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figure-spec

Generate deterministic publication-quality architecture, workflow, and pipeline diagrams from structured JSON (FigureSpec) into editable SVG. Use when user says "架构图", "workflow 图", "pipeline 图", "确定性矢量图", "figure spec", "draw architecture", or needs precise, editable, publication-ready vector diagrams. Preferred over AI illustration for formal architecture/workflow figures.

Quality

76%

Does it follow best practices?

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SecuritybySnyk

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Fix and improve this skill with Tessl

tessl review fix ./skills/skills-codex/figure-spec/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

62%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The figure-generation core is excellent — a clear five-step workflow with validation-first rendering, error-recovery loops, a visual review checklist, schema tables, and concrete patterns/anti-patterns. However, the skill is weighed down by environment-specific reviewer-routing and legacy path-resolution machinery inlined in the body, and it depends on shared reference files that are not part of the bundle.

Suggestions

Move the 'Before each reviewer slot' reviewer-routing blockquote and the 'Review Tracing' section into a reference file (e.g. references/review-loop.md), keeping only a one-line pointer in SKILL.md — this machinery is not needed for the core figure-generation task.

Collapse the 5-layer FIGURE_RENDERER resolution chain to the canonical location plus a single fallback, and relocate the 'Phase 3.1 (Arch C)' migration history and pre-Phase-3.1 layout notes to a clearly-labeled deprecated/old-patterns section or reference file.

Complete the architecture JSON template (replace the '...' elisions in nodes/edges with fully-formed examples) so the primary template is copy-paste executable, matching the quality of the workflow and decision-diamond examples.

DimensionReasoningScore

Conciseness

Several padded sections unrelated to figure generation: the 'Before each reviewer slot' blockquote on reviewer-backend routing, and the 5-layer path-resolution chain narrating 'Phase 3.1 (Arch C) move', 'pre-Phase-3.1 layout', and install_aris_codex.sh re-run instructions — time-sensitive version/migration detail not placed in a deprecated section. Not 3 because this is more than 'some' unnecessary explanation; not 1 because the core workflow, schema, and patterns sections are lean and assume competence.

2 / 5

Actionability

Concrete executable commands throughout: 'python3 "$FIGURE_RENDERER" render <spec.json> --output <out.svg>', 'validate', 'schema', and 'rsvg-convert -f pdf', plus a complete copy-paste resolution script. Not 5 because the architecture JSON template contains '...' placeholder elisions and the 'spawn_agent' review invocation is a text sketch rather than an executable command.

4 / 5

Workflow Clarity

Steps 1-5 are clearly sequenced with 'Validate first' as an explicit checkpoint, feedback loops for error recovery ('If validation fails, inspect the error … and fix the JSON'; 'edit the JSON spec (never the generated SVG) and re-render'), a visual review checklist, and iterate-until thresholds (all axes ≥ 7/10). Matches the anchor-5 pattern fully.

5 / 5

Progressive Disclosure

Section headers are clear, but heavy operational machinery (reviewer routing policy, review tracing policy, the 5-layer tool resolution chain) is inlined in SKILL.md where it belongs in reference files, and the 'shared-references/' links point outside the skill bundle with no reference files present within it. Not 4 because content that should be separate is inline and the out-of-bundle references are not verifiable in the bundle structure.

3 / 5

Total

14

/

20

Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that clearly states what the skill does and when to use it, with natural bilingual trigger terms and explicit conflict-resolution guidance against AI illustration. Its main weaknesses are a few missing common synonyms and minor overlap risk with sibling diagramming skills.

DimensionReasoningScore

Specificity

Names the concrete transformation 'from structured JSON (FigureSpec) into editable SVG' with diagram types and output qualities — several specific actions with minor coverage gaps (validation and PDF conversion unmentioned). Not 3 because it goes beyond 1-2 generic actions; not 5 because it is essentially one generate-action with qualifiers rather than a comprehensive action list.

4 / 5

Completeness

Explicitly answers both: what ('Generate deterministic publication-quality architecture, workflow, and pipeline diagrams from structured JSON (FigureSpec) into editable SVG') and when ('Use when user says …') with concrete trigger phrases. Matches the anchor-5 example pattern exactly.

5 / 5

Trigger Term Quality

Good natural coverage across languages — 'draw architecture', 'workflow 图', 'pipeline 图', 'figure spec', '确定性矢量图' — phrases a user would actually say. Not 5 because common synonyms like 'system diagram', 'topology', 'flowchart', or 'SVG' are absent.

4 / 5

Distinctiveness Conflict Risk

Clear niche (deterministic, editable, publication-ready vector diagrams) with an explicit preference statement ('Preferred over AI illustration for formal architecture/workflow figures'). Not 5 because triggers like 'workflow 图' and 'draw architecture' could still overlap with lighter flowchart/diagram skills that the description does not differentiate.

4 / 5

Total

17

/

20

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 1 suspicious

Warning

Total

13

/

16

Passed

Repository

wanshuiyin/Auto-claude-code-research-in-sleep

Path

skills/skills-codex/figure-spec/SKILL.md

Reviewed

Table of Contents

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