SKILLEMALL.ai
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C github-contribution

(no description)

ClawHub Agent Skills author: Andy Tien v1.7.4 MIT-0 7 files · 1 script body ≈ 6 157 tokens open source ↗ analyzed 25 h ago
ProcedureGitHubInfrastructuretype 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
C
60/100
Overall score
Safety 60%
100
Quality 40%
0
Tests bonus
0

How to improve

  1. Add a description to the frontmatter: without it the skill can never trigger.
  2. The SKILL.md body exceeds 5,000 tokens: move reference detail into references/ and load it on demand.
  3. Add evals/evals.json with 4–6 real requests and expected answers: the full check will then use your cases instead of a model draft.
  4. Add a spec.yaml with triggers and assertions (skilltest init): the behaviour contract for CI.

Guard findings · 0

✓ No critical or high findings

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Lint

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger
  • warning body-long SKILL.md body ≈ 6157 tokens (recommended < 5000); move details to references/

Process maturity 52/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Tools and files. Uses tools (bash, web, git, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6157 tokens
  • 85Steps. 159 steps, 1 vague phrases
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 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)
  • +3Description length 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2105 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 82 headings
  • +3Step-by-step instructions: 159 items
  • +4Has examples (22 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: suspicious
This skill is coherent for GitHub contribution automation, but it includes destructive Git synchronization steps that can discard local work and push changes without enough warning or confirmation.
LLM: suspicious (high) · 23 Jul 2026