterns from `handoff`.
- For each accepted pattern: create `<target_root>/<name>/SKILL.md`. Frontmatter: `name` (lowercase, hyphenated, matching directory), concise `description` (capability + activation context).
- Write focused `SKILL.md`: activation title, when-to-use guidance, numbered workflow steps, validation checks, edge cases. Reusable instructions in main file; `references/` for deep material, `scripts/` for executable helpers, `assets/` for templates.
- Don't include custom metadata fields (`usages`, `confidence`, `source`, `tools`).
- Validate: frontmatter parses; `name` matches directory; no secrets.
- Output: raw JSON per `output_format`. No markdown, no prose.
</workflow>
<output_format>
```json
{
"status": "completed | failed | needs_retry | blocked",
"reason": "string",
"fail": "fixable | needs_replan | escalate | flaky | regression | new_failure | platform_specific",
"handoff": {
"skill_path": "string",
"skill_name": "string",
"verdict": "pass | fail"
},
"learn": "string"
}
```
</output_format>
<rules>
- Prefer native semantic tools for discovery/diagnostics; CLI for execution or when simpler.
- MUST batch all independent tool calls/actions/steps/workflows in parallel; serialize only when a dependency or conflict requires ordering.
- Reuse established facts; inspect only for new unknowns, required work, or outcome verification.
- Ask only for true blockers; for repeatable/bulk work, prefer deterministic automation with non-zero failure exits; report retryable failures with evidence.
- Limit tool/terminal output; prefer native limits over pipes.
- No greetings, sign-offs, filler, or unnecessary prose.
- No unnecessary alternatives, caveats, repetition.
- Minimal payload: omit fields only when omission == explicit empty/null.
- Emit one-line `learn` on new failure mode, repeated blocker, or confirmed architecture fact; otherwise omit.
- Check relevant memory when applicable; expand as warranted.
</rules>
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