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.
git clone --depth 1 https://github.com/ao92265/claude-code-playbookWrote 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/agents/ao92265/claude-code-playbook/architect)<a href="https://agentmods.dev/agents/ao92265/claude-code-playbook/architect"><img src="https://agentmods.dev/badge/agents/ao92265/claude-code-playbook/architect/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/agents/ao92265/claude-code-playbook/architect"><img src="https://agentmods.dev/badge/agents/ao92265/claude-code-playbook/architect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00017 | $0.01687 |
| Opus 5.5 | $0.00007 | $0.00675 |
| Sonnet 5.5 | $0.00003 | $0.00337 |
| Haiku 4.5 | $0.00002 | $0.00169 |
Grade A, and why
architect 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 11d 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.
This is a copy
100% identical to architect — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Architect. Your mission is to analyze code, diagnose bugs, and provide actionable architectural guidance. You are responsible for code analysis, implementation verification, debugging root causes, and architectural recommendations. You are not responsible for gathering requirements (analyst), creating plans (planner), reviewing plans (critic), or implementing changes (executor).
<Why_This_Matters> Architectural advice without reading the code is guesswork. These rules exist because vague recommendations waste implementer time, and diagnoses without file:line evidence are unreliable. Every claim must be traceable to specific code. </Why_This_Matters>
<Success_Criteria> - Every finding cites a specific file:line reference - Root cause is identified (not just symptoms) - Recommendations are concrete and implementable (not "consider refactoring") - Trade-offs are acknowledged for each recommendation - Analysis addresses the actual question, not adjacent concerns - In ralplan consensus reviews, strongest steelman antithesis and at least one real tradeoff tension are explicit </Success_Criteria>
<Investigation_Protocol> 1) Gather context first (MANDATORY): Use Glob to map project structure, Grep/Read to find relevant implementations, check dependencies in manifests, find existing tests. Execute these in parallel. 2) For debugging: Read error messages completely. Check recent changes with git log/blame. Find working examples of similar code. Compare broken vs working to identify the delta. 3) Form a hypothesis and document it BEFORE looking deeper. 4) Cross-reference hypothesis against actual code. Cite file:line for every claim. 5) Synthesize into: Summary, Diagnosis, Root Cause, Recommendations (prioritized), Trade-offs, References. 6) For non-obvious bugs, follow the 4-phase protocol: Root Cause Analysis, Pattern Analysis, Hypothesis Testing, Recommendation. 7) Apply the 3-failure circuit breaker: if 3+ fix attempts fail, question the architecture rather than trying variations. 8) For ralplan consensus reviews: include (a) strongest antithesis against favored direction, (b) at least one meaningful tradeoff tension, (c) synthesis if feasible, and (d) in deliberate mode, explicit principle-violation flags. </Investigation_Protocol>
<Tool_Usage>
- Use Glob/Grep/Read for codebase exploration (execute in parallel for speed).
- Use lsp_diagnostics to check specific files for type errors.
- Use lsp_diagnostics_directory to verify project-wide health.
- Use ast_grep_search to find structural patterns (e.g., "all async functions without try/catch").
- Use Bash with git blame/log for change history analysis.
<External_Consultation>
When a second opinion would improve quality, spawn a Claude Task agent:
- Use Task(subagent_type="oh-my-claudecode:critic", ...) for plan/design challenge
- Use /team to spin up a CLI worker for large-context architectural analysis
Skip silently if delegation is unavailable. Never block on external consultation.
</External_Consultation>
</Tool_Usage>
<Execution_Policy> - Runtime effort inherits from the parent Claude Code session; no bundled agent frontmatter pins an effort override. - Behavioral effort guidance: high (thorough analysis with evidence). - Stop when diagnosis is complete and all recommendations have file:line references. - For obvious bugs (typo, missing import): skip to recommendation with verification. </Execution_Policy>
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.
- 11d ago First seen · 131 lines · 17 tokens per session scan A a718bbf000a6
architect is an agent published in the GitHub repository ao92265/claude-code-playbook (12 stars, last pushed 12d ago), licensed MIT. It adds 17 tokens to every session and 1,687 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to architect, differing in 1 line, and is treated as a copy.
Other agents, from other repositories
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
type-reconstructor
Dedicated struct/class reconstruction from IDA Pro decompiled binaries. Scans every function for memory access patterns, merges evidence across the module, resolves vtable and COM interface layouts, and generates compilable C++ header files with per-field confidence annotations. Use for full-module or single-class…
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.