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/dhevenddra/forensic-deepdive/codebase-exploringnpx skills add Dhevenddra/forensic-deepdive --skill codebase-exploringgit clone --depth 1 https://github.com/Dhevenddra/forensic-deepdiveWhat 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 | $0.00115 | $0.00501 |
| Opus 5 | $0.00057 | $0.00251 |
| Sonnet 5 | $0.00023 | $0.00100 |
| Haiku 4.5 | $0.00012 | $0.00050 |
Grade A, and why
codebase-exploring 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
Codebase exploring
Read-only orientation. Answer 'what is this and how is it laid out' without re-deriving structure by walking files.
When to use
- User is new to a region of code or the whole repo.
- Question shape: 'what is this', 'how is X organized', 'where does the request flow start', 'what are the main modules'.
- User just opened an unfamiliar file and asks about it.
When NOT to use
- User reports a bug or unexpected behavior →
codebase-debugging. - User wants to change something and asks 'what will break' →
codebase-impact-analysis. - User is brand new to the team and wants the broad brief →
codebase-onboarding. - Question is code-semantic ('does this handle null') — just read the file.
How to answer
- Always read
docs/codebase/AGENT_BRIEF.mdfirst — it's small and pins the never/always rules. - Match the question shape:
| Question shape | Artifact |
|---|---|
| 'What are the entry points / domains' | docs/codebase/MENTAL_MODEL.md |
| 'Most central / load-bearing files' | docs/codebase/MAP.md |
| 'Key definitions in this module' | docs/codebase/MAP.md (Key definitions) |
| 'What rules apply when editing X' | docs/codebase/AGENT_BRIEF.md |
- If an MCP server (
forensic serve) is running, also callcontext(symbol)to get the symbol's neighborhood in one shot.
Citation rule
Cite docs/codebase/MAP.md:142-158 or docs/codebase/AGENT_BRIEF.md:23. Never paraphrase a fact without a line citation.
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 · 37 lines · 115 tokens per session scan A b3ba9ccc6b66
codebase-exploring is a skill published in the GitHub repository Dhevenddra/forensic-deepdive (2 stars, last pushed 16d ago), licensed Apache-2.0. It adds 115 tokens to every session and 501 once invoked, about $0.0006 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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Recall ChatCrystal memories for debugging tasks involving failing tests, compiler errors, runtime exceptions, dependency issues, environment breakage, or performance regressions. Use when historical root causes, fixes, or pitfalls may accelerate diagnosis before proposing a fix.
chatcrystal-task-recall
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slm-recall
Search and retrieve facts, decisions, and past context from SuperLocalMemory. Use when the user asks to recall, find, search, or "what did we decide/say about X". Triggers multi-channel semantic retrieval with reranking; always call before storing anything new.