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Agent Hub Release

OrganizationPopular
amd
agent-hub-release

Cut or wire a frozen-binary + npm sidecar release for a GAIA agent (the email-agent CI pipeline: freeze -> Agent Hub Worker /publish -> npm OIDC). Use when releasing or onboarding a sidecar agent under hub/agents/, or authoring a release_agent_<id>.yml. For the standard wheel/PyPI + Hub publish, defer to the author guide docs/guides/hub-publishing.mdx — this skill is the sidecar extension on top of it.

Overview

Publisheramd
Repositorygaia
Skill nameagent-hub-release
Stars
1.6K
Forks
176
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by amd on GitHub. Read the source before you install it.

Installation

Install the Agent Hub Release AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/amd/gaia/tree/main/.claude/skills/agent-hub-release
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/amd/gaia.git /tmp/gaia
mkdir -p .claude/skills
cp -r /tmp/gaia/.claude/skills/agent-hub-release .claude/skills/agent-hub-release
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Hub Release in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Hub Release on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Hub Release is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Releasing a GAIA Sidecar Agent (frozen binary + npm)

How to ship a sidecar agent — a frozen, no-Python REST binary plus a thin npm client — to the GAIA Agent Hub and npm, via the tag-triggered CI release. The email agent is the reference: hub/agents/email/python/ + hub/agents/email/npm/ + .github/workflows/release_agent_email.yml.

This is a phased process with one hard human gate (the agent-publish environment). Stop and confirm before anything irreversible — pushing a release tag, approving the publish gate. Publishes are immutable per filename: a bad release is fixed by a new version, never an overwrite.

Status — the email pipeline has not yet cut a real release. hub/agents/email/npm/binaries.lock.json still carries placeholder PENDING-1648 hashes and #1648 is open, so the freeze→publish→fetch-verify path has never run end-to-end. Treat this skill as the design of record, not a paved road, until the first real release lands and fills the lock. Likewise the agent-publish environment + GAIA_HUB_TOKEN + hub vars are maintainer setup (workflow header) — verify they exist before relying on them.

Relationship to the author guide (read first)

docs/guides/hub-publishing.mdx is the author-facing guide for the standard distribution: a Python wheel published to the Hub + PyPI via gaia agent publish (or the no-token PR route). It owns the authoritative rules for the manifest, versioning, immutability, and the two publish routes — don't restate or contradict them here.

This skill covers the additional channel an agent like email layers on top: a frozen native binary + an @amd-gaia/agent-<id> npm client, released through release_agent_<id>.yml. An agent can ship one or both channels. Where the two overlap (manifest, version rules), the guide is the source of truth.

Releasing an agent that has never shipped before? Cutting the release is the last phase. An agent is not release-ready because its code runs — it needs a capability-truth audit, a real scorecard, the doc bundle, and a day-one usability check first. Use porting-agent-to-hub for that flow, then come back here for the lane itself.

Distribution model (the mental picture)

freeze.py (PyInstaller, native per-OS, no cross-compile)
   └─ email-agent-<platform>[.exe]   ← one-file binary, boots a FastAPI REST sidecar
        └─ POST /publish  →  Agent Hub Worker (workers/agent-hub/) ── R2 bucket "gaia-hub"
             • stores each object IMMUTABLY under agents/<id>/<ver>/<file>
             • computes SHA-256 server-side
             • rebuilds index.json (the catalog the website reads)
        download = plain public GET at hub.amd-gaia.ai/agents/<id>/<ver>/<file>
   └─ @amd-gaia/agent-<id> (npm)  ← typed client + fetch CLI + sidecar lifecycle
        • binaries.lock.json maps platform → {filename, sha256, size}; the SHA-256
          is the integrity gate the fetch CLI enforces on download
        • published via npm OIDC trusted publishing (provenance, NO npm token)

The Worker fronts the bucket; CI never touches R2 directly — it POSTs to /publish so uploads are server-checksummed and the catalog is rebuilt atomically. The manifest + README ride along inside the publish.

What a sidecar agent adds (email = reference)

On top of the normal agent package (manifest + code + README + pyproject.toml, per the guide), a sidecar agent adds:

PathRole
hub/agents/<id>/python/packaging/freeze.py, smoke_test.py, server.py, gen_binaries_lock.py, publish_to_r2.py, HUB-UPLOAD.md (manual fallback)
hub/agents/<id>/npm/package.jsonESM-only client; exports . (Node) and ./client (browser-safe, client-only — landed in #1773)
hub/agents/<id>/npm/binaries.lock.jsonplatform → artifact + sha256 + size + baseUrl (placeholders until the first release)
hub/agents/<id>/npm/README.md (+ CHANGELOG.md)client docs; CHANGELOG is recommended (Keep a Changelog), not required by publish
hub/agents/<id>/npm/src/client.ts, client-entry.ts (browser entry, landed in #1773), fetch.ts, lifecycle, types.ts, errors.ts, cli.ts
.github/workflows/release_agent_<id>.ymlthe tag-triggered release (copy of release_agent_email.yml)

