SKILLEMALL.ai

AB paper-framework-figure-studio-pro

Use when the user wants to design, prompt, generate, critique, or integrate publication-ready research-paper framework figures: method overview diagrams, architecture diagrams, pipeline/process diagrams, agent workflows, system/data-flow figures, mechanism-intuition figures, case walkthrough panels, and reviewer-facing schematic figures. Generated from research-paper-figure-skill-factory v1.0.1 with full-feasible local PDF evidence, startup-plan-only first replies, strict text/image separation, mandatory text-candidate to visual-candidate setup to image-only candidate board to candidate-review selection workflow, optional sample images, ChatGPT web Create image / ChatGPT Images 2.0, Codex $imagegen first, all-step/current-position state footers, and next-question help in every text reply.

ClawHub Agent Skills author: c-narcissus v1.2.0 MIT-0 32 files body ≈ 2 293 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 68/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
68/100
Nearly there
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: 32. 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 68/100

    • 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
    • 85Steps. 78 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 9 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2293 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • +4No input/output examples
    • +2Single-language instructions
    • +3Description length 799: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 78 items
    • +4Reference files are cited in the instructions (11 of 11)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This is a disclosed research-figure workflow skill with no executable installer; the main cautions are language rigidity and sharing paper material with image-generation tools.
    LLM: benign (high) · VirusTotal: · 29 May 2026