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/study8677/repobrain/graph-retrievalnpx skills add study8677/repobrain --skill graph-retrievalgit clone --depth 1 https://github.com/study8677/repobrainWhat 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 | $0.00046 | $0.00228 |
| Opus 5 | $0.00023 | $0.00114 |
| Sonnet 5 | $0.00009 | $0.00046 |
| Haiku 4.5 | $0.00005 | $0.00023 |
Grade A, and why
graph-retrieval 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
Graph Retrieval Skill
Purpose
Expose graph-based retrieval as a tool capability without breaking the existing RepoBrain execution chain.
Tool
query_graph(query, max_hops=2, workspace='.')
Behavior
- Reads normalized graph store files under
.repobrain/graph/. - Builds a query-relevant subgraph.
- Returns LLM-friendly semantic triples plus replayable evidence metadata.
Output Contract
{
"summary": "...",
"triples": [["subject", "predicate", "object"]],
"evidence": [{"retrieval_id": "...", "tool_name": "..."}],
"nodes": [...],
"edges": [...]
}
Design Notes
- Keeps tool-driven and replayable architecture.
- Does not bypass pipeline.
- Intended for structure/dependency questions and context enrichment.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 35 lines · 46 tokens per session scan A a8894560cae0
graph-retrieval is a skill published in the GitHub repository study8677/repobrain (1,322 stars, last pushed 4d ago), licensed MIT. It adds 46 tokens to every session and 228 once invoked, about $0.0002 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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