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.
In this repository17 other files it gives its agents.
- aria-skill-candidatesSkill
- aria-skill-templateSkill
- aria-skill-testSkill
- call-scrubSkill
- cloudflare-dns-deploySkill
- doc-to-pdfSkill
- ffmpeg-audioSkill
- github-repo-deploySkill
- goal-to-planSkill
- headless-claudeSkill
- live-code-watchSkill
- premortemSkill
- screen-describeSkill
- session-cabinetSkill
- sprint-scaffoldSkill
- surgical-patchSkill
- video-ingestSkill
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
- Very specific: line 8
Every aria-skill is one executable.
≈ “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.
Files
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:
| Harness | File it needs |
| OpenAI / Codex / xAI Grok | manifest/openai.json (Tool/Function schema) |
| Google Gemini | manifest/gemini.json (function_declarations) |
| MCP — VS Code, Cursor, Claude Desktop | manifest/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 --forceSafety / 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--allis safe to run. --checkis the blanket enforcement. It's wired intoaria-skill-test, so a new skill that ships without manifests (or one whoseSKILL.mddescription 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) andaria-skill-test(the gate).
License
Apache 2.0
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.

