SKILLEMALL.ai

AC pudding-data-story

Build or revise reader-first interactive data stories and visual essays in the spirit of The Pudding. Use for Pudding-style websites, scrollytelling, scroll-driven graphics, interactive data journalism, data-backed longform features, animated visual explanations, storyboards, or audits of work that feels like a dashboard or ordinary chart. Also trigger for 中文 requests mentioning 数据叙事、滚动叙事、交互可视化、动态数据故事、Pudding 水准, or “不要像普通图表”. Covers editorial framing, data receipts, visual form, meaningful interaction, motion, implementation architecture, accessibility, mobile behavior, and QA.

ClawHub Agent Skills author: tseng71 v1.0.0 MIT-0 10 files body ≈ 2 189 tokens Open the sourceclawhub.ai analyzed 2 d ago

Build or revise reader-first interactive data stories and visual essays in the spirit of The Pudding.

As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorMedia and videoSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
52/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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: 10. 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 52/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 6 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 100Steps. 67 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2189 tokens
    • low 10 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)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 585: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 67 items
    • +4Reference files are cited in the instructions (6 of 6)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a coherent data-storytelling guide with a local audit helper, and I did not find hidden credential access, persistence, exfiltration, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 27 Jul 2026