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BF pandoc-convert

Convert documents between 40+ formats using pandoc CLI. Handles Markdown ↔ Word ↔ PDF ↔ HTML ↔ LaTeX ↔ EPUB with smart defaults, professional templates, and comprehensive tooling.

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 1 922 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Convert documents between 40+ formats using pandoc CLI.

As a process F 47/100 · Will not run — References files that are not bundled: references/conversion-guides.md, references/format-matrix.md, references/troubleshooting.md

IntegrationLaTeXWordSoftware developmentResearchtype 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
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
Run on models
none yet
Process rating
F
47/100
Will not run
References files that are not bundled: references/conversion-guides.md, references/format-matrix.md, references/troubleshooting.md
Tools and files w 18
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/conversion-guides.md
  • warning missing-ref reference to a missing file: references/format-matrix.md
  • warning missing-ref reference to a missing file: references/troubleshooting.md
  • warning missing-ref reference to a missing file: references/format-guide.md
  • warning missing-ref reference to a missing file: references/quick-reference.md
  • warning missing-ref reference to a missing file: references/templates.md

Process rating: all ten parameters 47/100

Will not run. References files that are not bundled: references/conversion-guides.md, references/format-matrix.md, references/troubleshooting.md
  • 0Tools and files. 6 referenced file(s) missing: references/conversion-guides.md, references/format-matrix.md, references/troubleshooting.md
  • 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
  • 40Consistency. Frontmatter name (pandoc-convert) differs from the folder (pandoc-convert-openclaw)
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 54 steps
  • 100Execution cost. Instruction body is 1922 tokens
  • 100Running it twice. No mutating operations
  • low 13 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)
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 179: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 54 items
  • +3Output format is stated explicitly
  • +4Has examples (7 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.