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AC auto-repo-setup

Diagnose, repair, and standardize repository setup and safe Git workflows for Claude Code or Codex. Use when a repository will not run, a collaborator is onboarding, dependencies or credentials are missing, the user wants startup sync, SessionStart output is duplicated, project instructions or hooks need auditing, or commit/push/conflict/history-cleanup needs a guarded workflow. Route ordinary startup behavior through project instructions or a natural language request; use lifecycle hooks only when behavior must occur before the first prompt and the target runtime has been verified.

daymade/claude-code-skills Claude Code author: daymade 10 files · 1 script body ≈ 2 486 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Diagnose, repair, and standardize repository setup and safe Git workflows for Claude Code or Codex.

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Failures and branches w 10
50
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 8. 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 61/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 51 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2486 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (3 tags): a typed call is more reliable
    • medium 4 test cases, all positive: not one "should refuse" or "should ask first"

    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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 589: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 51 items
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.