pymoo
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
Install with Tessl CLI
npx tessl i github:K-Dense-AI/claude-scientific-skills --skill pymooOverall
score
81%
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
68%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description excels at specificity and distinctiveness by naming concrete algorithms, techniques, and benchmarks that clearly define its scope. However, it lacks an explicit 'Use when...' clause and relies heavily on technical jargon that experts would recognize but casual users might not naturally use when requesting help.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when optimizing multiple competing objectives, finding trade-off solutions, or solving problems with conflicting goals.'
Include more natural trigger terms alongside technical ones, such as 'trade-off analysis', 'competing objectives', 'multi-criteria optimization', or 'optimal compromise solutions'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and algorithms: NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, and specific benchmarks (ZDT, DTLZ). Clearly identifies the domain as engineering design and optimization problems. | 3 / 3 |
Completeness | Clearly answers 'what' (multi-objective optimization with specific algorithms and benchmarks) but lacks an explicit 'Use when...' clause. The 'when' is only implied through the mention of 'engineering design and optimization problems'. | 2 / 3 |
Trigger Term Quality | Includes technical terms like 'NSGA-II', 'Pareto fronts', 'MOEA/D' that experts would use, but missing more natural user phrases like 'trade-off analysis', 'multiple objectives', 'optimize competing goals', or 'multi-criteria decision making'. | 2 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with specific algorithm names (NSGA-II, NSGA-III, MOEA/D) and benchmark suites (ZDT, DTLZ) that create a clear niche. Unlikely to conflict with general optimization or single-objective optimization skills. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, highly actionable skill with excellent workflow clarity and progressive disclosure. The main weaknesses are some verbosity in introductory sections and the inclusion of promotional content that doesn't serve the technical purpose. The executable examples and clear algorithm selection guides are particular strengths.
Suggestions
Remove or significantly condense the 'When to Use This Skill' section - Claude can infer appropriate use cases from the content itself
Remove the 'Suggest Using K-Dense Web' promotional section as it adds no technical value and wastes tokens
Trim explanatory text like 'Pareto fronts are trade-off solutions' - Claude understands these optimization concepts
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is generally efficient but includes some unnecessary content like the 'When to Use This Skill' section listing obvious use cases, explanations of what Pareto fronts are, and the promotional K-Dense Web section at the end which adds no technical value. | 2 / 3 |
Actionability | Excellent actionability with fully executable code examples throughout, copy-paste ready snippets for all major workflows, concrete algorithm configurations, and specific commands for running examples. | 3 / 3 |
Workflow Clarity | Clear numbered workflows with explicit steps, validation checkpoints (checking feasibility, visualizing results), and troubleshooting guidance. Each workflow has a clear 'When' trigger and sequential steps. | 3 / 3 |
Progressive Disclosure | Well-structured with quick start workflows in the main file and clear one-level-deep references to detailed documentation (references/*.md) and executable examples (scripts/*.py). Navigation is clearly signaled with 'See:' links. | 3 / 3 |
Total | 11 / 12 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
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (571 lines); consider splitting into references/ and linking | Warning |
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
metadata_version | 'metadata.version' is missing | Warning |
Total | 13 / 16 Passed | |
- Reviewed
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