code-review-graph is a local-first code intelligence graph that builds a persistent structural map of a codebase and supplies relevant context to AI coding tools through MCP and a CLI. It is used for code review and large-repository workflows, with catalogue add-ons providing integrations and instructions for operating it.
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 tirth8205/code-review-graph --skill debug-issuegit clone --depth 1 https://github.com/tirth8205/code-review-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/skills/tirth8205/code-review-graph/debug-issue)<a href="https://agentmods.dev/skills/tirth8205/code-review-graph/debug-issue"><img src="https://agentmods.dev/badge/skills/tirth8205/code-review-graph/debug-issue/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/tirth8205/code-review-graph/debug-issue"><img src="https://agentmods.dev/badge/skills/tirth8205/code-review-graph/debug-issue.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00013 | $0.00260 |
| Opus 5.5 | $0.00005 | $0.00104 |
| Sonnet 5.5 | $0.00003 | $0.00052 |
| Haiku 4.5 | $0.00001 | $0.00026 |
Grade A, and why
debug-issue 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- debug-issue — 100% identical, 25 lines differ
What it actually says
Debug Issue
Trace a bug through the knowledge graph before reading source.
Steps
- Call
semantic_search_nodes_toolto find code related to the issue. - Call
query_graph_toolwithcallers_ofandcallees_ofto trace the call chain in both directions. - Call
get_flow_toolfor the execution path that reaches the suspect code. Its entry point is where the bug is triggered. - Call
detect_changes_toolto check whether a recent change caused the issue. - Call
get_impact_radius_toolon the suspect files to see what a fix would affect.
Token Efficiency Rules
- Call
get_minimal_context_tool(task="<your task>")before any other graph tool. - Pass
detail_level="minimal"wherever a tool accepts it. Use "standard" only when minimal is not enough. - Prefer a targeted
query_graph_toolcall over a broad listing call. - Budget: about five tool calls and 800 tokens of graph output per task.
- Read the implementation and its tests before changing code. The graph narrows scope; it does not replace the source.
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 Changed · -5 lines 17d008a2c6cb
- 1mo ago First seen · 29 lines · 13 tokens per session scan A 68dd9bd6810e
debug-issue is a skill published in the GitHub repository tirth8205/code-review-graph (32,175 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 260 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.
issue-root-resolution
Trigger: root audit, atacar la raíz, issue roots, backlog roots, mechanism map, deletion-driven fix, resolver issues de raíz, close outdated issues. Audit and resolve issue clusters by verified root cause.
rdd-defect-workflow
Trigger: RDD, receipt-driven development, review authority, receipt/lineage, correction/recovery, delivery gate/kill switch, bounded review defects. Guide work.
autofix
Review and repair current local changes until they converge, or run Qwen Code Autofix issue and review workflows from GitHub Actions.
codegraph
A local code-graph query tool for an existing project. It maps symbols and their relationships so you can search for definitions, callers, callees, affected files, and focused context.
gitnexus
A code-graph analysis add-on for examining an existing codebase, including symbols, call paths, execution flows, and effects across repositories. It can query GitNexus through its command-line or MCP interfaces.