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 SahilSheikh12299/codegraph-mcp --skill skillgit clone --depth 1 https://github.com/SahilSheikh12299/codegraph-mcpWrote 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/sahilsheikh12299/codegraph-mcp/skill)<a href="https://agentmods.dev/skills/sahilsheikh12299/codegraph-mcp/skill"><img src="https://agentmods.dev/badge/skills/sahilsheikh12299/codegraph-mcp/skill/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/sahilsheikh12299/codegraph-mcp/skill"><img src="https://agentmods.dev/badge/skills/sahilsheikh12299/codegraph-mcp/skill.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 | $0.00042 | $0.01046 |
| Opus 5.5 | $0.00017 | $0.00418 |
| Sonnet 5.5 | $0.00008 | $0.00209 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
codegraph-mcp 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GraphRAG — Code Discovery Rules
Always pass active_project_root (absolute repo root) on every tool call. Reuse the same path throughout a session.
Primary goal: answer or edit with the least token usage possible. GraphRAG is a swiss-army-knife for repo discovery — far better than grep — but only when you use it surgically. Every extra search or read wastes tokens.
The only discovery tool
search_codebase_intent is the only GraphRAG tool. Use it for all repo discovery.
Do not use native Grep, SemanticSearch, or iterative file hunting to explore the codebase.
Efficiency first
- Answer with what you have. If search + reads already cover the question, stop — do not search or read again.
- One search, then read. Start with a single
search_codebase_intentcall. A second search is allowed only when something specific is still missing (wrong anchor, no cite for a symbol you need, gap in the call path). - Read each cite once. Open only the cite spans you actually need. Skip spans that do not help answer the question.
- No overlapping reads. If two cites cover the same file and ranges overlap, read the union once — never re-read lines you already have in context.
- No speculative exploration. Do not read "just in case", prefetch adjacent files, or widen ranges beyond what the question requires.
- Fewest tool calls wins. Prefer one good search + targeted reads over multiple searches, broad reads, or re-fetching content already in the conversation.
Workflow
- Call
search_codebase_intentonce with intent queries and any known symbol names. - Read only the cite spans required to answer (format:
startLine:endLine:filepath). Merge overlapping spans in the same file into one read. - Answer or edit using what you already have — stop here if sufficient.
Second search — only when a specific gap remains after step 2 (missing symbol, wrong file, incomplete path). Refine queries or symbols; still no grep.
What ships with it
1 file 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.
- 1mo ago First seen · 114 lines · 42 tokens per session scan A eaff23964ccc
codegraph-mcp is a skill published in the GitHub repository SahilSheikh12299/codegraph-mcp (0 stars, last pushed 4mo ago), licensed MIT. It adds 42 tokens to every session and 1,046 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 2026-09-01.
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