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visual-asset-generator

Generate research visuals (figures, diagrams) with constraints, evidence alignment, and confidence ceilings.

allowed_tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite

model: sonnet

$ インストール

git clone https://github.com/DNYoussef/context-cascade /tmp/context-cascade && cp -r /tmp/context-cascade/skills/research/visual-asset-generator ~/.claude/skills/context-cascade

// tip: Run this command in your terminal to install the skill

SKILL.md

View on GitHub →

name: visual-asset-generator description: Generate research visuals (figures, diagrams) with constraints, evidence alignment, and confidence ceilings. allowed-tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite model: sonnet x-version: 3.2.0 x-category: research x-vcl-compliance: v3.1.1 x-cognitive-frames:

HON
MOR
COM
CLS
EVD
ASP
SPC

STANDARD OPERATING PROCEDURE

Purpose

Produce visual assets that accurately reflect research findings and constraints.
Apply constraint hygiene and explicit ceilings to avoid misrepresentation.
Maintain structure-first documentation for reproducibility.

Trigger Conditions

Positive: requests for figures, diagrams, charts, or schematics tied to research outputs.
Negative: purely aesthetic design work unrelated to research; or text-only summaries.

Guardrails

Constraints bucketed: HARD (data accuracy, confidentiality, formats), SOFT (style preferences), INFERRED (audience literacy).
Two-pass loop: draft visual plan → validate against evidence and constraints.
Explicitly cite data sources and uncertainty; include confidence ceilings where interpretation is inferred.

Inputs

Goal of the visual, target audience, and format requirements.
Data/metrics to visualize and source locations.
Style guidance and accessibility needs.

Workflow

Scope & Constraints: Capture objectives and constraint buckets; confirm INFERRED assumptions.
Design Plan: Choose visual types, annotations, and data mappings; check feasibility.
Create Draft: Build the asset with labeled data sources and units.
Validate: Verify data accuracy, legends, accessibility, and confidentiality; apply ceilings to interpretive statements.
Deliver & Store: Provide assets, source files, and usage notes; update references/examples.

Validation & Quality Gates

Data sources cited; transformations documented.
Visual readable and accessible; constraints respected.
Interpretations include confidence ceilings.

Response Template

**Goal & Constraints**
- HARD / SOFT / INFERRED.

**Design**
- Visual type, data sources, annotations.

**Validation**
- Accuracy checks, accessibility, risks.

**Deliverables**
- Asset paths, source files, usage notes.

Confidence: 0.80 (ceiling: research 0.85) - based on validated visuals and data checks.

Confidence: 0.80 (ceiling: research 0.85) - reflects validated visual assets tied to evidence.