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BD vibe-coding-toolkit

Vibe Coding Toolkit — AI开发项目治理工具包（单包，含4个模块：health-check / commit-check / task-manager / project-init）。零网络访问、零数据外传；仅读取平台注入的工作区变量与家目录用于平台探测；所有写入仅限当前项目目录内。当用户需要给项目做体检/健康巡检、验证 AI 提交是否真实合规、用自然语言管理任务流转、初始化项目治理骨架（自动建本地 git 库并管理版本，不需要账号，用户零操作）时，加载本技能并按 SKILL.md「子命令路由表」执行对应脚本。

ClawHub Agent Skills author: clancy-feng v1.2.0 MIT-0 25 files · 6 scripts body ≈ 1 041 tokens Open the sourceclawhub.ai↗ analyzed 34 h ago

Vibe Coding Toolkit — AI开发项目治理工具包（单包，含4个模块：health-check / commit-check / task-manager /…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype 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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
43/100
Unfinished process
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 · 0

✓ No critical or high findings

Files scanned: 25. 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")
  • note frontmatter-key unknown frontmatter key "title"
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "priority"

Process rating: all ten parameters 43/100

  • 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
  • 30Running it twice. 15 mutating operations with no state check
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1041 tokens

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
  • +2Single-language instructions
  • +3Description length 268: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 17 items
  • +4Reference files are cited in the instructions (4 of 5)
  • +1License stated

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

External checks

ClawHub: suspicious
This skill is mostly a local project-governance tool, but it can automatically stage and commit all repository changes and guide file-restoring rollbacks without enough per-action safeguards.
LLM: suspicious (high) · 27 Aug 2026