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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.

68

Quality

83%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

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 library skill: executable quick-start and workflow code, per-module pointers to real one-level-deep reference files, and implicit validation guidance in the best practices. The main cost is redundancy — the 'When to Use', 'Additional Capabilities', and 'Reference Files' sections repeat information already present in the frontmatter or the inline 'See:' links and could be trimmed for token efficiency.

Suggestions

Trim conciseness: delete the trailing 'Reference Files' section (it duplicates the per-module 'See: references/...' pointers) and collapse the 'Additional Capabilities' stub sections into a single pointer to references/wcs_and_other_modules.md.

Reduce the 'When to Use This Skill' bullet list or the frontmatter description — they currently say nearly the same thing twice; keep one authoritative trigger list.

Tighten code examples: remove the unused `match_coordinates_sky` import in the cross-matching workflow and drop the trailing empty line so every token earns its place.

DimensionReasoningScore

Conciseness

The body is mostly efficient code and concrete lists, but contains several redundant sections: the 'When to Use This Skill' bullet list restates the frontmatter description, the closing 'Reference Files' section duplicates the per-module 'See:' pointers already given inline, and the 'Additional Capabilities' stubs add little beyond what a single pointer to wcs_and_other_modules.md would convey. This sits between 'noticeably verbose' (2) and 'efficient with minor trim' (4) — the padding is real but does not explain concepts Claude already knows.

3 / 5

Actionability

Fully executable, copy-paste-ready code throughout: a Quick Start touching every major submodule, an install command, and four complete Common Workflows (coordinate conversion, FITS analysis, cosmological distances, catalog cross-matching) covering the most common use cases. Only trivially below perfect (e.g., an unused `match_coordinates_sky` import in the cross-match example), which keeps it at the level-5 anchor rather than 4.

5 / 5

Workflow Clarity

The Common Workflows give clear, runnable sequences for each task, and the Best Practices list embeds implicit checkpoints ('Check coordinate frames', 'Check WCS validity', 'Verify the frame before transformations'). There are no explicit validation/verify steps in the workflows, but the operations are read/analyze rather than destructive or batch, so the level-3 cap does not apply; this is 'clear sequence with most checkpoints present, minor validation gaps' rather than the feedback-loop-rich level 5.

4 / 5

Progressive Disclosure

The SKILL.md body is a clean overview: each of the seven capability sections ends with a clearly signaled 'See: references/<file>.md' pointer, and all seven referenced files (units.md, coordinates.md, cosmology.md, fits.md, tables.md, time.md, wcs_and_other_modules.md) exist in the bundle exactly one level deep. This matches the level-5 anchor of a clear overview with well-signaled, one-level-deep references; the only blemish is the redundant duplicate reference listing at the end.

5 / 5

Total

17

/

20

Passed

Description

87%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 description: it names a distinct domain, enumerates concrete capabilities, and provides an explicit, detailed 'use when' trigger clause. Its only weaknesses are light generic padding ("Comprehensive...", "astronomical data analysis") and a few missing natural synonyms/file extensions.

DimensionReasoningScore

Specificity

The description lists several concrete actions ("coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions") with minor gaps in coverage, though phrases like "astronomical data analysis" and "Comprehensive Python library" are generic filler. It lists multiple specific actions but stops short of the fully comprehensive coverage of the level-5 anchor, and is clearly above the 1-2 concrete actions of level 3.

4 / 5

Completeness

It explicitly answers both questions: what ("Comprehensive Python library for astronomy and astrophysics" with an enumerated capability list) and when ("This skill should be used when working with astronomical data including... Use when tasks involve coordinate transformations..."). The 'when' clause is explicit with concrete trigger phrases, matching the level-5 anchor rather than the weaker 'when' of level 4.

5 / 5

Trigger Term Quality

Good natural keyword coverage: "FITS files", "celestial coordinates", "physical units", "cosmological calculations", "tables", "WCS", "time systems" — terms a user working with astronomy data would naturally say. A few common variations and synonyms are missing (e.g., ".fits" extension, redshift, catalogs, magnitudes), so it falls just short of the comprehensive synonym-plus-extension coverage of level 5 while exceeding the 'some relevant keywords' of level 3.

4 / 5

Distinctiveness Conflict Risk

Clear niche (astronomy/astrophysics) with distinct triggers — FITS files, WCS, celestial coordinates, cosmological distances — that virtually no other skill would claim. This is a well-carved domain with minimal overlap risk, matching the level-5 anchor.

5 / 5

Total

18

/

20

Passed

Validation

87%

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

CriteriaDescriptionResult

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
synthetic-sciences/openscience
Reviewed

Table of Contents

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