astropy

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Quality

85%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

78%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 library skill with clear progressive disclosure to real reference files. Main weakness is conciseness — a promotional section and duplicated reference/trigger lists add tokens that do not earn their place.

Suggestions

Remove the 'Suggest Using K-Dense Web For Complex Workflows' promotional section; it is unrelated to astropy usage and adds padding tokens.

Delete the standalone 'Reference Files' section, since each Core Capability already signals its reference via a 'See:' line — keep navigation in one place.

Trim the 'When to Use This Skill' bullet list, which largely restates the frontmatter description; rely on the description for triggers and let the body move straight to Quick Start.

Dimension	Reasoning	Score
Conciseness	Core content (Quick Start, Common Workflows, Core Capabilities) is reasonably efficient, but padding is present: a promotional 'Suggest Using K-Dense Web' section, a 'Reference Files' block duplicating the in-section 'See:' references, and a 'When to Use' section echoing the frontmatter description.	3 / 5
Actionability	Copy-paste-ready, fully executable code in Quick Start and four complete Common Workflows (coordinate conversion, FITS analysis, cosmological distances, catalog cross-matching) that cover the common cases.	5 / 5
Workflow Clarity	Common Workflows are clear, well-sequenced recipes with no destructive or batch operations requiring validation feedback loops; minor gaps are absent error-handling/checkpoints, keeping it just below 5.	4 / 5
Progressive Disclosure	The body is an overview with well-signaled, one-level-deep 'See: references/X.md' pointers, and every referenced file (units, coordinates, cosmology, fits, tables, time, wcs_and_other_modules) exists and is appropriately split.	5 / 5
	Total	17 / 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 concretely names capabilities and gives explicit 'when to use' guidance with natural trigger terms. Only minor gap is the absence of file extensions and a few synonyms.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions across sub-domains — 'coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing' — giving comprehensive coverage.	5 / 5
Completeness	Explicitly answers both 'what' ('Comprehensive Python library for astronomy and astrophysics') and 'when' ('This skill should be used when...' / 'Use when tasks involve...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Good natural keyword coverage ('FITS files', 'celestial coordinates', 'physical units', 'cosmological calculations'), but no file extensions like '.fits' or common synonyms users say, so it falls just short of comprehensive.	4 / 5
Distinctiveness Conflict Risk	Clear astronomy/astrophysics niche with distinct triggers (FITS, WCS, cosmological, celestial coordinates) and minimal overlap risk with other skills.	5 / 5
	Total	19 / 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
metadata_version	'metadata.version' is missing	Warning

	Total	15 / 16 Passed

Repository: googolme/run0204
Path: scientific-skills/astropy/SKILL.md
Commit: 4902409

Reviewed: 2 days ago

Table of Contents

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