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.
git clone --depth 1 https://github.com/sakrut/ai-code-graphWrote 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/rules/sakrut/ai-code-graph/ai-code-graph)<a href="https://agentmods.dev/rules/sakrut/ai-code-graph/ai-code-graph"><img src="https://agentmods.dev/badge/rules/sakrut/ai-code-graph/ai-code-graph/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/rules/sakrut/ai-code-graph/ai-code-graph"><img src="https://agentmods.dev/badge/rules/sakrut/ai-code-graph/ai-code-graph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00213 | $0.00213 |
| Opus 5.5 | $0.00085 | $0.00085 |
| Sonnet 5.5 | $0.00043 | $0.00043 |
| Haiku 4.5 | $0.00021 | $0.00021 |
Grade A, and why
ai-code-graph 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.
What it actually says
AI Code Graph Integration
If cg_* MCP tools are available, use them for code-understanding tasks.
Before editing any method, call cg_get_context first (when graph data exists) to review complexity, callers, callees, duplicates, and cluster context.
Primary tools:
cg_get_contextcg_get_hotspotscg_get_callgraphcg_get_impactcg_querycg_dead_code
Secondary tools:
cg_token_search,cg_semantic_search,cg_get_similarcg_get_duplicates,cg_get_clusters,cg_export_graphcg_churn,cg_coupling,cg_diff,cg_get_drift,cg_get_tree,cg_analyze
If the database is missing, run cg_analyze first to build ./ai-code-graph/graph.db.
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 · 26 lines · 213 tokens per session scan A cb76c8f5a2a5
ai-code-graph is a cursor rule published in the GitHub repository sakrut/ai-code-graph (3 stars, last pushed 7mo ago), licensed MIT. It adds 213 tokens to every session, about $0.0009 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 2026-09-03.
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