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BC impl-project-manager

实施项目经理工具箱 — IT/软件交付项目的全流程管理，覆盖项目管理（立项、里程碑、风险、变更）、主合同签订回款跟踪、采购分包付款跟踪三大模块。数据存储在飞书在线表格，PM 在飞书录入，Skills 读取分析后通过对话确认并自动更新飞书表格。触发词：项目管理、项目立项、里程碑、回款跟踪、分包管理、付款跟踪、进度报告、合同跟踪、项目计划书、结项复盘。

ClawHub Agent Skills author: smallKeyboy v1.0.0 MIT-0 12 files body ≈ 674 tokens Open the sourceclawhub.ai↗ analyzed 25 h ago

实施项目经理工具箱 — IT/软件交付项目的全流程管理，覆盖项目管理（立项、里程碑、风险、变更）、主合同签订回款跟踪、采购分包付款跟踪三大模块。数据存储在飞书在线表格，PM 在飞书录入，Skills…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

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
89/100
safety, quality, tests
Safety 60%
98
Quality 40%
75
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token references/feishu-config.md:7
    High-entropy token-like string (may be an id, hash or a credential)
    - **App Secret：** oZ6e…tk8
  • low Secrets in code secret-high-entropy-token scripts/feishu_api.py:13
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    APP_SECRET = os.environ.get("FEISHU_APP_SECRET", "oZ6e…tk8")
    quoted

Files scanned: 12. 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")

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 44 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 674 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)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 175: enough signal without eating the budget
  • +4Structure: 22 headings
  • +3Step-by-step instructions: 44 items
  • +4Reference files are cited in the instructions (7 of 7)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
The skill is a coherent Feishu project-management tool, but it exposes a real Feishu app secret and automatically grants broad organization-wide edit access to newly created project sheets.
LLM: suspicious (high) · 28 May 2026