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Unified Ai Gateway

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Operate and evaluate Unified AI System through fifteen governed MCP tools, including provider-free prompt enhancement, while preserving fake-provider, authorization, and evidence boundaries.

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  • Added September 26, 2026
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SKILL.md
---
name: unified-ai-gateway
description: Operate and evaluate Unified AI System through fifteen governed MCP tools, including provider-free prompt enhancement, while preserving fake-provider, authorization, and evidence boundaries.
license: Apache-2.0
metadata:
  author: happy520ai
  category: ai-ml
  date_added: "2026-08-01"
  license_source: https://github.com/happy520ai/unified-ai-system/blob/master/LICENSE
  risk: critical
  source: https://github.com/happy520ai/unified-ai-system/tree/master/skills/unified-ai-gateway
  source_repo: happy520ai/unified-ai-system
  source_type: official
  tags: "ai-gateway, codex, mcp, self-hosted, governance"
  tools: codex
---

# Unified AI Gateway

## Overview

Use the official `unified-ai-system` MCP server to inspect and exercise a local
AI gateway without provider credentials. This skill file provides operating
guidance; it does not install the server or change Codex configuration by
itself. The official Codex plugin bundles the MCP definition, while skill-only
installations require the manual setup below.

## Version Note

These are two different things and they are not equal today:

- **Current release: `v0.8.0`.** It declares and ships fifteen tool names, and the
  [60-second demo command](https://github.com/happy520ai/unified-ai-system#try-it-in-60-seconds)
  in the README names that version. Read it live with
  `node tools/verify-image-roster.mjs 0.8.0`, which reports the roster from the
  image bytes rather than from this file. That command needs a clone of the
  repository, run from its root: the script ships with the source, not inside an
  installed skill bundle. Without a clone, the same roster is published at
  https://happy520ai.github.io/unified-ai-system/verify-mcp-docker-image.html.
- **Newest content review: `0.8.0`** ([review](https://github.com/happy520ai/unified-ai-system/blob/master/docs/security/mcp-image-review-0.8.0.md)),
  read from the published layer tarballs with `node tools/inspect-image-filesystem.mjs 0.8.0` - no Docker
  engine and nothing executed. It found one thing worth knowing before you pull: the `linux/arm64` tag carries
  x86-64 native modules, including `better_sqlite3.node`, so request `--platform linux/amd64`.
- **Reviewed and pinned below: `0.4.9`.** The inspection procedure in this file
  pins that image's recorded digests because `0.4.9` is the newest version reviewed by that procedure, which
  exports a container filesystem with Docker. The 0.8.0 review above uses a different method and pins its own
  digests, so the table below still describes 0.4.9 until it is rewritten against a 0.8.0 export.
  `0.4.9` carries 9 of the fifteen names: the model-backed enhancement, knowledge
  retrieval and workflow execution tools arrived at 0.5.0, and the three
  governance tools at 0.8.0.

Do not substitute a mutable tag for a pinned digest, and do not move the pin to a
newer version just because this file looks out of date: a new content review is
required first, and the pinned identity is only as good as the review that backs it.