Notes:

  • The npm client is ESM-only ("type": "module"). Node consumers use the . entry (fetch + spawn); browser/Electron renderers use ./client (client-only, zero Node built-ins) — landed in #1773, documented by #1776.
  • binaries.lock.json ships placeholder hashes until the first real release. While a hash is a placeholder the fetch CLI is fail-loud — a bad binary can never be fetched. For local dev, point the lifecycle helpers at a locally-frozen binary instead of fetchBinary.
  • Manifest validation: validate the author manifest with gaia agent test --lint. Do not validate gaia-agent.yaml against workers/agent-hub/schemas/manifest.schema.json — that is the Hub's server-side aggregate schema and requires fields you never hand-write (versions, latest_version, deprecated, security_tier, permissions).
  • Platform-name skew (easy bug): the manifest's requirements.platforms uses win-x64; binaries.lock.json + the CI matrix use win32-x64. Same agent, two spellings — don't copy one into the other.

The three version numbers the release checks

The Resolve + validate release version step fails loudly unless all three are identical:

  1. the tag (or workflow_dispatch input) — agent-pkg-<id>-v<version> → <version>
  2. hub/agents/<id>/npm/package.json → .version
  3. hub/agents/<id>/python/gaia-agent.yaml → version

Bump the Python side with gaia agent version patch|minor|major (it rewrites gaia-agent.yaml + pyproject.toml + __init__.py together — bumping from the gaia-agent.yaml value, ignoring whatever the npm package.json currently says), then manually set the npm package.json to that same version — the release tooling checks all three agree. (Heads up: they can already be out of sync — e.g. a package.json ahead of gaia-agent.yaml — so a blind patch bumps the yaml base, not the npm value; the manual npm sync is what actually reconciles them.) Add the matching CHANGELOG.md entry too if the agent keeps one (recommended, not required by publish). binaries.lock.json's agentVersion

  • baseUrl are regenerated by CI — don't hand-edit them for a release.

Cutting a release (existing agent)

  1. Version-bump PR → main. gaia agent version <bump>, sync the npm package.json, add the CHANGELOG entry, merge to main (the workflow asserts the release commit is a main ancestor — publishing is allowed only from main).
  2. Pre-flight in hub/agents/<id>/npm/: npm ci && npm run build && npm test, and npm pack --dry-run to confirm README.md ships (and CHANGELOG.md, if you keep one).
  3. Tag from main (or workflow_dispatch with the version):
    bash
    git tag agent-pkg-<id>-v<version> && git push origin --tags
    Namespace is agent-pkg-<id>-* (NOT v*) — it deliberately does not fire the core publish.yml.
  4. Build stage freezes on 4 platforms — win32-x64, darwin-arm64, linux-x64 required; darwin-x64 (Intel) best-effort — smoke-tests each, hashes it. (The smoke test proves the binary boots and the REST route answers; with no Lemonade in CI it does not exercise real LLM triage — a 502/timeout passes.)
  5. Approve the gate. The publish job pauses on the agent-publish environment until a maintainer approves; the publish token isn't readable until then.
  6. Publish stage (atomic): POST every binary to /publish → regenerate binaries.lock.json with the real hashes → fetch-verify every published object against the lock → npm publish via OIDC (provenance) → trigger deploy_website.yml so the new catalog entry appears.

Monitor with gh run watch. npm publish skips if that exact version already exists; /publish is a verified 409 no-op for identical bytes.

Onboarding a NEW sidecar agent (one-time)

  1. Scaffold the normal agent first (gaia agent init, per the guide), then add packaging/ and the hub/agents/<id>/npm/ client. Mirror email.
  2. Adapt the packaging scripts. freeze.py (its NAME = "email-agent" constant) and publish_to_r2.py (the executable name + the email-agent- filename prefix it parses) hardcode email-agent — copy + parameterize them for <id>. gen_binaries_lock.py is already generic (driven by published.json + manifest id); the agents/email hub prefix lives in the workflow's HUB_PREFIX env, not a script.
  3. Copy the workflow release_agent_email.yml → release_agent_<id>.yml and change: PKG_DIR, MANIFEST, README, FREEZE_DIST, HUB_PREFIX (agents/<id>), the tag trigger (agent-pkg-<id>-*), the artifact/frozen names, and the npm package name in the verify/publish steps.
  4. Register the npm trusted publisher for @amd-gaia/agent-<id> against the exact filename release_agent_<id>.yml. ⚠️ The OIDC subject is tied to the filename — renaming the workflow later breaks publish.
  5. (Maintainability) per-agent copies of a ~550-line workflow + three hardcoded scripts will drift. The durable fix is a reusable workflow_call release workflow + scripts parameterized by <id>; the per-agent copy is interim.

