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CC implementing-secret-scanning-with-gitleaks

This skill covers implementing Gitleaks for detecting and preventing hardcoded secrets in git repositories. It addresses configuring pre-commit hooks, CI/CD pipeline integration, custom rule authoring for organization-specific secrets, baseline management for existing repositories, and remediation workflows for exposed credentials.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 8 files · 2 scripts body ≈ 2 658 tokens Open the sourcegithub.com↗ analyzed 5 d ago

This skill covers implementing Gitleaks for detecting and preventing hardcoded secrets in git repositories.

As a process C 63/100 · Has gaps — weak spots: failures and branches, running it twice, progress reporting

AnalyzerAWSGitHubSoftware 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
C
86/100
safety, quality, tests
Safety 60%
88
Quality 40%
82
Run on models
none yet
Process rating
C
63/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
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

    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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Dangerous commands cmd-privilege assets/template.md:112
      Privilege escalation / world-writable permissions
      sudo mv gitleaks /usr/local/bin/
    • medium Dangerous commands cmd-privilege references/api-reference.md:21
      Privilege escalation / world-writable permissions
      chmod +x gitleaks && sudo mv gitleaks /usr/local/bin/
    • low Secrets in code secret-aws-key assets/template.md:82
      AWS access key ID (placeholder value)
      regexes = ["AKIA…PLE"]
      placeholder
    • low Secrets in code secret-aws-key references/api-reference.md:41
      AWS access key ID (placeholder value)
      echo "aws_secret_access_key=AKIA…PLE" | gitleaks stdin
      placeholder

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"
    • note edit-residue the text marks something as outdated (lines 260): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 63/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 21 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 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 2658 tokens

    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
    • -43 reference files, but SKILL.md never points to them: the model will not open them
    • -32 of 2 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 333: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 21 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.