## Prerequisites And Setup

1. Confirm that Codex CLI and Docker are installed and Docker is running.
2. If the nine tools are already visible, skip setup and do not register a
   duplicate server.
3. Explain the first stage: it downloads one reviewed platform from the
   immutable `0.4.9` multi-platform index into Docker's cache, inspects its
   metadata and layer history, creates but never starts a temporary container,
   exports its root filesystem, removes that temporary container, and writes an
   inspection inventory to a temporary directory. The reviewed platforms are
   linux/amd64 and linux/arm64. Obtain explicit user approval for those download
   and inspection changes only.
4. After that first approval, pull the reviewed platform manifest and complete
   the inspection. Do not execute the image or register it yet:

```bash
IMAGE='ghcr.io/happy520ai/unified-ai-system/mcp-server@sha256:751a0d32acd2d6b1da6ad9ac67987fbd1ff36ce26b7160014d8605f18b7907b3'
PLATFORM='linux/amd64' # Use linux/arm64 only on a reviewed ARM64 engine.
REVIEW_DIR="$(mktemp -d)"

docker pull --platform "$PLATFORM" "$IMAGE"
docker image inspect "$IMAGE" --format 'Id={{.Id}} OS={{.Os}} Architecture={{.Architecture}} User={{json .Config.User}} Entrypoint={{json .Config.Entrypoint}} Cmd={{json .Config.Cmd}} Labels={{json .Config.Labels}}'
docker image history --no-trunc "$IMAGE" > "$REVIEW_DIR/image-history.txt"

REVIEW_CONTAINER="$(docker create --platform "$PLATFORM" --pull never --entrypoint /bin/true "$IMAGE")"
docker export --output "$REVIEW_DIR/rootfs.tar" "$REVIEW_CONTAINER"
docker rm "$REVIEW_CONTAINER"

tar -tf "$REVIEW_DIR/rootfs.tar" > "$REVIEW_DIR/rootfs-files.txt"
mkdir -p "$REVIEW_DIR/rootfs"
tar --same-permissions -xf "$REVIEW_DIR/rootfs.tar" -C "$REVIEW_DIR/rootfs"
find "$REVIEW_DIR/rootfs/app" -type f -print > "$REVIEW_DIR/app-files.txt"
: > "$REVIEW_DIR/app-links.txt"
while IFS= read -r -d '' APP_LINK; do
  ls -ld -- "$APP_LINK" >> "$REVIEW_DIR/app-links.txt"
done < <(find "$REVIEW_DIR/rootfs/app" \( -type l -o -type f -links +1 \) -print0)
: > "$REVIEW_DIR/native-binaries.sha256"
while IFS= read -r -d '' NATIVE_BINARY; do
  sha256sum -- "$NATIVE_BINARY" >> "$REVIEW_DIR/native-binaries.sha256"
done < <(find "$REVIEW_DIR/rootfs/app" -type f -name '*.node' -print0)
find "$REVIEW_DIR/rootfs" -type f \( -perm -0100 -o -perm -0010 -o -perm -0001 \) -print > "$REVIEW_DIR/executable-files.txt"
find "$REVIEW_DIR/rootfs" -type f \( -perm -4000 -o -perm -2000 \) -print > "$REVIEW_DIR/suid-sgid-files.txt"
find "$REVIEW_DIR/rootfs/app" -type f \( -name '.env' -o -name '.env.*' -o -name '*.pem' -o -name '*.key' -o -name '*.p12' -o -name '*.pfx' -o -path '*/.ssh/id_*' \) -print > "$REVIEW_DIR/credential-like-files.txt"
grep -RInHE --include='package.json' '"(preinstall|install|postinstall|prepare|prepack|postpack)"' "$REVIEW_DIR/rootfs/app" > "$REVIEW_DIR/lifecycle-hooks.txt"
grep -RInE 'child_process|spawn\(|fetch\(|AI_GATEWAY_MCP_URL|process\.env|writeFile|appendFile|unlink|rm\(' "$REVIEW_DIR/rootfs/app/packages/mcp-server/src" "$REVIEW_DIR/rootfs/app/packages/shared-sdk/src" > "$REVIEW_DIR/runtime-sensitive-code.txt"
```

If `sha256sum` is unavailable, use the platform's SHA-256 utility and preserve
the same report. Keep the review directory until the report is accepted; its
deletion is another filesystem change and requires approval for the exact path.

5. Read every generated inventory and report the inspection before proceeding.
   Compare it with the versioned
   [image content review](https://github.com/happy520ai/unified-ai-system/blob/master/docs/security/mcp-image-review-0.4.9.md).
   Require OCI index digest
   `sha256:751a0d32acd2d6b1da6ad9ac67987fbd1ff36ce26b7160014d8605f18b7907b3`.
   For linux/amd64, require manifest digest
   `sha256:ff6cf988b01d5fb2e97aabe8e952f6a303dcffe650df5b4dcb0ba3d51ee88c06`
   and config digest
   `sha256:0c2c0c7b9c7fb7ca24c73d9a903bcf719b079a0b285a3a3269ee3ae059905e97`.
   For linux/arm64, require manifest digest
   `sha256:90318b9e373820f863c1c1addc759be4b5ce186f2ecb6232ee502fad7c6613de`
   and config digest
   `sha256:c2047eb63fdc42bcb16d53fca17d78a4a6fb355cf6320b9aa6688e594371054f`.
   Require source `https://github.com/happy520ai/unified-ai-system`, revision
   `342a47313927870bcc696be13c9e5fb922062dac`, version `0.4.9`, license
   `Apache-2.0`, entrypoint `docker-entrypoint.sh`, and command
   `node packages/mcp-server/src/index.js`.

