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AF chart-generator

Data visualization chart generator. Use when user needs to create charts from data for reports, presentations, or documents. Supports bar, line, pie, scatter, radar charts with PNG/SVG output. 数据可视化、图表生成、数据报告。

ClawHub Agent Skills author: ToBeWin v1.0.2 MIT-0 2 files body ≈ 3 945 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 28/100 · Will not run — References files that are not bundled: {base64_img}

GeneratorData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
F
28/100
Will not run
References files that are not bundled: {base64_img}
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: {base64_img}
  • note frontmatter-key unknown frontmatter key "dependencies"

Process rating: all ten parameters 28/100

Will not run. References files that are not bundled: {base64_img}
  • 0Tools and files. 1 referenced file(s) missing: {base64_img}
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (chart-generator) differs from the folder (chart-maker)
  • 100Steps. 23 steps
  • 100Execution cost. Instruction body is 3945 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
  • -212 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 209: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This is a local chart-generation skill with some documentation inconsistencies, but its file reads and document outputs are disclosed in the body and fit the chart/reporting purpose.
LLM: benign (high) · VirusTotal: · 29 May 2026