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AA taku-plan

Turn an approved design into an executable implementation plan. Three-step pipeline: scope + architecture review → design review (UI only) → plan writing. Auto-detects which step to start from based on project state. Invoke when DESIGN.md exists and is approved. Triggers on "write the plan", "create implementation plan", "plan this", "review this plan", "scope check", "architecture review", "design review", "is this plan buildable", "what could go wrong", "写计划", "制定方案", "规划实施", "架构评审", "这个方案可行吗", "有什么风险", or after /taku-think completes.

ClawHub Agent Skills author: KennyWu v1.0.0 MIT-0 6 files body ≈ 2 800 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process A 85/100 · Runs to the end — no weak spots found

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
A
85/100
Runs to the end
Result and completion w 14
60
When it triggers w 12
70
Inputs and preconditions w 11
70
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 85/100

    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 4 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 31 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2800 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +4Description does not say when NOT to use the skill (false activations)
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 10 example trigger phrases
    • +3Description length 542: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 31 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This planning skill appears useful and not malicious, but it can modify project planning files from broad review prompts with unclear write boundaries.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026