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CD hunt-websocket

Hunt WebSocket vulnerabilities

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 1 file body ≈ 1 995 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Hunt WebSocket vulnerabilities

As a process D 36/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

AnalyzerSecuritytype 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
D
36/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
When it triggers w 12
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 · 0

    ✓ No critical or high findings

    Files scanned: 1. 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"
    • note frontmatter-key unknown frontmatter key "report_count"

    Process rating: all ten parameters 36/100

    • 0Steps. Prose only: no discrete steps
    • 0Result and completion. Does not say what the result is
    • 0When it triggers. No condition that starts the skill
    • 0Failures and branches. Linear process with no failure handling
    • 30Running it twice. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1995 tokens
    • 100Progress reporting. Reports progress
    • low 10 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 30: 120–800 characters recommended
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Structure: 11 headings
    • +4Has examples (1 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.