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DC make-pdf

Turn any markdown file into a publication-quality PDF. (gstack)

garrytan/gstack Agent Skills author: garrytan MIT 44 files · 36 scripts body ≈ 5 020 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Turn any markdown file into a publication-quality PDF.

As a process C 55/100 · Has gaps — References files that are not bundled: data.png, arch.png, shot.png

GeneratorWordSoftware developmentAI and agentsMarketingtype 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
D
74/100
safety, quality, tests
Safety 60%
95
Quality 40%
43
Run on models
none yet
Process rating
C
55/100
Has gaps
References files that are not bundled: data.png, arch.png, shot.png
Tools and files w 18
0
When it triggers w 12
20
Inputs and preconditions w 11
30
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.

Broad scope 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 asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read AskUserQuestion

Files scanned: 18. 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 body-long SKILL.md body ≈ 5020 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: data.png
  • warning missing-ref reference to a missing file: arch.png
  • warning missing-ref reference to a missing file: shot.png
  • note frontmatter-key unknown frontmatter key "preamble-tier"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 55/100

Will not run. References files that are not bundled: data.png, arch.png, shot.png
  • 0Tools and files. 3 referenced file(s) missing: data.png, arch.png, shot.png
  • 20When it triggers. No condition that starts the skill
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 1 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 5020 tokens
  • 100Steps. 14 steps
  • 100Failures and branches. 5 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 tags): a typed call is more reliable

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 63: 120–800 characters recommended
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 14 items
  • +3Output format is stated explicitly
  • +4Has examples (18 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 43.

In the sandbox The scripts kept to themselves

The skill's scripts were run in a throwaway machine: no network, fake keys in the home directory, a tracer watching. We wrote down what they did. Reaching for the network or for secrets caps the technical grade at C; a quiet run adds no points.

Запущено 12 скриптов, ещё 5 не поместились в лимит; каждому дали двадцать секунд, поддельный домашний каталог с ключами и сеть, в которой ничего нет.

src/asideClient.tsничего за пределами своей папки
src/cli.tsничего за пределами своей папки
src/commands.tsничего за пределами своей папки
src/diagram-prepass.tsничего за пределами своей папки
src/docx-images.tsничего за пределами своей папки
src/html-to-docx.d.tsничего за пределами своей папки
src/html-to-vdom.d.tsничего за пределами своей папки
src/image-policy.tsничего за пределами своей папки
src/image-size.tsничего за пределами своей папки
src/orchestrator.tsничего за пределами своей папки
src/pdftotext.tsничего за пределами своей папки
src/print-css.tsничего за пределами своей папки

19 Oct 2026