phylogenetic-tree-styler

Analyze data with `phylogenetic-tree-styler` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.

Quality

39%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Data Analysis/phylogenetic-tree-styler/SKILL.md

Quality

Content

50%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 body contains genuinely useful, executable usage and example content for tree styling, but it is buried under large amounts of generic boilerplate, contradictory/time-sensitive metadata, and vague reference signaling. Structure and token efficiency are the main weaknesses.

Suggestions

Remove the generic boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Response Template, Output Contract, Validation and Safety Rules) that are not specific to phylogenetic tree styling.

Resolve the contradiction between Dependencies (ete3, matplotlib, numpy, pandas) and Prerequisites ("No additional Python packages required"), and drop the time-sensitive "Next Review Date".

Replace generic "references/" mentions with an explicit link to references/runtime_checklist.md, and fix the inverted "See `## Features` above" self-references.

Dimension	Reasoning	Score
Conciseness	The body is padded with many generic boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Output Requirements, Response Template, Output Contract, Validation and Safety Rules) that teach nothing tree-specific, and includes a time-sensitive date ("Next Review Date: 2026-03-06") and a contradictory Prerequisites section, so it is noticeably verbose with several unnecessary sections.	2 / 5
Actionability	It provides concrete executable invocations with real flags (e.g. `python3 scripts/main.py -i tree.nwk -o tree_bootstrap.png --show-bootstrap --bootstrap-threshold 70`), a full parameter table, taxonomy CSV format, and a Newick example, with only minor gaps such as the off-topic medical sample string in an example invocation.	4 / 5
Workflow Clarity	A 5-step Workflow and a py_compile Quick Check are present, but the steps are generic process boilerplate with only a parse-check validation and no output validation checkpoint or validate-fix-retry feedback loop for the actual styling task.	3 / 5
Progressive Disclosure	Bundle files exist (references/runtime_checklist.md, scripts/main.py) but the body only gestures at "references/" generically and never links the specific file, while nearly all content is inlined in one 275-line SKILL.md alongside confusing self-references like "See `## Features` above".	3 / 5
	Total	12 / 20 Passed

Description

28%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.

The description is generic and boilerplate-heavy: it says "Analyze data" with process language rather than naming the skill's actual tree-styling capabilities, and it omits any "Use when" trigger guidance. It is distinguishable mainly because the tool name encodes the niche.

Suggestions

Rewrite to name concrete actions, e.g. "Beautify phylogenetic trees with taxonomy color blocks, bootstrap values, and timelines from Newick files."

Add an explicit trigger clause such as "Use when styling or annotating phylogenetic trees, adding bootstrap values, or rendering taxonomy color blocks."

Drop the generic process filler ("reproducible workflow, explicit validation, structured outputs for review-ready interpretation") which adds no specificity.

Dimension	Reasoning	Score
Specificity	The description only offers the generic action "Analyze data" plus process filler ("reproducible workflow, explicit validation, structured outputs") and names no concrete domain actions like beautifying trees, adding taxonomy blocks, or bootstrap values; it names the tool but not the substantive capabilities.	2 / 5
Completeness	It states a vague "what" ("Analyze data ...") and has no "Use when ..." trigger clause at all, matching the anchor for a vague what with no when rather than the cap-3 case which requires a clear what.	2 / 5
Trigger Term Quality	The only natural keyword is embedded in the tool name "phylogenetic-tree-styler"; the surrounding language ("Analyze data", "review-ready interpretation") is generic and misses the phrases users would actually say such as phylogenetic tree, Newick, bootstrap, or taxonomy.	2 / 5
Distinctiveness Conflict Risk	The niche tool name "phylogenetic-tree-styler" distinguishes it, but the descriptive language ("reproducible workflow, explicit validation, structured outputs") is generic boilerplate that could describe many data-analysis skills, leaving moderate overlap risk.	3 / 5
	Total	9 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Data Analysis/phylogenetic-tree-styler/SKILL.md
Commit: 63c61d3

Reviewed: 9 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.