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AC competitor-docs

Search and analyze competitor documentation archives using full-text search (FTS). Use when you need to find information in structured documentation folders containing articles with source URLs (marked with "*Source:" pattern). Provides fast BM25-ranked search across thousands of articles with automatic source URL extraction for citations. Ideal for competitive intelligence research, feature comparisons, and documentation lookups. Requires indexing documentation first with `docs.py index`.

modbender/skill-library-mcp Agent Skills author: modbender MIT 8 files body ≈ 1 349 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Search and analyze competitor documentation archives using full-text search (FTS).

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerKubernetesWriting and documentstype 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
A
95/100
safety, quality, tests
Safety 60%
98
Quality 40%
91
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

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 Risky intent intent-offensive-security references/ci-patterns.md:85
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      # Ransomware
    • low Risky intent intent-offensive-security references/ci-patterns.md:86
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      scripts/search_docs.py ./docs "ransomware\|immutable\|air.?gap" --mode regex
      quoted

    Files scanned: 8. 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 53/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1349 tokens
    • 100Running it twice. No mutating operations
    • 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 494: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 15 items
    • +4Has examples (11 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 6 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.