tooluniverse-systems-biology

Comprehensive systems biology and pathway analysis using multiple pathway databases (Reactome, KEGG, WikiPathways, Pathway Commons, BioModels). Performs pathway enrichment, protein-pathway mapping, keyword searches, and systems-level analysis. Use when analyzing gene sets, exploring biological pathways, or investigating systems-level biology.

Quality

78%

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 ./skills/bio/tooluniverse-systems-biology/SKILL.md

Quality

Content

63%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.

A well-structured, highly actionable tool-orchestration skill with clear phased workflows, decision logic, and fallbacks. Its main weaknesses are verbosity from redundant summary/use-pattern sections and a monolithic single-file layout that does not leverage progressive disclosure.

Suggestions

Remove or drastically trim the 'Summary' and 'Common Use Patterns' sections — they restate the phase workflows and decision logic already covered above, saving meaningful tokens.

Move the 'Tool Parameter Reference' and 'Limitations & Known Issues' tables into a separate reference file (e.g. references/tool-reference.md) and link to it from the body, so SKILL.md stays a lean overview.

Inline a brief validation/quality-check reminder at the end of each phase workflow (rather than only in a standalone Quality Checks section) to make per-phase checkpoints explicit.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient and does not explain basic concepts Claude already knows, but the closing 'Summary' section and 'Common Use Patterns' largely restate the phase workflows, adding tokens that do not earn their place.	3 / 5
Actionability	Provides concrete tool names, exact parameter names, example inputs (e.g. id 'P53350', library 'KEGG_2021_Human'), and a critical-parameter reference table — mostly executable guidance with only minor gaps.	4 / 5
Workflow Clarity	Phases 1–4 are clearly sequenced with per-phase decision logic, fallback strategies, and a Quality Checks checklist providing feedback loops, though validation checkpoints live in a separate section rather than inline within each workflow step.	4 / 5
Progressive Disclosure	At ~370 lines with no references/scripts/assets bundle, content that would naturally live in separate files (Tool Parameter Reference, Limitations, detailed phase docs) is fully inlined; structure is good but nothing is split out or referenced.	3 / 5
	Total	14 / 20 Passed

Description

92%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.

A strong, third-person description that names concrete capabilities, the integrated databases, and explicit use-when triggers with minimal conflict risk. The only gap is slightly limited synonym coverage in trigger terms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'pathway enrichment, protein-pathway mapping, keyword searches, and systems-level analysis' — alongside the specific databases used, giving comprehensive coverage of capabilities.	5 / 5
Completeness	Explicitly answers both 'what' (performs enrichment, mapping, keyword searches, systems-level analysis across named databases) and 'when' ('Use when analyzing gene sets, exploring biological pathways, or investigating systems-level biology') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Includes natural trigger phrases users would say ('analyzing gene sets', 'exploring biological pathways', 'investigating systems-level biology'), but coverage stops short of enumerating synonyms or common phrasings a user might alternatively use.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (systems biology / pathway analysis with named curated databases) with distinct triggers, making overlap with unrelated skills minimal.	5 / 5
	Total	19 / 20 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: wu-yc/LabClaw
Path: skills/bio/tooluniverse-systems-biology/SKILL.md
Commit: df37802

Reviewed: 7 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.