Atlas / Skills / openai / Openai Knowledge

Openai KnowledgeSAFE

skills/openai/openai-knowledge

A lightweight, powerful framework for multi-agent workflows

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
1 documented
License
MIT
Stars
29,851
01

Overview

A lightweight, powerful framework for multi-agent workflows

Read from source at commit 090ff821bbcdOBSERVED · 2026-10-06
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
codexmentioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: openai-knowledge
description: Retrieve authoritative OpenAI API and platform documentation when an integration or claim needs current external evidence.
---

# OpenAI Knowledge

## Overview

Use the OpenAI Developer Documentation MCP server to search and fetch exact docs (markdown), then base your answer on that text instead of guessing.

## Workflow

### 1) Check whether the Docs MCP server is available

If the `mcp__openaiDeveloperDocs__*` tools are available, use them.

If you are unsure, run `codex mcp list` and check for `openaiDeveloperDocs`.

### 2) Use MCP tools to pull exact docs

- Search first, then fetch the specific page or pages.
  - `mcp__openaiDeveloperDocs__search_openai_docs` → pick the best URL.
  - `mcp__openaiDeveloperDocs__fetch_openai_doc` → retrieve the exact markdown (optionally with an `anchor`).
- When you need endpoint schemas or parameters, use:
  - `mcp__openaiDeveloperDocs__get_openapi_spec`
  - `mcp__openaiDeveloperDocs__list_api_endpoints`

Base your answer on the fetched text and quote or paraphrase it precisely. Do not invent flags, field names, defaults, or limits.

### 3) If MCP is not configured, guide setup (do not change config unless asked)

Provide one of these setup options, then ask the user to restart the Codex session so the tools load:

- CLI:
  - `codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp`
- Config file (`~/.codex/config.toml`):
  - Add:
    ```toml
    [mcp_servers.openaiDeveloperDocs]
    url = "https://developers.openai.com/mcp"
    ```

Also point to: https://developers.openai.com/resources/docs-mcp#quickstart
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (1)

LOWInventory / provenance · inv.symlink · CWE-1104
CLAUDE.md
CLAUDE.md
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-10-06 · audit v0.4.1 · source sha 090ff821bbcdfull audit observations/trust-audit/skill/openai__openai-knowledge.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-06090ff821bbcdSAFEB89first audit
06

Questions

What does the Openai Knowledge skill do?

A lightweight, powerful framework for multi-agent workflows

Is Openai Knowledge safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Openai Knowledge access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does Openai Knowledge work with?

Its documentation mentions codex. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (090ff821bbcd), read on 2026-10-06. The repository is watched, and a new audit runs when it changes — this is the first audit.

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