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/thangchung/agent-engineering-experiment/explore-codebasenpx skills add thangchung/agent-engineering-experiment --skill explore-codebasegit clone --depth 1 https://github.com/thangchung/agent-engineering-experimentWhat 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 | $0.00015 | $0.00283 |
| Opus 5 | $0.00008 | $0.00142 |
| Sonnet 5 | $0.00003 | $0.00057 |
| Haiku 4.5 | $0.00002 | $0.00028 |
Grade A, and why
explore-codebase 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 2d 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:
- explore-codebase — 100% identical, 2 lines differ
What it actually says
Explore Codebase
Use the code-review-graph MCP tools to explore and understand the codebase.
Steps
- Run
list_graph_statsto see overall codebase metrics. - Run
get_architecture_overview_toolfor high-level community structure. - Use
list_communities_toolto find major modules, thenget_communityfor details. - Use
semantic_search_nodes_toolto find specific functions or classes. - Use
query_graph_toolwith patterns likecallers_of,callees_of,imports_ofto trace relationships. - Use
list_flowsandget_flowto understand execution paths.
Tips
- Start broad (stats, architecture) then narrow down to specific areas.
- Use
children_ofon a file to see all its functions and classes. - Use
find_large_functionsto identify complex code.
Token Efficiency Rules
- ALWAYS start with
get_minimal_context(task="<your task>")before any other graph tool. - 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.
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.
- 2d ago First seen · 29 lines · 15 tokens per session scan A 10bc1bd838ad
explore-codebase is a skill published in the GitHub repository thangchung/agent-engineering-experiment (24 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 283 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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