codegraph

A local code knowledge graph that maps approximate relationships between files, definitions, and calls in a large codebase. A codebase is the complete collection of a project's source files.

In plain words
What is it for?
It helps find where code is used, trace calls between files, and estimate what may be affected by a change in repositories with more than 500 files.
Why use it?
It speeds up orientation in unfamiliar repositories, while making clear that its results can miss relationships and should be checked with normal text search.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/onsager-ai/dev-skills/codegraph
Any agent
npx skills add onsager-ai/dev-skills --skill codegraph
Clone the repo
git clone --depth 1 https://github.com/onsager-ai/dev-skills

Made for: Claude Code, Codex.

Per session 199 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,632 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00199 $0.01632
Opus 5 $0.00100 $0.00816
Sonnet 5 $0.00040 $0.00326
Haiku 4.5 $0.00020 $0.00163

Measured yesterday against content hash effb466edb67, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

skills/codegraph/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

codegraph

Local code graph exposed as 8 MCP tools. Accelerates exploration with O(1) SQLite lookups and FTS5 search — slashing the grep + Read loops needed to orient in a codebase.

It does not replace grep. Codegraph is a tree-sitter approximation of the call graph, not a compiler-grade one: it is fast and low-token but unsound (it has false negatives). Treat it as the accelerator for orientation and traversal, and keep grep as the source of truth for completeness. See Soundness & limits below — this distinction is load-bearing, not a footnote.

When to use

  • Brownfield repo where structure is non-obvious
  • Task involves: "where is X used", "what breaks if I change Y", "trace flow from A to B"
  • Long-running session — cold-start cost amortizes over multiple queries

When NOT to use

  • Single-file edits or trivial lookups
  • Session likely shorter than cold-start cost (see references/spike.md for per-repo numbers)
  • Repo not initialized AND no cached .codegraph/ AND short session

Soundness & limits — read before trusting a result

Codegraph is built on tree-sitter, not the compiler, so its call/reference edges are an approximation. It fails in three confirmed ways. The governing rule falls out of them:

Grep is the source of truth for completeness. Codegraph is the accelerator for orientation and traversal. Never invert these.

The asymmetry is the whole argument: for a refactor, a false negative is dangerous (you miss a caller, ship a break); a false positive is merely annoying (you glance and discard). Codegraph has false negatives; grep does not. So codegraph may propose and rank, but grep confirms whenever the answer must be exhaustive.

The three failure modes (measured on a ~580-file Rust+TS repo):

  1. Unsound edges → false negatives. callers/callees/impact miss real call sites when the receiver type can't be resolved from syntax alone (calls on locals, generics, trait objects). Measured: a method with 8 real callers returned 2 — the 5 dropped were local.method() and generic-dispatch sites, with no warning. Exact on unique free-functions + direct calls (verified 1/1, 2/2); unreliable on method dispatch.
  2. Name resolution is fuzzy and overload-blind. Bare-name queries prefix-match (useWorkspace answered for useWorkspacesQuery — a different symbol) and conflate overloads (execute, with 19 definitions, returned sqlx's .execute() DB calls, not the trait method). For any name with multiple definitions, drop to codegraph_node on a specific symbol id; bare callers/callees are unattributable.
  3. The index lags the disk. CLI sees nothing until codegraph sync (~0.3s); the MCP file-watcher closes the gap to ~1–2s. Right after an edit, the index is wrong — grep/Read is ground truth until it catches up.

Read the full file on GitHub · 75 lines

Files

What ships with it

3 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.

Changes

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.

  1. yesterday First seen · 75 lines · 199 tokens per session scan A effb466edb67

Subscribe to this mod's changes

codegraph is a skill published in the GitHub repository onsager-ai/dev-skills (5 stars, last pushed 19d ago), licensed MIT. It adds 199 tokens to every session and 1,632 once invoked, about $0.0010 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 2026-08-31.

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