astropy

Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

Quality

68%

Does it follow best practices?

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tessl review fix ./skills/astropy/SKILL.md

Quality

Content

61%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 content is highly actionable with excellent executable code examples, but it is somewhat padded with restated concepts, lacks sequenced workflows with validation checkpoints, and its progressive-disclosure references are empty placeholders that do not deliver the promised detail.

Suggestions

Replace the placeholder reference files with the promised substantive content (unit systems, equivalencies, coordinate-frame details, FITS header manipulation, etc.) or remove the references and inline only what is needed.

Add explicit validation/verification steps to the FITS and cross-matching workflows (e.g. verify HDU structure, check match counts against a threshold) to introduce real feedback loops.

Trim restated explanations of concepts Claude already knows (e.g. the FITS acronym expansion and per-module purpose restatements) and consolidate the duplicate 'Reference Files' listing with the inline 'See:' pointers.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient with code examples and bulleted capability lists, but it re-states concepts Claude already knows (e.g. 'FITS (Flexible Image Transport System) files', restating each module's purpose that the import paths already convey) and the long 'Core Capabilities' bullet lists plus repeated 'Reference Files' section add padding that could be tightened.	3 / 5
Actionability	It provides copy-paste-ready executable code throughout — a Quick Start block and four complete Common Workflows (coordinate transforms, FITS analysis, cosmological distances, catalog cross-matching) with correct imports and real method calls covering the common cases.	5 / 5
Workflow Clarity	The 'Common Workflows' are code recipes rather than sequenced processes, and the 'Best Practices' list is unordered tips with no validation checkpoints or validate-fix-retry feedback loops; per the rubric's destructive/batch cap (e.g. FITS file manipulation, batch catalog matching have no verification steps), workflow clarity cannot exceed 3.	3 / 5
Progressive Disclosure	References are clearly signaled one level deep in the body, but every reference file is only a placeholder that restates the promise and redirects to upstream docs rather than containing the promised detailed material (e.g. 'comprehensive documentation, unit systems, equivalencies' is never actually present), so the disclosure structure is largely hollow and content that should exist is missing.	2 / 5
	Total	13 / 20 Passed

Description

75%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 specific and distinctive, clearly conveying astropy's domain and scope, but it lacks an explicit 'Use when...' trigger clause, which caps completeness at 3 and leaves a few natural trigger synonyms missing.

Suggestions

Append an explicit trigger clause, e.g. 'Use when tasks involve celestial coordinates, FITS files, astronomical unit calculations, cosmology, or precise time handling.'

Add natural synonyms and file extensions users would say ('FITS', '.fits', 'celestial coordinates', 'spectroscopy') to broaden trigger coverage.

Dimension	Reasoning	Score
Specificity	The phrase 'core Python package for astronomy, providing essential functionality for astronomical research and data analysis' names the domain and the broad functional scope, and the body enumerates many concrete capabilities (coordinate transformations, unit calculations, FITS operations, cosmological calculations, time handling, table manipulation, image processing); the description itself states the essential-functionality claim comprehensively for its length.	5 / 5
Completeness	It clearly answers 'what' (core astronomy package providing essential functionality for research and data analysis) but contains no explicit 'when to use' / 'Use when...' trigger clause in the description field, so per the rubric guideline a missing explicit trigger clause caps completeness at 3.	3 / 5
Trigger Term Quality	It includes natural terms a user would say ('astronomy', 'astronomical research', 'data analysis', 'coordinate transformations', 'FITS files'), but the description omits common synonyms and file extensions (e.g. 'FITS', '.fits', 'celestial coordinates', 'photometry') that a user might naturally mention, leaving a few natural terms missing.	4 / 5
Distinctiveness Conflict Risk	The astronomy/astrophysics niche is highly specific with distinct triggers (FITS, celestial coordinates, cosmology, time scales) and minimal realistic overlap with other skills, so it is unlikely to trigger for the wrong skill.	5 / 5
	Total	17 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: sickn33/antigravity-awesome-skills
Path: skills/astropy/SKILL.md
Commit: 1f67c44

Reviewed: about 17 hours ago

Table of Contents

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