SKILLEMALL.ai
RU Sign in

AD panda-git-commit

智能生成符合 Conventional Commits 规范的 Git Commit Message。 自动检测 monorepo scope，支持将变更按功能拆分为多个 commit。 触发词："commit"、"提交"、"生成 commit message"、"拆分提交"、 "split commits"、"git commit"。

ClawHub Agent Skills author: hash panda v1.0.2 MIT-0 15 files body ≈ 2 152 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

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

ReferenceSoftware developmenttype 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
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: 15. 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. 54 mutating operations with no state check
  • 60Tools and files. Uses tools (git) that frontmatter does not declare
  • 100Steps. 57 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2152 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (10 tags): a typed call is more reliable

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
  • -31 of 7 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 169: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 57 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This skill is a disclosed Git commit-message helper that reads repository changes and history, with optional local config writes and commits tied to user-invoked workflow steps.
LLM: benign (high) · VirusTotal: · 29 May 2026