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Detect 500+ types of hardcoded secrets (API keys, credentials, tokens) before they leak into git. Wraps GitGuardian's ggshield CLI.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 2 032 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Detect 500+ types of hardcoded secrets (API keys, credentials, tokens) before they leak into git.

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

IntegrationGitHubDockerAWSSlackInfrastructureSoftware developmentData and analyticstype 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
B
82/100
safety, quality, tests
Safety 60%
90
Quality 40%
71
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Dangerous commands cmd-pipe-to-shell README.md:222
    Downloads and executes remote code from an unrecognised host (pipe to shell) (documentation of a security skill)
    curl -fsSL https://molt.bot/install.sh | bash
    security skill
  • low Secrets in code secret-aws-key README.md:121
    AWS access key ID (placeholder value)
    echo 'AWS_KEY="AKIA…PLE"' > test-data/secrets.py
    placeholder
  • low Secrets in code secret-slack-token README.md:122
    Slack token (placeholder value)
    echo 'SLACK_TOKEN="xoxb…hij"' >> test-data/secrets.py
    placeholder
  • low Exfiltration read-dotenv README.md:127
    Reads a .env file (documentation of a security skill)
    export $(cat .env | xargs) && uv run python -c "
    security skill
  • low Exfiltration read-dotenv README.md:143
    Reads a .env file (documentation of a security skill)
    export $(cat .env | xargs) && uv run python -c "
    security skill
  • low Dangerous commands cmd-shell-rc SKILL.md:259
    Writes to a shell startup file (documentation of a security skill)
    echo 'export GITGUARDIAN_API_KEY="your-key"' >> ~/.bashrc
    security skill

Files scanned: 4. 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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 9 mutating operations with no state check
  • 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
  • 85Steps. 37 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2032 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 131: enough signal without eating the budget
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (24 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.