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AC mermaid-diagrams

Author, render, troubleshoot, and review Mermaid diagrams for documentation, architecture, processes, and technical communication. Use when a versionable diagram must communicate a defined audience job across a real renderer, including narrative, hierarchy, labels, legends, accessibility fallback, and uncertainty. Do not use for C4 level/model ownership, architecture decisions, or full accessibility conformance.

magnus919/agent-skills Agent Skills author: magnus919 MIT 13 files · 1 script body ≈ 2 377 tokens Open the sourcegithub.com↗ analyzed 26 h ago

Author, render, troubleshoot, and review Mermaid diagrams for documentation, architecture, processes, and technical communication.

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerGitHubPlaywrightWriting and documentsMarketingAI and agentstype 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
A
98/100
safety, quality, tests
Safety 60%
99
Quality 40%
96
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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
    • low Dangerous commands cmd-privilege references/pdf-rendering-pipeline.md:98
      Privilege escalation / world-writable permissions (detector / deny-list definition)
      args: ["--no-sandbox", "--disable-setuid-sandbox"]
      detector

    Files scanned: 12. 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 54/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 1 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 17 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2377 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (4 tags): a typed call is more reliable
    • medium 5 test cases, all positive: not one "should refuse" or "should ask first"
    • low No test case covers injection arriving through data

    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
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 415: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 17 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (8 of 9)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.