OpenGAP is a framework-independent standard for defining AI agents as Git repositories, using files such as an agent manifest and identity document. It is intended for portable, version-controlled agents that can be adapted to systems such as Claude Code, OpenAI, LangChain, CrewAI, and AutoGen. The catalogue skills represent workflows and extensions built around this agent format.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add open-gitagent/opengap --skill wiki-ingestgit clone --depth 1 https://github.com/open-gitagent/opengapWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/open-gitagent/opengap/wiki-ingest)<a href="https://agentmods.dev/skills/open-gitagent/opengap/wiki-ingest"><img src="https://agentmods.dev/badge/skills/open-gitagent/opengap/wiki-ingest/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/open-gitagent/opengap/wiki-ingest"><img src="https://agentmods.dev/badge/skills/open-gitagent/opengap/wiki-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.00629 |
| Opus 5.5 | $0.00021 | $0.00252 |
| Sonnet 5.5 | $0.00011 | $0.00126 |
| Haiku 4.5 | $0.00005 | $0.00063 |
Grade A, and why
wiki-ingest scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiki Ingest
Process a new source document and integrate its knowledge into the wiki.
Workflow
Step 1: Read the source
Read the full source document from knowledge/. Identify:
- Key entities (people, organizations, concepts, technologies)
- Main claims and findings
- Relationships between entities
- Data points and statistics
- Contradictions with or confirmations of existing knowledge
Step 2: Discuss with the user
Before writing, share a brief summary of key takeaways. Ask:
- What aspects to emphasize?
- Any entities or concepts to prioritize?
- Should this update existing pages or create new ones?
Step 3: Update the wiki
For each significant entity or concept found in the source:
- Check if a wiki page exists — read
memory/wiki/index.md - If page exists — read it, integrate new information, update the "Sources" section, update frontmatter
updateddate andsource_count - If page doesn't exist — create a new page in
memory/wiki/with proper frontmatter, content, and source citations - Update cross-references — add
[[wikilinks]]in both directions between related pages
Step 4: Write a source summary page
Create memory/wiki/sources/<source-name>.md with:
- One-paragraph summary
- Key claims extracted
- Entities mentioned (with wikilinks to their pages)
- Date ingested
Step 5: Update index and log
- Update
memory/wiki/index.md— add/update entries for all pages touched - Update
knowledge/index.yaml— ensure the source is cataloged with tags and priority - Append to
memory/log.md:## [YYYY-MM-DD] ingest | Source Title - Pages created: [list] - Pages updated: [list] - Key findings: [1-2 sentences]
Example
User drops knowledge/quantum-computing-review-2026.pdf and says "ingest this".
- Read the paper, identify entities: quantum computing, error correction, IBM, Google, topological qubits
- Discuss key findings with user
- Create/update:
quantum-computing.md,error-correction.md,ibm.md,google.md - Create:
sources/quantum-computing-review-2026.md - Update
index.mdwith all new/updated pages - Append ingest entry to
log.md
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 65 lines · 53 tokens per session scan A b17f8ef12591
wiki-ingest is a skill published in the GitHub repository open-gitagent/opengap (2,981 stars, last pushed 3mo ago), licensed MIT. It adds 53 tokens to every session and 629 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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