   Report these reviewed risks explicitly: the image uses the default root
   user; includes Debian shell/package utilities and 11 base-image SUID/SGID
   files; contains 522 internal pnpm links, three native Node binaries, and eight
   lifecycle-hook declarations; and starts a child gateway with loopback HTTP.
   The optional `AI_GATEWAY_MCP_URL` can make an HTTP or HTTPS connection only
   when explicitly passed. The registered command below passes no host files,
   environment variables, or ports and disables container networking. Stop on
   any mismatch, unexpected link, credential-like file, native binary, hook,
   privileged file, or sensitive-code behavior.
6. Explain the second stage: it persists a Codex MCP configuration and permits
   Codex to launch the inspected image in a later task. Obtain a separate
   explicit approval for registration and activation; the download approval
   does not carry over.
7. After that second approval, register the reviewed platform digest with
   pulling, container networking, Linux capabilities, and privilege escalation
   disabled, then inspect the stored configuration:

```bash
IMAGE='ghcr.io/happy520ai/unified-ai-system/mcp-server@sha256:751a0d32acd2d6b1da6ad9ac67987fbd1ff36ce26b7160014d8605f18b7907b3'
PLATFORM='linux/amd64' # Match the reviewed platform inspected above.
codex mcp add unified-ai-system -- docker run --rm -i --pull never --platform "$PLATFORM" --network none --cap-drop ALL --security-opt no-new-privileges "$IMAGE"
codex mcp get unified-ai-system --json
```

8. Restart Codex or open a new task, then use `/mcp verbose` to confirm that all
   nine tools are available - the pinned `0.4.9` image ships nine of the fifteen
   names the current release declares. Remove the registration when it is no longer
   wanted:

```bash
codex mcp remove unified-ai-system
```

Removing the registration does not remove the pulled image from Docker's
cache. Treat image-cache deletion as a separate host-state change and obtain
approval before doing it.

## When to Use This Skill

- Use when a user asks whether Unified AI System is healthy or ready.
- Use when a user wants a credential-free gateway chat proof.
- Use when a user asks about the gateway's knowledge, workflow, or workforce
  surfaces.
- Use when a user wants evidence from the bundled MCP tools rather than a claim
  inferred from documentation or process exit codes.

Do not use this skill for generic model comparisons, unrelated MCP servers, or
deploying a production gateway.

## Workflow

1. Confirm that the `unified-ai-system` MCP tools are available in the current
   task. If they are absent, follow the approved setup above and wait for a
   restarted or new task.
2. Call `gateway_health`, then `gateway_readiness`, before attempting chat.
3. Select the narrowest additional tool that answers the request.
4. Report returned provider, execution mode, readiness, and blockers exactly.
5. Separate transport success from product, production-readiness, autonomy, or
   AGI claims.

## Tool Map

Nine of these ship in the reviewed `0.4.9` image below; the six marked 0.5.0 and
0.8.0 are in the current release and are absent from that older image.

