astropy

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

Quality

55%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/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 body is a well-organized, code-rich capability reference with good progressive-disclosure structure pointing to per-module reference files. Its main weaknesses are mild redundancy, descriptive (non-code) Core Capability sections, and an absence of validation checkpoints in the worked recipes.

Suggestions

Add a verification step to the cross-matching and FITS-writing workflows (e.g., print match counts and assert separation thresholds, or verify a written FITS file reopens with the expected header) to provide explicit validation checkpoints.

Collapse the duplicated reference signaling — keep either the inline 'See:' links or the bottom 'Reference Files' index, not both — and ensure the references/*.md files are actually shipped in the bundle.

Replace or trim the conceptual 'Key operations' bullet lists in Core Capability sections with a short representative code snippet or a direct pointer to the reference file, reducing overlap with Quick Start and Common Workflows.

Dimension	Reasoning	Score
Conciseness	Largely code-driven and lean with no over-explanation of astronomy concepts, but the 'Key operations' bullets in each Core Capability section describe library capabilities conceptually, Quick Start and Common Workflows overlap, and the reference list is duplicated (in-text 'See:' plus a bottom 'Reference Files' section), matching 'mostly efficient but some unnecessary explanation or could be tightened'.	3 / 5
Actionability	Substantial copy-paste-ready astropy code in Quick Start and four Common Workflows covering coordinate conversion, FITS reading, cosmology, and catalog cross-matching, but the Core Capability sections rely on descriptive bullets without code, leaving minor gaps.	4 / 5
Workflow Clarity	The Common Workflows are clear step sequences, but no validation or verification checkpoints appear anywhere, and the catalog cross-matching recipe is a batch operation with no verify step, matching 'steps listed but validation gaps; checkpoints missing or implicit'.	3 / 5
Progressive Disclosure	A clear overview with well-signaled one-level-deep references and a navigation index is textbook good structure, but the referenced references/*.md files do not actually exist in the bundle and the reference signaling is duplicated, matching 'good structure; references mostly clear; minor organization gaps'.	4 / 5
	Total	14 / 20 Passed

Description

48%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 correctly identifies the niche in third person but is too generic: it states what Astropy is without listing concrete capabilities or any 'Use when…' trigger guidance. Adding specific actions and explicit trigger phrases would lift specificity, completeness, and trigger-term quality together.

Suggestions

List 3-5 concrete actions (e.g., 'convert celestial coordinates, read/write FITS files, perform cosmological distance calculations') instead of 'providing essential functionality'.

Add an explicit 'Use when…' clause naming natural triggers users say: 'Use when working with FITS files, celestial coordinates, WCS, cosmological calculations, or astronomical units and times.'

Include the domain-specific file extension (.fits) and common synonyms (coordinates, cosmology, units) to improve trigger-term coverage.

Dimension	Reasoning	Score
Specificity	Names the domain ('astronomy', 'core Python package') but the only action language is generic — 'providing essential functionality for astronomical research and data analysis' — with no concrete actions listed, matching the anchor 'Names the domain but actions are minimal or generic'.	2 / 5
Completeness	Provides a clear 'what' (core astronomy package) but no 'when' or 'Use when…' trigger guidance; per the guideline a missing 'Use when…' clause caps completeness at 3.	3 / 5
Trigger Term Quality	Includes natural terms a user would say ('astronomy', 'astronomical research') but misses the common variations and synonyms users actually invoke (FITS, coordinates, WCS, cosmology, units), matching 'some relevant keywords but missing common variations'.	3 / 5
Distinctiveness Conflict Risk	Astronomy is a clear niche unlikely to trigger unrelated skills, with only minor overlap risk against generic data-analysis skills; not 5 because no distinct trigger phrases are stated.	4 / 5
	Total	12 / 20 Passed

Validation

81%

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 — 13 / 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
referenced_paths_exist	Referenced path issues: 15 missing	Warning

	Total	13 / 16 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: plugins/AI-Agents-Safe-Coding-Skills-claude/skills/astropy/SKILL.md
Commit: debb2ec

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.