# Artifact Librarian

> Operate the local Agent Librarian workflow using the synthetic sample collection, approval-gated runtime wrapper, deterministic CLI outputs, and human-review summary.

- **Type:** Skill
- **Install:** `agentstack add skill-elvinmorales-agent-librarian-artifact-librarian`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [ElvinMorales](https://agentstack.voostack.com/s/elvinmorales)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [ElvinMorales](https://github.com/ElvinMorales)
- **Source:** https://github.com/ElvinMorales/agent-librarian/tree/main/packages/openai/codex/.agents/skills/artifact-librarian

## Install

```sh
agentstack add skill-elvinmorales-agent-librarian-artifact-librarian
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Artifact Librarian

Use this skill to run a public-safe Codex demo of `agent-librarian`. Lead
with the functional portable-agent workflow, not taxonomy.

## Workflow

```text
Codex reads AGENTS.md
-> Codex explains safe scope
-> Codex proposes runtime-wrapper commands
-> user approves exact command
-> wrapper runs deterministic CLI backend
-> Codex summarizes CLI evidence
-> human reviews generated outputs
```

## Steps

1. Explain the agent in plain language.
   - Codex is the interface layer.
   - The deterministic CLI and generated outputs are the source of truth.
   - The demo uses only the synthetic `examples/sample-collection`.

2. Inspect only allowed public demo files.
   - Allowed source: `examples/sample-collection`.
   - Allowed generated catalog: `examples/generated-catalog`.
   - Allowed package instructions: `packages/openai/codex/`.
   - Do not scan private/work files, work-internal folders, credentials,
     secrets, private prompts, private traces, logs, memory snapshots, state
     snapshots, employer/client data, internal URLs, or private generated
     catalogs.
   - Do not use non-demo paths.

3. Propose commands before running anything.
   - Prefer runtime-wrapper `propose` commands.
   - Show exact command, read scope, write scope, generated files, and
     sensitivity note.

4. Require exact approval.
   - Do not run on vague approval.
   - Do not run if the approval string is different from the command shown.
   - Changed command, path, argument, sensitivity, or retry requires fresh
     approval.

5. Run only approved wrapper commands.
   - Do not run arbitrary shell.
   - Do not chain commands.
   - Do not execute, edit, delete, merge, publish, or rewrite source files.
   - Do not create git commits, pushes, tags, releases, pull requests, or
     GitHub/yeet publishing flows.
   - Do not edit repo files during the demo unless the user explicitly asks
     for development work.

6. Summarize deterministic outputs.
   - Use runtime-wrapper output, CLI output, and generated files as evidence.
   - Preserve warnings, diagnostics, validation failures, and overlap
     candidates.
   - Do not invent counts, files, findings, or status.

7. Explain what the demo proves.
   - Codex can scope a synthetic public demo.
   - Codex can propose bounded wrapper commands.
   - Exact approval gates local execution.
   - The deterministic backend produces evidence for human review.

8. Explain what the demo does not prove.
   - It does not certify safety, privacy, correctness, completeness, approval,
     compliance, or publication readiness.
   - It does not scan private or work-internal material.
   - It does not add OpenAI API integration, network behavior, MCP server
     code, arbitrary shell execution, or autonomous publication.

## Allowed Demo Commands

```bash
python -m agent_librarian.runtime_wrapper propose catalog examples/sample-collection --out examples/generated-catalog
python -m agent_librarian.runtime_wrapper propose validate examples/generated-catalog
python -m agent_librarian.runtime_wrapper propose report examples/generated-catalog
python -m agent_librarian.runtime_wrapper run report examples/generated-catalog --approve-exact "agent-librarian report examples/generated-catalog"
```

Wrong approval demonstration:

```bash
python -m agent_librarian.runtime_wrapper run report examples/generated-catalog --approve-exact "wrong command"
```

The wrong approval should fail with a nonzero status and must not run the
backend.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [ElvinMorales](https://github.com/ElvinMorales)
- **Source:** [ElvinMorales/agent-librarian](https://github.com/ElvinMorales/agent-librarian)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-elvinmorales-agent-librarian-artifact-librarian
- Seller: https://agentstack.voostack.com/s/elvinmorales
- Browse the marketplace: https://agentstack.voostack.com/browse

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