kdense-matplotlib

name

kdense-matplotlib

description

Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.

Kdense Matplotlib

Use this Codex adapter for the pinned upstream scientific skill.

Catalog status

• Status: inactive
• Source: kdense
• Audit reasons: executable-content
• Upstream license: https://github.com/matplotlib/matplotlib/tree/main/LICENSE
• Inventory: ../../inventory.json
• Upstream instructions: ../../../vendor/scientific-agent-skills/skills/matplotlib/SKILL.md

Procedure

1. Resolve the plugin root as three directories above this skill directory.
2. Read the matching inventory record and verify its status, reasons, source path, and pinned revision.
3. Do not read the upstream instructions until the user has seen every audit reason and given explicit acknowledgement. Acknowledgement permits instruction inspection only.
4. Treat upstream frontmatter as source metadata, not as Codex configuration. Follow the instruction body only where it is compatible with available Codex tools and the current user-approved plan.
5. Treat tools named for another agent runtime as capability requests. Map them to an available Codex tool only when the behavior is equivalent; otherwise report the unavailable capability.
6. Ask before credentials, package installation, new network hosts, remote compute, writes, paid services, destructive actions, or imported executable code.
7. Use $science-provenance for produced scientific outputs and $science-review before presenting scientific claims.

Boundaries

• This wrapper does not grant credentials, network access, package installation, or script execution.
• Do not change an inactive record to active from inside a research task.
• Preserve failures, uncertainty, source identifiers, and licensing constraints.