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AD github-mcp

Use the GitHub MCP server (github-mcp-server) to browse repositories, manage issues and PRs, analyze code, search files, monitor CI/CD workflows, and automate GitHub operations. Triggers when user asks to search code, manage GitHub issues/PRs, view commits, analyze repository structure, check CI/CD status, fork repos, create branches, or any GitHub-related operations that require API access. Works with local stdio-based github-mcp-server binary or remote HTTP endpoint (https://api.githubcopilot.com/mcp/).

ClawHub Agent Skills author: zwj-opener v0.1.0 MIT-0 3 files body ≈ 187 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 40/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

IntegrationGitHubAI and agentsSoftware developmentInfrastructuretype 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
D
40/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 40/100

    • 0Steps. Prose only: no discrete steps
    • 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
    • 40Consistency. Frontmatter name (github-mcp) differs from the folder (zwj-github-mcp)
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Execution cost. Instruction body is 187 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
    • +4Description does not say when NOT to use the skill (false activations)
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 510: enough signal without eating the budget
    • +4Structure: 8 headings
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

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

    External checks

    ClawHub: suspicious
    This GitHub integration is purpose-aligned but needs review because it can use a GitHub token for real repository changes and recommends a remote authenticated endpoint without enough safety guidance.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026