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 skills/tirth8205/code-review-graph/debug-issuenpx skills add tirth8205/code-review-graph --skill debug-issuegit clone --depth 1 https://github.com/tirth8205/code-review-graphWhat 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 | $0.00013 | $0.00272 |
| Opus 5 | $0.00006 | $0.00136 |
| Sonnet 5 | $0.00003 | $0.00054 |
| Haiku 4.5 | $0.00001 | $0.00027 |
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 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.
What it actually says
Debug Issue
Use the knowledge graph to systematically trace and debug issues.
Steps
- Use
semantic_search_nodes_toolto find code related to the issue. - Use
query_graph_toolwithcallers_ofandcallees_ofto trace call chains. - Use
get_flow_toolto see full execution paths through suspected areas. - Run
detect_changes_toolto check if recent changes caused the issue. - Use
get_impact_radius_toolon suspected files to see what else is affected.
Tips
- Check both callers and callees to understand the full context.
- Look at affected flows to find the entry point that triggers the bug.
- Recent changes are the most common source of new issues.
Token Efficiency Rules
- Start with
get_minimal_context_tool(task="<your task>")before other graph tools. - Use
detail_level="minimal"on all calls. Only escalate to "standard" when minimal is insufficient. - Target: complete any review/debug/refactor task in ≤5 tool calls and ≤800 total output tokens.
- 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.
- yesterday 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 (31,016 stars, last pushed 5d ago), licensed MIT. It adds 13 tokens to every session and 272 once invoked, about $0.0001 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 2026-08-30.
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