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pymoo

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

60

Quality

72%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./bundled/skills/pymoo/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%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.

A highly actionable, well-structured guide with excellent progressive disclosure and executable examples, weakened by conceptual padding that Claude doesn't need and workflows that lack explicit validation checkpoints.

Suggestions

Trim conceptual padding (Problem Types definitions, the Overview, and the 'When to Use' list) that overlaps the routing boundary and restates the description.

Add explicit validation checkpoints to each workflow (e.g. after minimize(), verify feasibility via result.CV and check convergence before accepting the solution).

DimensionReasoningScore

Conciseness

The body is mostly efficient with substantial executable code, but it pads with concepts Claude already knows (Problem Types definitions, an Overview that restates the description, and a 'When to Use' list overlapping the routing boundary), so it is mostly efficient but could be tightened.

2 / 3

Actionability

It provides fully executable, copy-paste-ready code across all seven workflows with correct imports, concrete parameter values, and specific algorithm-selection tables — meeting the 'fully executable, specific examples' anchor.

3 / 3

Workflow Clarity

Each workflow lists a numbered sequence, but validation/verification checkpoints are implicit (e.g. no 'check feasibility/convergence before accepting' step), matching the 'steps listed but checkpoints missing or implicit' anchor.

2 / 3

Progressive Disclosure

SKILL.md is a clear overview with well-signaled, one-level-deep references to references/ (5 files) and scripts/ (5 files), all of which exist; content is appropriately split with explicit 'See: ...' navigation.

3 / 3

Total

10

/

12

Passed

Description

72%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.

A specific, well-targeted description with strong trigger terms and low conflict risk, but it lacks an explicit 'Use when...' trigger clause and frames capabilities as feature nouns rather than actions, capping completeness and specificity at 2.

Suggestions

Add an explicit trigger clause, e.g. 'Use when solving multi-objective or constrained optimization problems, finding Pareto fronts, or benchmarking evolutionary algorithms (NSGA-II/III, MOEA/D).'

Reframe capabilities as concrete actions (e.g. 'Solve multi-objective problems, find Pareto-optimal trade-offs, handle constraints') rather than a bare list of feature nouns.

DimensionReasoningScore

Specificity

The description names a concrete domain and many specific capabilities ("NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ)"), but these are feature nouns rather than concrete verb-actions like the anchor-3 example, so it sits at the 'names domain and some actions, not comprehensive as actions' level.

2 / 3

Completeness

It clearly answers 'what' (a multi-objective optimization framework with listed algorithms/benchmarks) but the only 'when' cue is the weak domain phrase "for engineering design and optimization problems"; there is no explicit 'Use when...' trigger clause, which caps completeness at 2 per the guidelines.

2 / 3

Trigger Term Quality

It includes natural terms a user in this domain would actually say — "multi-objective optimization", "NSGA-II", "NSGA-III", "MOEA/D", "Pareto fronts", "ZDT", "DTLZ", "engineering design" — giving good coverage of common variations.

3 / 3

Distinctiveness Conflict Risk

The niche is sharply defined by named algorithms and benchmark families (NSGA-II/III, MOEA/D, Pareto, ZDT/DTLZ), making it clearly distinguishable and unlikely to trigger for the wrong skill.

3 / 3

Total

10

/

12

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (573 lines); consider splitting into references/ and linking

Warning

metadata_version

'metadata.version' is missing

Warning

Total

14

/

16

Passed

Repository
foryourhealth111-pixel/Vibe-Skills
Reviewed

Table of Contents

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