etetoolkit

Phylogenetic tree toolkit (ETE). Tree manipulation (Newick/NHX), evolutionary event detection, orthology/paralogy, NCBI taxonomy, visualization (PDF/SVG), for phylogenomics.

1.37x

Quality

66%

Does it follow best practices?

Impact

85%

1.37x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./scientific-skills/etetoolkit/SKILL.md

Quality

Discovery

82%

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 is a strong, domain-specific description that clearly communicates concrete capabilities with excellent use of natural trigger terms from the bioinformatics domain. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The specificity and distinctiveness are excellent given the narrow scientific domain.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about phylogenetic trees, evolutionary analysis, species trees, gene trees, or needs to parse Newick/NHX files.'

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: tree manipulation with format details (Newick/NHX), evolutionary event detection, orthology/paralogy analysis, NCBI taxonomy integration, and visualization with output formats (PDF/SVG).	3 / 3
Completeness	Clearly answers 'what does this do' with specific capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. Per rubric guidelines, missing 'Use when' caps completeness at 2.	2 / 3
Trigger Term Quality	Includes strong natural keywords users would say: 'phylogenetic tree', 'ETE', 'Newick', 'NHX', 'orthology', 'paralogy', 'NCBI taxonomy', 'phylogenomics', 'PDF/SVG'. These are the exact terms bioinformatics users would use.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive niche in phylogenetics/evolutionary biology. Terms like 'ETE', 'Newick/NHX', 'orthology/paralogy', and 'phylogenomics' are extremely specific and unlikely to conflict with any other skill.	3 / 3
	Total	11 / 12 Passed

Implementation

50%

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

The skill provides highly actionable, executable code examples covering the full breadth of ETE toolkit capabilities, which is its primary strength. However, it is excessively verbose with significant redundancy between sections and use cases, and includes content that should be delegated to the referenced external files. Multi-step workflows lack validation checkpoints, particularly for batch/destructive operations.

Suggestions

Reduce the main SKILL.md to ~150 lines by moving detailed examples for visualization, clustering, tree comparison, and taxonomy into the referenced files (visualization.md, workflows.md, api_reference.md), keeping only quick-start patterns inline.

Remove redundant content: ortholog detection code appears in both Section 2 and Use Case 1; tree format conversion appears in both Section 1 CLI and Use Case 2.

Add explicit validation checkpoints to batch workflows (Use Case 4): verify output file was created, check tree integrity after modifications, add try/except with error logging for failed trees.

Remove explanatory text Claude already knows (e.g., the Overview paragraph, 'PDF (vector) for publications', what iterators are) and trim the best practices list to only non-obvious, ETE-specific guidance.

Dimension	Reasoning	Score
Conciseness	The skill is extremely verbose at ~400+ lines, with significant redundancy. Multiple use cases repeat patterns already shown in earlier sections (e.g., ortholog detection appears in both Section 2 and Use Case 1). Best practices list items like 'Use PDF or SVG for publication figures' that Claude already knows. The overview section explains what ETE is, which is unnecessary.	1 / 3
Actionability	The skill provides fully executable, copy-paste ready Python code and CLI commands throughout. Code examples are complete with imports, concrete file paths, and realistic parameters. Both programmatic and command-line interfaces are covered with specific examples.	3 / 3
Workflow Clarity	Multi-step workflows are present (e.g., Use Case 1 phylogenomic pipeline, Use Case 2 batch processing), but they lack explicit validation checkpoints. For batch operations like Use Case 4 (automated tree analysis processing multiple files), there are no validation steps or error handling/recovery loops, which should cap this at 2.	2 / 3
Progressive Disclosure	References to external files (api_reference.md, workflows.md, visualization.md) are well-signaled, but the main SKILL.md contains far too much inline content that should be in those reference files. The visualization section, clustering analysis, and tree comparison sections could be summarized with pointers to the reference docs instead of being fully detailed inline.	2 / 3
	Total	8 / 12 Passed

Validation

81%

Warnings & errors only

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

Validation — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (622 lines); consider splitting into references/ and linking	Warning
metadata_version	'metadata.version' is missing	Warning

	Total	9 / 11 Passed

Repository: K-Dense-AI/claude-scientific-skills
Commit: b58ad7e

Reviewed: 2 days ago

Table of Contents

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