scientist-low

Basic data analysis - fast exploratory analysis (Haiku-tier)

Quality

47%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./skills/scientist-low/SKILL.md

Quality

Content

72%

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

This skill provides good actionable code examples for basic data analysis tasks with clear structure. However, it includes some unnecessary framing content and lacks validation/error handling guidance that would help Claude handle common data loading failures gracefully.

Suggestions

Remove the 'Use Cases' section and closing tagline - they add no actionable value and waste tokens

Add basic error handling patterns for common failures (file not found, encoding issues, malformed data)

Dimension	Reasoning	Score
Conciseness	Mostly efficient but includes some unnecessary framing ('You are Scientist-Low', the tagline at the end) and the 'Use Cases' section lists things Claude already knows how to do without adding actionable guidance.	2 / 3
Actionability	Provides fully executable, copy-paste ready Python code examples for data loading, statistics, and visualization with specific library usage and file paths.	3 / 3
Workflow Clarity	Shows a logical sequence (load → inspect → analyze → visualize) but lacks validation checkpoints or error handling guidance for data operations that could fail (e.g., file not found, malformed CSV).	2 / 3
Progressive Disclosure	For a simple, single-purpose skill under 50 lines, the content is well-organized with clear sections (Use Cases, REPL, Output Format, Visualization) and doesn't require external references.	3 / 3
	Total	10 / 12 Passed

Description

22%

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 is too vague and lacks the specificity needed for effective skill selection. It fails to list concrete actions, omits explicit trigger guidance, and relies on internal terminology ('Haiku-tier') that users wouldn't naturally use. The description would benefit significantly from concrete capability examples and a clear 'Use when...' clause.

Suggestions

Add specific concrete actions like 'Summarize datasets, compute basic statistics, create quick visualizations, identify patterns in tabular data'

Include a 'Use when...' clause with natural trigger terms: 'Use when the user needs quick data summaries, basic CSV analysis, simple statistics, or initial data exploration'

Replace 'Haiku-tier' jargon with user-facing language like 'lightweight' or 'quick' and add file type triggers like 'CSV', 'spreadsheet', '.xlsx'

Dimension	Reasoning	Score
Specificity	The description uses vague language like 'basic data analysis' and 'fast exploratory analysis' without listing any concrete actions. No specific capabilities like 'create charts', 'compute statistics', or 'clean data' are mentioned.	1 / 3
Completeness	The description weakly addresses 'what' (basic data analysis) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill.	1 / 3
Trigger Term Quality	Contains some relevant keywords ('data analysis', 'exploratory analysis') that users might say, but missing common variations like 'CSV', 'spreadsheet', 'statistics', 'visualize', or 'summarize data'. The term 'Haiku-tier' is internal jargon users wouldn't use.	2 / 3
Distinctiveness Conflict Risk	The 'Haiku-tier' qualifier and 'fast exploratory' framing provide some distinction from potentially more advanced analysis skills, but 'data analysis' is still broad enough to overlap with many other analytical skills.	2 / 3
	Total	6 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

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

	Total	10 / 11 Passed

Repository: TurnaboutHero/oh-my-antigravity
Commit: fab464f

Reviewed: 4 months ago

Table of Contents

Discovery Implementation Validation

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