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CC perl-environment-setup

This skill should be used when the user asks to "install perlbrew", "set up Perl environment", "install Perl version", "manage Perl versions", "switch Perl version", "install plenv", or mentions Perl version management, development environment setup, or multiple Perl installations.

Jamie-BitFlight/claude_skills Agent Skills author: Jamie-BitFlight MIT 1 file body ≈ 1 631 tokens Open the sourcegithub.com↗ analyzed 8 d ago

This skill should be used when the user asks to "install perlbrew", "set up Perl environment", "install Perl version", "manage Perl versions", "switch Perl…

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

IntegrationSoftware 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
81/100
safety, quality, tests
Safety 60%
75
Quality 40%
89
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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

    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 · 5

    ✓ No critical or high findings

    Medium and low: 5
    • medium Dangerous commands cmd-pipe-to-shell SKILL.md:27
      Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)
      curl -L https://install.perlbrew.pl | bash
      vendor-host
    • medium Dangerous commands cmd-pipe-to-shell SKILL.md:299
      Downloads and executes remote code from an unrecognised host (pipe to shell) (the skill's own vendor host)
      curl -L https://install.perlbrew.pl | bash
      vendor-host
    • medium Dangerous commands cmd-shell-rc SKILL.md:315
      Writes to a shell startup file
      echo 'source ~/perl5/perlbrew/etc/bashrc' >> ~/.bashrc
    • medium Dangerous commands cmd-shell-rc SKILL.md:328
      Writes to a shell startup file
      echo 'export PATH="$HOME/.plenv/bin:$PATH"' >> ~/.bashrc
    • medium Dangerous commands cmd-shell-rc SKILL.md:329
      Writes to a shell startup file
      echo 'eval "$(plenv init -)"' >> ~/.bashrc

    Files scanned: 1. 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 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 4 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 10 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1631 tokens
    • low 15 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

    • +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
    • +5Description quotes 6 example trigger phrases
    • +3Description length 282: enough signal without eating the budget
    • +4Structure: 31 headings
    • +3Step-by-step instructions: 10 items
    • +4Has examples (20 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.