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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.

74

Quality

93%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

86%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 body is well-structured and action-oriented, with executable examples and clean progressive disclosure to verified reference files. The main weakness is mild redundancy between the capability listings and the description, which slightly inflates token use.

Suggestions

Trim the "When to Use" bullet list and "Core Capabilities" Key operations to avoid restating capabilities already named in the frontmatter description and Overview.

Add a concrete WCS workflow example to match the depth of the other Common Workflows sections.

Consider consolidating the per-module "Key operations" bullets, which overlap heavily with the corresponding reference files' coverage.

DimensionReasoningScore

Conciseness

Mostly efficient with executable examples and tight bullet lists, but capability descriptions in "When to Use", "Core Capabilities", and "Best Practices" repeat content already in the description/overview, leaving minor trim opportunities.

4 / 5

Actionability

Multiple complete, copy-paste-ready code blocks (Quick Start plus four Common Workflows) with real imports cover the common cases; only the WCS workflow lacks a full example.

5 / 5

Workflow Clarity

Common Workflows give clear, sequenced examples and Best Practices include validation-style checks ("Check coordinate frames", "Check WCS validity"), though explicit validate-then-retry checkpoints are implicit rather than formal.

4 / 5

Progressive Disclosure

SKILL.md is a concise overview with seven well-signaled, one-level-deep references to real files (units.md, coordinates.md, cosmology.md, fits.md, tables.md, time.md, wcs_and_other_modules.md), each linked inline and recapped in a Reference Files section.

5 / 5

Total

18

/

20

Passed

Description

100%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 exemplary: it states the skill's purpose, enumerates concrete capabilities, and provides explicit trigger guidance with natural user-facing terms. It is distinct within a narrow niche with no measurable conflict risk.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ("coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions") with comprehensive domain coverage.

5 / 5

Completeness

Explicitly answers both what ("Comprehensive Python library for astronomy and astrophysics") and when ("This skill should be used when working with..." / "Use when tasks involve...") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Comprehensive natural terms including synonyms and file extension: "celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), astronomical data analysis."

5 / 5

Distinctiveness Conflict Risk

Occupies a clear astronomy/astrophysics niche with distinct, domain-specific triggers, giving minimal conflict risk with other skills.

5 / 5

Total

20

/

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.

Validation14 / 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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