Knowledge RetrievalSAFE
A framework-agnostic, git-native standard for defining AI agents
Overview
A framework-agnostic, git-native standard for defining AI agents
799d6d0ad18cOBSERVED · 2026-10-07What 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: knowledge-retrieval description: Semantic search over ingested documents using RAG (LlamaIndex/ChromaDB or Foundational RAG) allowed-tools: knowledge-retrieval --- # Knowledge Retrieval Perform semantic search over a pre-ingested document collection using Retrieval-Augmented Generation (RAG). Backed by LlamaIndex with ChromaDB or NVIDIA Foundational RAG. ## When to Use - Searching internal or pre-ingested documents and reports - Finding information in PDFs, whitepapers, or technical documentation - Retrieving domain-specific knowledge not available on the open web - This is the **highest priority** source — check the knowledge base first before web or paper searches ## How to Use 1. Formulate a semantic search query describing the information needed 2. Call `knowledge_retrieval` with the query 3. Review returned chunks for relevance 4. Note the citation metadata (filename, page number) for sourcing ## Result Format Results are returned as text chunks with citation metadata: ``` Relevant text passage from the ingested document... Citation: filename.pdf, p.12 ``` ## Constraints - Searches only over documents that have been ingested into the knowledge index - Returns ranked chunks based on semantic similarity - Citation format: `Citation: filename.ext, p.X` - Each call counts toward the researcher's 8-call limit per task ## Backend Options - **LlamaIndex + ChromaDB** — Local vector store with LlamaIndex orchestration - **NVIDIA Foundational RAG** — NVIDIA-hosted RAG service with NeMo Retriever
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.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
799d6d0ad18cfull audit observations/trust-audit/skill/open-gitagent__knowledge-retrieval.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-07 | 799d6d0ad18c | SAFE | B | 89 | first audit |
Questions
What does the Knowledge Retrieval skill do?
A framework-agnostic, git-native standard for defining AI agents
Is Knowledge Retrieval 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 Knowledge Retrieval access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (799d6d0ad18c), read on 2026-10-07. The repository is watched, and a new audit runs when it changes — this is the first audit.