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基于《AI超级个体》第二章的技术理解、产品思维、业务洞察和推进落地四项能力，诊断从岗位执行者到全栈产品经理的差距，并生成真实项目驱动的 90 天升级路径。用于“能力升级”“产品思维”“全栈 PM”“从执行者到操盘手”等请求。

ClawHub Agent Skills author: 菜根老谭 v0.1.0 MIT-0 3 files body ≈ 945 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

基于《AI超级个体》第二章的技术理解、产品思维、业务洞察和推进落地四项能力，诊断从岗位执行者到全栈产品经理的差距，并生成真实项目驱动的 90 天升级路径。用于“能力升级”“产品思维”“全栈 PM”“从执行者到操盘手”等请求。

As a process F 35/100 · Will not run — References files that are not bundled: assets/90天全栈PM成长计划.docx

Proceduretype 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
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: assets/90天全栈PM成长计划.docx
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: assets/90天全栈PM成长计划.docx

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: assets/90天全栈PM成长计划.docx
  • 0Tools and files. 1 referenced file(s) missing: assets/90天全栈PM成长计划.docx
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 100Steps. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 945 tokens
  • 100Running it twice. No mutating operations

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 112: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: clean
This skill is a career-planning assistant that creates local reports and uses a bundled template, with no evidence of code execution, exfiltration, or deceptive behavior.
LLM: benign (high) · VirusTotal: · 10 Sept 2026