SKILLEMALL.ai

BC git-cli-tool-pro

面向企业研发团队的高级Git命令行工具,提供自动化脚本、深度仓库诊断、工作流模板、故障排除与批量操作能力。核心能力: - Git自动化脚本库 - 深度仓库诊断与分析 - 标准化工作流模板 - 故障排除与恢复 - 批量Git操作 - 多仓库管理 适用场景: - 企业级Git工作流自动化 - 仓库健康诊断 - 团队标准化操作 - 复杂故障排除 差异化: - 专业版完全兼容免费版命令,支持平滑升级 - 提供自动化脚本和批量操作 - 内置深度诊断和工作流模板 - 支持多仓库统一管理 ...

ClawHub Hermes author: 天轰穿 v1.0.1 MIT-0 3 files body ≈ 1 905 tokens Open the sourceclawhub.ai analyzed 2 d ago

面向企业研发团队的高级Git命令行工具,提供自动化脚本、深度仓库诊断、工作流模板、故障排除与批量操作能力。核心能力: - Git自动化脚本库 - 深度仓库诊断与分析 - 标准化工作流模板 - 故障排除与恢复 - 批量Git操作 - 多仓库管理 适用场景: - 企业级Git工作流自动化 - 仓库健康诊断 -…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
C
51/100
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.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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-long-hermes description is 246 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • 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 "edition"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 51/100

  • 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. 1 mutating operations with no state check
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 28 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1905 tokens
  • low 16 top-level sections: this looks like several domains in one skill

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
  • +2Single-language instructions
  • +3Description length 246: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
This Git automation skill is mostly aligned with its purpose, but it needs review because it can automatically stage, commit, push, rebase, and delete branches across repositories without clear user-controlled safeguards.
LLM: suspicious (high) · 29 Aug 2026