One-time infrastructure (verify it exists)

Per the workflow header (release_agent_email.yml), these are maintainer setup — confirm each before the first release:

  • GitHub environment agent-publish with required reviewers; restrict its deployment branches/tags to main and the agent-pkg-* tag pattern (a main-only rule blocks the tag-triggered gate).
  • Secret GAIA_HUB_TOKEN — Agent Hub Bearer token matching an entry in the Worker's PUBLISH_TOKENS, scoped to the agent's author. Define it as an environment secret on agent-publish (not a repo secret) so it's unreadable until the gate is approved. (The workflow maps it into the publish script's AGENT_HUB_PUBLISH_TOKEN env var — same token, different name inside the script.)
  • Var GAIA_HUB_BASE_URL — public Worker origin for downloads + the lock baseUrl (default https://hub.amd-gaia.ai).
  • Var GAIA_HUB_PUBLISH_URL — the Worker's workers.dev URL for uploads. The free-plan WAF on the proxied hub.amd-gaia.ai custom domain blocks large binary uploads (but not GETs). Required — the release fails loudly if it is unset (no silent fallback to the custom domain).
  • Railway HUB_CATALOG_URL=https://hub.amd-gaia.ai so the website rebuild reflects the new entry.

Invariants & gotchas

  • Immutable per filename. The Worker 409s on any re-POST of an existing filename (it keys on the filename via head(), not a byte-compare). The publish script then re-fetches and hashes the stored object: identical bytes → idempotent no-op, a hash mismatch → fail loudly. Fix a bad release with a new version — never an overwrite. (Same immutability the guide describes for id@version.)
  • Publish only from main. The job asserts the release commit is on main.
  • SCHEMA_VERSION MAJOR is the compat gate. Client and binary must agree on the wire-contract MAJOR or startSidecar throws VersionMismatchError. Bump the npm package and re-publish the binary together.
  • Best-effort Intel. darwin-x64 builds on macos-26-intel, then is verified on macos-15-intel. If it fails/absent it's dropped (3-platform release) with a loud ::warning::; Intel users get a clear "no binary for darwin-x64" install error, never a placeholder one.
  • SHA-256 provenance. publish_to_r2.py hashes each binary locally and the Worker hashes it server-side; the script asserts they match on the 201 before that (local, server-verified) hash is written to binaries.lock.json. The lock hash is then the gate the npm fetch CLI enforces on download (PlatformError on a placeholder, IntegrityError on a mismatch).
  • Fetch-verify is the real gate. After /publish, CI re-fetches every object via the npm fetch CLI and checks bytes-hash-to-lock (bounded retry for Cloudflare edge propagation) before npm publish.
  • Website is rebuilt, not patched. Hub pages build from live index.json; the publish job triggers deploy_website.yml on main. (A generic per-agent auto-redeploy is still being wired — see the guide's Verify step.)
  • Manual fallback: hub/agents/<id>/python/packaging/HUB-UPLOAD.md documents the by-hand rclone path to the gaia-hub bucket — identical objects + lock as CI.
  • Write the CHANGELOG entry, PR body, and your status reports per CLAUDE.md → How You Communicate: lead with what changes for someone installing the agent, put versions, hashes, and workflow mechanics underneath. Always say which platforms actually shipped — a dropped Intel build is the headline, not a footnote.

Reference files

  • .github/workflows/release_agent_email.yml — the canonical release workflow (its header comments document the whole contract).
  • docs/guides/hub-publishing.mdx — the author guide (manifest, versioning, wheel + PR publish routes). The overlap's source of truth.
  • hub/agents/email/python/gaia-agent.yaml — manifest reference.
  • hub/agents/email/npm/{package.json,binaries.lock.json,README.md} — client package reference.
  • hub/agents/email/python/packaging/{freeze,smoke_test,publish_to_r2,gen_binaries_lock}.py, HUB-UPLOAD.md — packaging + publish tooling.
  • workers/agent-hub/{README.md,schemas/manifest.schema.json,src/} — the Worker, the /publish contract, and the server-side aggregate schema.

Frequently asked questions

What does the Agent Hub Release AI skill do?

Cut or wire a frozen-binary + npm sidecar release for a GAIA agent (the email-agent CI pipeline: freeze -> Agent Hub Worker /publish -> npm OIDC). Use when releasing or onboarding a sidecar agent under hub/agents/, or authoring a release_agent_<id>.yml. For the standard wheel/PyPI + Hub publish, defer to the author guide docs/guides/hub-publishing.mdx — this skill is the sidecar extension on top of it.

Why use Agent Hub Release on TypingMind?

Because you install it once and use it with any model. Agent Hub Release is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Hub Release in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/amd/gaia/tree/main/.claude/skills/agent-hub-release. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Hub Release?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Hub Release?

As many as you like. As long as a model supports skills, you can use Agent Hub Release with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Hub Release AI skill free?

Yes. It is published on GitHub by amd under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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