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AD ai-smart-commit

智能 Git 提交信息生成工具。根据代码 diff 自动生成规范的 commit message、PR 描述和 Release Notes。 **当以下情况时使用此 Skill**: (1) 需要根据代码变更生成 commit message (2) 需要编写 PR/MR 描述 (3) 需要生成 Release Notes / Changelog (4) 用户提到"commit"、"提交"、"PR描述"、"changelog"、"发布说明" (5) 想让 git log 更规范、更有价值 (6) 需要分析代码变更的影响范围

ClawHub Agent Skills author: VelenGao v1.0.1 MIT-0 5 files body ≈ 886 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentWriting and documentsInfrastructuretype 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
D
45/100
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: 5. 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 45/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 20 mutating operations with no state check
  • 60Tools and files. Uses tools (git) that frontmatter does not declare
  • 100Steps. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 886 tokens
  • 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)
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 265: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (7 code blocks)

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

External checks

ClawHub: clean
This appears to be a development-writing skill with minor activation and language-selection concerns, but no evidence of hidden, destructive, or credential-stealing behavior.
LLM: benign (medium) · VirusTotal: · 28 May 2026