agentleFS
iansteitz1-engiansteitz1-eng/aria-skills/skill-manifest-gen/SKILL.md

skill-manifest-gen

Skill0 starsChanged 2 months agoApache-2.0View on GitHub

Generate cross-harness discovery manifests (openai.json · gemini.json · mcp.json + README) so an aria-skill is findable from OpenAI/Codex/Grok, Google Gemini, and MCP clients (VS Code, Cursor, Claude Desktop) — not just Claude Code. Derived deterministically from SKILL.md + the script's argparse, so manifests never drift. --all sweeps the repo, --check is a CI drift gate, --force overwrites. Use when Ian says "generate manifests", "MCP marketplace", "discoverable in VS Code/Cursor", "backfill manifests", or after adding a skill.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Every aria-skill is one executable.

    line 8

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Skill Manifest Gen — cross-harness discovery, blanket-covered

Every aria-skill is one executable. Claude Code discovers it via SKILL.md; other harnesses need their own discovery file. This generates all three from the same sources of truth so they can't drift:

HarnessFile it needs
OpenAI / Codex / xAI Grokmanifest/openai.json (Tool/Function schema)
Google Geminimanifest/gemini.json (function_declarations)
MCP — VS Code, Cursor, Claude Desktopmanifest/mcp.json (tool spec 2024-11-05)

Sources of truth: SKILL.md frontmatter (name + description) + the skill's script argparse (→ the input parameter schema). Nothing is hand-authored, so a regenerate always matches the skill.

Run it

# one skill (skips if manifest/ already exists)
python3 skill-manifest-gen/gen_manifests.py --skill-dir safe-restart

# blanket: every skill in the repo (existing manifests left untouched)
python3 skill-manifest-gen/gen_manifests.py --all --repo-root .

# CI drift gate: report any skill missing a manifest or whose description is stale
python3 skill-manifest-gen/gen_manifests.py --all --check        # exit 2 if any

# deliberately regenerate a curated one
python3 skill-manifest-gen/gen_manifests.py --skill-dir foo --force

Safety / fidelity

  • Never clobbers. In write mode an existing manifest/ is skipped unless --force — curated manifests are often hand-tuned past what argparse exposes (richer param docs, corrected defaults), so a blanket --all is safe to run.
  • --check is the blanket enforcement. It's wired into aria-skill-test, so a new skill that ships without manifests (or one whose SKILL.md description drifts from its manifest) FAILS the regression harness. That's how "nothing goes missing again" is guaranteed, not just fixed once.
  • Generated manifests are a correct starting point; refine param descriptions by hand when useful, then they're protected by the no-clobber rule.

Notes

  • manifest/ is discovery glue only — the script remains the behavior truth.
  • Pairs with marketplace-publish (which uploads the VS Code extension / app-store builds) and aria-skill-test (the gate).

License

Apache 2.0

Download now (ZIP)

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