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 rules/lagrahhn/codegraph-branch/codegraphgit clone --depth 1 https://github.com/lagrahhn/codeGraph-branchWhat 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 | $0.00819 | $0.00819 |
| Opus 5 | $0.00409 | $0.00409 |
| Sonnet 5 | $0.00164 | $0.00164 |
| Haiku 4.5 | $0.00082 | $0.00082 |
Grade A, and why
codegraph 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 yesterday.
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.
This is a copy
100% identical to codegraph — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CodeGraph
This project has a CodeGraph MCP server (codegraph_* tools) configured. CodeGraph is a tree-sitter-parsed knowledge graph of every symbol, edge, and file. Reads are sub-millisecond and return structural information grep cannot.
When to prefer codegraph over native search
Use codegraph for structural questions — what calls what, what would break, where is X defined, what is X's signature. Use native grep/read only for literal text queries (string contents, comments, log messages) or after you already have a specific file open.
| Question | Tool |
|---|---|
| "Where is X defined?" / "Find symbol named X" | codegraph_search |
| "What calls function Y?" | codegraph_callers |
| "What does Y call?" | codegraph_callees |
| "How does X reach/become Y? / trace the flow from X to Y" | codegraph_trace (one call = the whole path, incl. callback/React/JSX dynamic hops) |
| "What would break if I changed Z?" | codegraph_impact |
| "Show me Y's signature / source / docstring" | codegraph_node |
| "Give me focused context for a task/area" | codegraph_context |
| "See several related symbols' source at once" | codegraph_explore |
| "What files exist under path/" | codegraph_files |
| "Is the index healthy?" | codegraph_status |
Rules of thumb
- Answer directly — don't delegate exploration. For "how does X work" / architecture questions, answer with 2-3 codegraph calls:
codegraph_contextfirst, then ONEcodegraph_explorefor the source of the symbols it surfaces. For a specific flow ("how does X reach Y") start withcodegraph_tracefrom→to — one call returns the whole path with dynamic hops bridged — then ONEcodegraph_explorefor the bodies; don't rebuild the path withcodegraph_search+codegraph_callers. Codegraph IS the pre-built index, so spawning a separate file-reading sub-task/agent — or running a grep + read loop — repeats work codegraph already did and costs more for the same answer. - Trust codegraph results. They come from a full AST parse. Do NOT re-verify them with grep — that's slower, less accurate, and wastes context.
- Don't grep first when looking up a symbol by name.
codegraph_searchis faster and returns kind + location + signature in one call. - Don't chain
codegraph_search+codegraph_nodewhen you just want context —codegraph_contextis one call. - Don't loop
codegraph_nodeover many symbols — onecodegraph_explorecall returns several symbols' source grouped in a single capped call, while each separate node/Read call re-reads the whole context and costs far more. - Index lag — check the staleness banner, don't guess a wait. When a codegraph response starts with "⚠️ Some files referenced below were edited since the last index sync…", the listed files are pending re-index — Read those specific files for accurate content. Files NOT in that banner are fresh and codegraph is authoritative for them.
codegraph_statusalso lists pending files under "Pending sync".
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.
- yesterday First seen · 40 lines · 819 tokens per session scan A b7113a7f7a9b
codegraph is a cursor rule published in the GitHub repository lagrahhn/codeGraph-branch (2 stars, last pushed 1mo ago), licensed MIT. It adds 819 tokens to every session, about $0.0041 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to codegraph, differing in 0 lines, and is treated as a copy.
Other cursor rules, from other repositories
codestory
CodeStory local grounding. Use repo evidence before source claims.
jarvis-agent-rules
MCP server jarvis: notes, Jira, knowledge graph, sessions, preferences.
gitnodes
GitNodes repository conventions for AI agents and contributors.
codebase
Forensic codebase brief for AI agents.
session-memory
Use at conversation wrap-up or when the user explicitly indicates end-of-session — capture residual lessons not captured in-flight.
design-patterns
Design patterns (GoF) and file size conventions for sweagent TypeScript codebase.