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AF github-digest

Generate a structured GitHub repo digest with briefing summary, categorized changes (breaking/major features/minor features/bug fixes), community discussions, and clickable source links. Use when: (1) user asks about a repo's recent activity, releases, PRs, or issues, (2) user wants a daily/weekly GitHub digest or briefing, (3) user asks 'what's new' or 'what happened' on a GitHub repo. NOT for: single PR review (use github skill), code changes (use coding-agent), or CI/issue management (use github skill directly).

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 783 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Generate a structured GitHub repo digest with briefing summary, categorized changes (breaking/major features/minor features/bug fixes), community discussions…

As a process F 55/100 · Will not run — References files that are not bundled: link

GeneratorGitHubSoftware developmentWriting and documentsAI 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
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
F
55/100
Will not run
References files that are not bundled: link
Tools and files w 18
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: link

Process rating: all ten parameters 55/100

Will not run. References files that are not bundled: link
  • 0Tools and files. 1 referenced file(s) missing: link
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 50When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 21 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 783 tokens
  • 100Running it twice. No mutating operations

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
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 520: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 21 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.