SKILLEMALL.ai

AC svg-architecture-diagram

Create professional, publication-quality technical architecture diagrams using pure SVG in HTML, then screenshot via Playwright. Produces crisp, pixel-perfect diagrams with precise connection lines, color-coded modules, and clear text at any resolution. Use when: (1) user asks for a system architecture diagram, (2) user wants a technical component diagram or flow chart, (3) user needs a data flow or pipeline visualization, (4) any diagram requiring accurate text labels and precise connecting lines. Triggers: "architecture diagram", "架构图", "技术架构", "system diagram", "component diagram", "flow diagram", "数据流图", "模块图", "draw architecture", "画架构图", "technical diagram". Prefer this over AI image generation for any diagram with text labels.

ClawHub Agent Skills author: Garming v1.2.0 MIT-0 6 files body ≈ 1 727 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorPlaywrightInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 0

    ✓ No critical or high findings

    Files scanned: 6. 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 64/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 31 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1727 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (7 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

    • +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
    • +5Description quotes 6 example trigger phrases
    • +3Description length 743: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 31 items
    • +4Has examples (9 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

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

    External checks

    ClawHub: clean
    This skill is a coherent diagram-generation helper, with some disclosed network-related options that users should handle carefully.
    LLM: benign (high) · VirusTotal: · 29 May 2026