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/brain-bootstrap/claude-code-brain-bootstrap/asknpx skills add brain-bootstrap/claude-code-brain-bootstrap --skill askgit clone --depth 1 https://github.com/brain-bootstrap/claude-code-brain-bootstrapWhat 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 | $0.00037 | $0.00385 |
| Opus 5 | $0.00018 | $0.00192 |
| Sonnet 5 | $0.00007 | $0.00077 |
| Haiku 4.5 | $0.00004 | $0.00038 |
Grade A, and why
ask 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.
What it actually says
Ask Skill — Codebase Question Router
Answer a question about the codebase by routing to the most effective tool.
Don't search files manually when a smarter tool exists.
Routing Rules
Architecture / flow / how does X work / trace a call
Use mcp__codebase-memory__trace_path or mcp__codebase-memory__get_architecture.
Zero file reads. 120× fewer tokens than manual exploration.
Find / search / locate / what file / which function
Use mcp__cocoindex-code__search with a semantic query.
Finds code by meaning, not exact text — useful when you don't know the exact name.
Safe to change / impact / blast radius / what breaks / risk score
Use mcp__code-review-graph__detect_changes_tool with base_branch="main".
Reports: risk score 0–100, blast radius, breaking changes, dependent modules.
General code question (narrow, specific file, no plugin fits)
Read the file directly. Grep for the symbol.
Decision Logic
- Contains architecture/flow/trace/how/explain → codebase-memory-mcp
- Contains find/search/locate/where/what file → cocoindex-code
- Contains safe/impact/blast/breaks/risk/change → code-review-graph
- None of the above → read directly
Answer Format
- Tool used and why
- Finding (file path + line if applicable)
- Surprising cross-module connections revealed by the graph (if any)
If no tool gives a clear answer, fall back to reading relevant files.
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 · 43 lines · 37 tokens per session scan A 043ab3189787
ask is a skill published in the GitHub repository brain-bootstrap/claude-code-brain-bootstrap (11 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 385 once invoked, about $0.0002 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.
Other skills, from other repositories
implement
TRIGGER when: user asks to implement, fix, build, or work on something — whether from a docs/wip plan OR a standalone task (bug fix, GitHub issue, one-off change). Examples: "work on task 1", "fix this bug", "implement feature X from the issue". Provides structured execution with profile detection, dependency…
review-spec
Use after implementing tasks or mid-feature to verify code matches design docs and ensure they are in sync. Detects spec deviations, missing implementations, doc inconsistencies, and outdated docs in design and implementation documentation.
chain-of-verification
Apply Chain-of-Verification (CoVe) prompting to improve response accuracy through self-verification. Use when complex questions require fact-checking, technical accuracy, or multi-step reasoning.
review-design
Review design, implementation, and task documents produced by design. Evaluates document quality, internal consistency, and technical soundness. Use after design completes and before starting implement.
review-code
Code review of current git changes with an expert senior-engineer lens. Detects SOLID violations, security risks, and proposes actionable improvements. Use when performing code reviews.
dependency-handling
TRIGGER when: adding or upgrading any dependency — library, SDK, framework, API, IaC API version (K8s/Terraform/Helm), CRD, or container image. Use BEFORE writing the call. Forces context7/capy lookup instead of guessing.