Status and boundaries:

- `gateway_health`: gateway health, provider mode, and the real-provider safety flag
- `gateway_readiness`: first-run readiness for chat and the local gateway runtime
- `knowledge_readiness`: knowledge infrastructure without loading or changing data
- `workflow_health`: the governed workflow subsystem without starting a workflow
- `workflow_actions`: workflow action definitions without invoking any action
- `workforce_health`: the workforce subsystem without planning or executing work
- `workforce_agents`: configured workforce agent descriptors without dispatching them

Doing work locally, still with no provider call:

- `gateway_prompt_enhance`: structures a plain-language request into a prompt
  locally, without provider credentials or provider calls
- `gateway_prompt_enhance_llm` *(0.5.0)*: semantic rewriting through a provider
  when one is configured, falling back to the deterministic local engine when none is
- `knowledge_retrieve` *(0.5.0)*: keyword search over the local knowledge base,
  returning ranked chunks with citations; calls no provider
- `workflow_run` *(0.5.0)*: the 3-step local workflow - retrieve knowledge, compose
  a Markdown report, write a controlled artifact; calls no provider
- `gateway_chat`: one chat request, accepted only when the gateway proves real
  providers are disabled

The governed Agent surface, read-only *(0.8.0)*:

- `agent_governance_status`: governance status through the authenticated Gateway
  identity; no tenant override is accepted and it fails closed when that identity is
  not authorized for platform status
- `agent_governance_list`: only the governed Agents visible to that tenant, with no
  tenant or owner override argument
- `agent_governance_describe` (takes `agentId`): one Agent as seen by that tenant;
  cross-tenant and missing identifiers stay indistinguishable on purpose

Creating, executing, revoking, approving or activating anything in that surface
remains a human REST/SDK/CLI operation and is not exposed to the model at all.

## Example

```text
User: Check whether the local gateway is ready, then prove chat works safely.

Agent:
1. Call gateway_health.
2. Call gateway_readiness.
3. Call gateway_chat only if both results prove fake-provider mode.
4. Report provider, model, execution mode, response, and every blocker.
```

## Safety Boundaries

- Keep the credential-free local fake provider as the default.
- Never request, read, or transmit provider credentials through this skill.
- Do not enable or call a real provider without explicit scoped authorization.
- Treat MCP registration, image pulls, container creation, networking, and
  teardown as host-state changes that require informed user approval.
- Never substitute a mutable tag, a different OCI index, or an unreviewed
  platform manifest for the reviewed `0.4.9` identities. Keep download and
  inspection approval separate from registration and activation approval.
- Keep `--pull never` in the registered command. If the reviewed image is
  absent from the local cache, fail closed and return to the first approval
  stage.
- Keep `--network none`, `--cap-drop ALL`, and
  `--security-opt no-new-privileges` in the registered command.
- Do not claim production readiness, L5 autonomy, or AGI from a healthy handshake.
- Treat a zero exit code as transport evidence, not proof that readiness gates
  passed.

## Limitations

- This skill file does not bundle the MCP server, Docker image, or Codex
  configuration. It only operates tools supplied by the separately installed
  official integration.
- It does not deploy, benchmark, or certify the gateway for production use.
- The credential-free chat tool proves only the deterministic local fake path.
- It does not configure real providers or handle provider credentials.
- The published MCP image requires Docker.
- The reviewed `0.4.9` path covers linux/amd64 and linux/arm64. Do not activate
  another platform image without a separate content review.
- The image runs as the container's default root user and bundles the gateway
  source, package-manager tooling, native dependencies, and base-image
  SUID/SGID files. The registered command drops capabilities, prevents new
  privileges, disables networking, and leaves the image in Docker's cache.
- Existing Codex tasks may not hot-load a newly installed MCP configuration.

## Troubleshooting

- If the tools are missing after approved registration, inspect
  `codex mcp get unified-ai-system --json`, then restart Codex or start a new
  task.
- If readiness is blocked, report the returned blocker instead of retrying chat
  blindly.
- If the runtime might use a real provider, stop before chat and keep the
  session read-only.

## Additional Resources

- [Unified AI System](https://github.com/happy520ai/unified-ai-system)
- [60-second Codex MCP quickstart](https://github.com/happy520ai/unified-ai-system/blob/master/docs/codex-mcp-quickstart.md)
- [MCP server guide](https://github.com/happy520ai/unified-ai-system/blob/master/packages/mcp-server/README.md)
- [MCP image content review](https://github.com/happy520ai/unified-ai-system/blob/master/docs/security/mcp-image-review-0.4.9.md)

Files in this skill

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