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 agentmods add skills/open-gitagent/opengap/researchnpx skills add open-gitagent/opengap --skill researchgit clone --depth 1 https://github.com/open-gitagent/opengapWhat 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 | $0.00061 | $0.00393 |
| Opus 5 | $0.00030 | $0.00197 |
| Sonnet 5 | $0.00012 | $0.00079 |
| Haiku 4.5 | $0.00006 | $0.00039 |
Grade A, and why
research 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 2d 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.
What it actually says
Research
Instructions
When researching a topic:
- Identify the core question or area of interest
- Break it into 3-5 key subtopics
- For each subtopic, provide factual information with reasoning
- Note areas of uncertainty or debate
- Synthesize findings into a coherent summary
Output Format
## TL;DR
[Brief summary]
## Research Findings
### [Subtopic]
- [Key point with supporting reasoning]
## Open Questions
- [Areas that need further investigation]
## Suggested Follow-ups
- [Related questions the user might want to explore]
Example Output
## TL;DR
WebAssembly (Wasm) is a binary instruction format that enables near-native performance in browsers and increasingly in server-side contexts.
## Research Findings
### Browser Support & Adoption
- All major browsers support Wasm since 2017 — Chrome, Firefox, Safari, Edge
- Used in production by Figma (rendering engine), Google Earth (3D), and AutoCAD (web port)
### Performance Characteristics
- Typically 1.1-1.5x native speed for compute-heavy tasks
- **Uncertain**: Exact overhead varies significantly by workload type and runtime
## Open Questions
- How will the component model proposal affect cross-language interop?
## Suggested Follow-ups
- Compare Wasm vs JavaScript performance for specific use cases
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.
- 2d ago First seen · 60 lines · 61 tokens per session scan A 34edcc7c9b73
research is a skill published in the GitHub repository open-gitagent/opengap (2,921 stars, last pushed 2mo ago), licensed MIT. It adds 61 tokens to every session and 393 once invoked, about $0.0003 per session on Opus 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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