geopandas

A Python library for reading, writing, and analyzing geospatial vector data; use it when you need spatial operations (buffer/overlay/join), CRS reprojection, or map visualization on formats like Shapefile/GeoJSON/GeoPackage or PostGIS.

Quality

76%

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Securityby

Passed

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tessl review fix ./scientific-skills/Data Analysis/geopandas/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 an excellent executable example and accurate API details, and references are well-structured. Its main weakness is a large block of generic boilerplate sections that inflate token cost without adding GeoPandas-specific value, and the real workflow lacks validation checkpoints.

Suggestions

Remove or trim the generic template sections (Required Inputs, Recommended Workflow, Deterministic Output Rules, Output Contract, Validation and Safety Rules, Failure Handling, Completion Checklist, Quick Validation, Scope Reminder) that do not add GeoPandas-specific guidance.

Add a concrete validation checkpoint to the Example Usage workflow, e.g. assert gdf.crs is not None before to_crs and verify output geometry types after to_file, since reprojection and batch I/O are error-prone.

Convert the flat parenthetical reference list into per-topic 'See references/X.md' pointers under each relevant section so navigation is explicit and the overview stays lean.

Dimension	Reasoning	Score
Conciseness	The GeoPandas-specific sections are efficient, but roughly half the body (Required Inputs, Recommended Workflow, Deterministic Output Rules, Output Contract, Validation and Safety Rules, Failure Handling, Completion Checklist, Quick Validation, Scope Reminder) is generic boilerplate padding that adds no GeoPandas knowledge Claude lacks.	2 / 5
Actionability	Provides a fully executable, copy-paste-ready 6-step example plus concrete API specifics (set_crs vs to_crs semantics, sjoin predicates, overlay how= values, use_arrow=True, bbox= filters), matching the score-5 anchor.	5 / 5
Workflow Clarity	The example is a clear numbered sequence but lacks validation checkpoints, and the generic Recommended Workflow's 'final validation pass' is boilerplate rather than tied to reprojection/batch-I/O where wrong-CRS metric errors are a real risk.	3 / 5
Progressive Disclosure	SKILL.md is an overview with one-level-deep references, all clearly listed and verified as real files mapped to capability areas; held at 4 because the references are a flat parenthetical rather than per-topic 'See X.md' pointers and some detail remains inlined.	4 / 5
	Total	14 / 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.

The description is strong: it states concrete capabilities, includes natural trigger terms and formats, and explicitly couples the 'what' with a 'use it when' trigger. Minor gap is the absence of explicit file extensions among the trigger terms.

Dimension	Reasoning	Score
Specificity	Names multiple concrete actions ('reading, writing, and analyzing geospatial vector data', 'spatial operations (buffer/overlay/join)', 'CRS reprojection', 'map visualization') with comprehensive coverage, matching the score-5 anchor.	5 / 5
Completeness	Explicitly answers both 'what' (reading/writing/analyzing geospatial vector data) and 'when' via a concrete 'use it when...' clause listing specific triggers, matching the score-5 anchor.	5 / 5
Trigger Term Quality	Strong natural keyword coverage ('spatial operations', 'buffer/overlay/join', 'CRS reprojection', 'map visualization', Shapefile/GeoJSON/GeoPackage, PostGIS) but a few natural terms/extensions (e.g. .shp, .geojson) are absent, sitting clearly above a 3.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (geospatial vector data with named operations and formats) with distinct triggers 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
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Data Analysis/geopandas/SKILL.md
Commit: f5ef65b

Reviewed: ~3 hours ago

Table of Contents

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