SKILLEMALL.ai
GitHub ↗ RU Sign in

BC web2-recon

Web2 recon pipeline

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 2 files body ≈ 3 460 tokens Open the sourcegithub.com↗ analyzed 22 h ago

Web2 recon pipeline

As a process C 64/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, progress reporting

ProcedureGitHubSecuritytype 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
B
90/100
safety, quality, tests
Safety 60%
98
Quality 40%
78
Run on models
none yet
Process rating
C
64/100
Has gaps
When it triggers w 12
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Dangerous commands cmd-shell-rc SKILL.md:43
      Writes to a shell startup file (code comment; documentation of a security skill)
      echo 'export CHAOS_API_KEY  # then set your ProjectDiscovery Chaos API key as the value' >> ~/.zshrc
      commentsecurity skill
    • low Dangerous commands cmd-cron-mention SKILL.md:335
      Mentions editing / listing crontab (documentation of a security skill)
      # Schedule: crontab -e → 0 8 * * * /bin/bash ~/monitors/subs-watch.sh
      security skill

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning description-short description under 40 chars: too little signal for triggering
    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "source_repo"
    • note frontmatter-key unknown frontmatter key "source_type"
    • note frontmatter-key unknown frontmatter key "date_added"
    • note frontmatter-key unknown frontmatter key "license_source"
    • note frontmatter-key unknown frontmatter key "sources"

    Process rating: all ten parameters 64/100

    • 0When it triggers. No condition that starts the skill
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 20 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3460 tokens
    • 100Running it twice. Mutating operations check current state
    • 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 19: 120–800 characters recommended
    • +2Single-language instructions
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 20 items
    • +3Output format is stated explicitly
    • +4Has examples (15 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.