Index of every page on this site: llms.txt
All skills
tristanmanchester avatar

/display-quantitative-information

@3323bc9
by Tristan Manchestertristanmanchester/agent-skills3 stars
2
Run it yourself

Design, critique, or implement quantitative graphics, scientific figures, dashboards, and evidence tables. Use for display choice, scale/encoding integrity, uncertainty, and accessible chart handoff. Do not use for decorative illustration or general data cleaning without a quantitative display.

Use this Skill: https://skilld.dev/gh/tristanmanchester/agent-skills/display-quantitative-information

Nothing lands on disk. Nothing to clean up.

Fork this Skill

Edit a local copy. It keeps the author and licence.

referenceschart-spec.md

≈404 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Chart Specification

Use a structured spec when auditing, handing off, or asking another tool to render a chart. assets/chart-spec-template.json is compatible with scripts/audit_visual_display.py.

Minimum fields

  • title: working title, not marketing copy.
  • purpose: viewer task or decision.
  • chart_type: bar, dot, line, scatter, map, table, small_multiples, etc.
  • data_points: approximate count of visible observations.
  • variables: field names and derived variables.
  • data_grain: one row means what.
  • encodings: x, y, color, size, shape, facet, label.
  • axes: labels, units, zero baseline, scale type, axis breaks, dual axes, panel scales.
  • labels: direct labels, legend, source, definitions, annotations.
  • context: denominator, uncertainty, sample size, comparison baseline, time range.
  • design: grid, decorations, 3D, area/volume encodings, color count, color-only identification.
  • integrity_measurements: data and visual percent effects where measurable.
  • medium: destination, color reliance, minimum text size.

Spec-first workflow

  1. Draft the spec before rendering.
  2. Run python3 scripts/audit_visual_display.py --spec spec.json --format markdown.
  3. Fix severe and warning findings.
  4. Render the chart or provide implementation guidance.
  5. Add final notes for source, units, uncertainty, and accessibility.

Do not overfit to the template

The template is a forcing function, not a bureaucracy. Skip irrelevant fields in the user-facing answer, but keep enough structure that another agent or developer can implement the display without guessing.

Source: SKILL.md on GitHub

Skill behaviors

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

Third-party checks

No alerts1mo3 checks · Risk SAFE
  • Gen Agent Trust Hub1mo

    The skill is safe to use and adheres to best practices for data visualization auditing. It provides analytical scripts to evaluate chart integrity based on Tufte's principles. All scripts use only the Python standard library, do not perform network requests, and do not access sensitive system files. A minor risk is documented regarding the attack surface for indirect prompt injection when processing untrusted user data.

  • Socket1mo

    No alerts

  • Snyk1mo

    Risk: LOW · No issues

Provenance

Signed by skilld at 3323bc9. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 weeks ago.

Steadyupdated last month

Capability

Other metadata
compatibility
Bundled helpers require Python 3.10+ and use the standard library. The SVG renderer is a first-pass tool, not a full plotting or accessibility-validation system.
metadata
{
  "version": "2.1.0",
  "reviewed": "2026-09-13",
  "source-note": "Tufte-informed methods adapted from previously supplied study material; source book text and images are not bundled. No missing licence terms have been reconstructed."
}

README badge

README badge for tristanmanchester/agent-skills/display-quantitative-information