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SKILL verified MIT Self-run

Chart Image

skill-rylaispirit-rylai-codex-hermes-skills-chart-image · by Rylaispirit

Create publication-quality chart images from supplied data using an available plotting library, with explicit scales, labels, and visual QA.

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Install

$ agentstack add skill-rylaispirit-rylai-codex-hermes-skills-chart-image

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
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2d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

> Rylai Codex-Hermes Edition | Original portable workflow by Rylai

Runtime Compatibility

  • Codex: install under ~/.agents/skills/chart-image and use agents/openai.yaml for UI metadata.
  • Hermes: install under ~/.hermes/skills/chart-image or expose the bundle through skills.external_dirs.
  • Resolve bundled files relative to this skill directory; do not depend on paths from another runtime.
  • Map capabilities to the current runtime: Codex image generation uses image_gen; Hermes uses image_generate.
  • Verify binaries, packages, credentials, network access, and tool availability before execution.

Portable Chart Image

Generate a chart image from the actual supplied data.

Workflow

  1. Inspect the schema, units, missing values, categories, and time fields.
  2. Choose a chart type that matches the analytical question.
  3. Use an available library such as Matplotlib, Seaborn, Plotly, Vega-Lite, or the repository's existing chart stack.
  4. Label axes, units, legends, source, and uncertainty where relevant.
  5. Prefer node scripts/chart.mjs for portable SVG output, or use the repository's installed plotting stack.
  6. Inspect the rendered image for clipping, unreadable labels, misleading scales, and color contrast.

Integrity

  • Do not infer values that are absent from the data.
  • Start quantitative axes at an appropriate baseline and disclose truncation.
  • Preserve a reproducible script or notebook with the output.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.