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node-link-and-diagram-layout

Choose and apply automatic layout strategies for node-link diagrams and connected-node visuals. Use when the user asks how to auto-arrange nodes, reduce line crossings, route edges, avoid overlaps, stabilize layout, or choose graph-layout algorithms for network diagrams, dependency graphs, database schema diagrams, ERDs, state machines, decision trees, flow diagrams, box-and-line editors, or other line-connected nodes.

75

Quality

92%

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-3

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

The body is a well-organized instruction-only skill with highly actionable algorithm and stack defaults, a clear sequenced workflow with a validation checklist, and clean progressive disclosure to verified reference files. Its only weakness is moderate verbosity and some overlap across the validation, anti-pattern, and output-expectation sections.

Suggestions

Consolidate the overlapping readability criteria that appear in step 8 (Validate), Anti-Patterns, and Output Expectations into a single checklist to reduce token redundancy.

Trim the Stack Defaults and Algorithm Defaults lists to the few top recommendations per graph family, moving exhaustive options into a reference file.

Consider pulling the detailed mobile/operational output expectations into the already-referenced foundations files so the body stays a concise overview.

DimensionReasoningScore

Conciseness

Mostly efficient and free of concept explanations Claude already knows, but the 158-line body carries some redundancy between step 8's readability checklist, Anti-Patterns, and Output Expectations that could be tightened to respect the token budget.

2 / 3

Actionability

Provides concrete, executable decision guidance — named algorithms (Reingold-Tilford, Buchheim, Sugiyama), named tools (dot, neato, fdp, sfdp, twopi, circo, ELK, React Flow+Dagre, Cytoscape.js), and explicit per-graph-type routing choices; code absence is not penalized for an instruction-only skill.

3 / 3

Workflow Clarity

An 8-step Core Workflow is clearly sequenced from graph classification through validation, with step 8 serving as an explicit readability/validaion checklist; no destructive or batch operation applies the cap.

3 / 3

Progressive Disclosure

The Overview-style body points to three verified one-level-deep reference files in a dedicated Reference Guide section and signals foundations references in the Overview, with detail appropriately split out of the main file.

3 / 3

Total

11

/

12

Passed

Description

100%Weight 40%Scale 1-3

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

The description is strong across all dimensions: it states concrete actions, supplies a rich set of natural trigger terms and diagram types, includes an explicit 'Use when' clause, and carves out a distinct niche. It is concise despite its breadth and avoids over-claims.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Choose and apply automatic layout strategies,' 'auto-arrange nodes, reduce line crossings, route edges, avoid overlaps, stabilize layout' — matching the anchor for listing several specific actions.

3 / 3

Completeness

Explicitly answers both 'what' (choose and apply layout strategies for connected-node visuals) and 'when' via a 'Use when the user asks...' clause with concrete triggering scenarios, satisfying the full what-and-when anchor.

3 / 3

Trigger Term Quality

Covers natural phrasing users would actually say ('auto-arrange nodes,' 'lines crossing,' 'route edges,' 'overlaps') plus many diagram types (network diagrams, dependency graphs, schema diagrams, ERDs, state machines, decision trees), giving strong natural-term coverage.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche — graph-layout algorithm choice for connected-node diagrams — with distinct triggers unlikely to fire for adjacent notation or general data-visualization skills; written in third person.

3 / 3

Total

12

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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