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CD claude-code-mastery

Master Claude Code for coding tasks. Includes setup scripts, dev team subagents (starter pack or full team), self-improving learning system, diagnostics, and troubleshooting.

modbender/skill-library-mcp Agent Skills author: modbender MIT 32 files · 10 scripts body ≈ 2 500 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Master Claude Code for coding tasks.

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsSoftware developmenttype 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
C
64/100
safety, quality, tests
Safety 60%
58
Quality 40%
72
Run on models
none yet
Process rating
D
46/100
Unfinished process
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 10

✓ No critical or high findings

Medium and low: 10
  • medium Dangerous commands cmd-shell-rc docs/troubleshooting.md:74
    Writes to a shell startup file
    echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.zshrc  # or ~/.bashrc
  • medium Dangerous commands cmd-pipe-to-shell-known-host docs/troubleshooting.md:88
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -fsSL https://claude.ai/install.sh | bash
  • medium Dangerous commands cmd-pipe-to-shell-known-host docs/troubleshooting.md:127
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash
  • medium Dangerous commands cmd-pipe-to-shell-known-host scripts/02-install-claude-code.sh:27
    Pipe-to-shell installer from a well-known host (still executes remote code)
    curl -fsSL https://claude.ai/install.sh | sh
  • medium Dangerous commands cmd-shell-rc scripts/02-install-claude-code.sh:47
    Writes to a shell startup file
    echo "   For bash (~/.bashrc):"
  • medium Dangerous commands cmd-shell-rc scripts/02-install-claude-code.sh:50
    Writes to a shell startup file
    echo "   For zsh (~/.zshrc):"
  • medium Dangerous commands cmd-shell-rc scripts/02-install-claude-code.sh:53
    Writes to a shell startup file
    echo "   Then restart your terminal or run: source ~/.zshrc"
  • medium Dangerous commands cmd-shell-rc scripts/08-troubleshoot.sh:87
    Writes to a shell startup file
    echo "         echo 'export PATH=\"\$HOME/.local/bin:\$PATH\"' >> ~/.zshrc"
  • low Dangerous commands cmd-pipe-to-shell-known-host scripts/01-check-dependencies.sh:46
    Pipe-to-shell installer from a well-known host (still executes remote code) (string literal in code, not executed)
    echo "   Install: curl -fsSL https://bun.sh/install | bash"
    code literal
  • low Dangerous commands cmd-pipe-to-shell-known-host scripts/05-setup-claude-mem.sh:124
    Pipe-to-shell installer from a well-known host (still executes remote code) (string literal in code, not executed)
    echo "   Install: curl -fsSL https://bun.sh/install | bash"
    code literal

Files scanned: 32. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 21 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2500 tokens
  • 100Running it twice. Mutating operations check current state
  • low 14 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
  • -2localhost URLs: will not work for another user
  • -31 of 9 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 174: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (2 of 6)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.