gene-structure-mapper

Use gene structure mapper for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.

Quality

38%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./scientific-skills/Data Analysis/gene-structure-mapper/SKILL.md

Quality

Content

48%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 is over-structured with generic process boilerplate that crowds out the thin gene-structure-specific guidance, and the actionable core is undercut by a stub script with no real visualization implementation. Workflow sequencing is the strongest aspect.

Suggestions

Trim the generic boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Response Template) or move them to a shared reference, keeping only gene-structure-specific guidance in SKILL.md.

Replace or augment the stub main.py with a real implementation (e.g. using Biopython or matplotlib) and show the actual drawing code so the example is genuinely executable.

Remove the repetitive "Use gene structure mapper for data analysis workflows that need…" insertions and the "See `## X` above" self-references, which read as templating artifacts.

Dimension	Reasoning	Score
Conciseness	The body is noticeably verbose, dominated by generic process boilerplate (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Output Requirements, Response Template) and the same meta-phrase ("data analysis workflows that need structured execution…") repeated several times.	2 / 5
Actionability	Concrete CLI commands and a Parameters table are provided, but the core task has no real executable implementation shown — the bundled script is a stub that only prints, and no gene-structure drawing code or library usage is documented.	3 / 5
Workflow Clarity	The Workflow section gives a clear 5-step sequence with explicit checkpoints (stop early on unsupported assumptions, fallback on failure); this is a read/write visualization task so the destructive/batch validation cap does not apply.	4 / 5
Progressive Disclosure	The single file is well-sectioned and its only bundle file (scripts/main.py) is referenced correctly at one level, but "See `## Features` above" self-references are awkwardly signaled and large amounts of generic content that belongs elsewhere are inlined.	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 circular and generic: it tells the user to invoke the skill for vague data-analysis process qualities rather than describing the concrete gene-structure visualization it performs. It lacks natural trigger terms and a clear statement of capability.

Suggestions

Rewrite the description to state the concrete capability first, e.g. "Visualize gene structure showing exons, introns, and protein domains, and mark mutation positions."

Add explicit natural trigger phrases such as "Use when the user asks to draw, plot, or visualize a gene's exon-intron structure or annotate domains/mutations."

Remove the generic process language ("structured execution, explicit assumptions, clear output boundaries") from the description; it does not distinguish this skill.

Dimension	Reasoning	Score
Specificity	The description names the domain ("gene structure mapper") but only offers generic process meta-language ("structured execution, explicit assumptions, and clear output boundaries") rather than concrete gene-structure actions like visualizing exons and introns.	2 / 5
Completeness	A vague "when" clause is present ("for data analysis workflows that need…") but the "what" is just the tool name restated, so the description does not explain what the skill actually does.	2 / 5
Trigger Term Quality	"gene structure" is a relevant keyword, but the natural phrases a user would say (exons, introns, visualize/plot a gene) are absent and the rest is generic data-analysis buzzwords rather than user-facing triggers.	2 / 5
Distinctiveness Conflict Risk	The named niche (gene structure mapping) is distinct, but the trigger conditions ("data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries") are generic and could overlap with many other analysis skills.	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/gene-structure-mapper/SKILL.md
Commit: 63c61d3

Reviewed: 8 hours ago

Table of Contents

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