geopandas

Guidance and local audit tools for Python workflows that directly use GeoPandas GeoSeries, GeoDataFrame, spatial operations, or vector-data I/O.

Quality

91%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

100%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An exceptionally lean, actionable, and well-structured skill body: executable pins and commands, a gated validation workflow for risky operations, and clean one-level-deep reference navigation. The only minor note is the length of the pinned-environment block, but it is justified for reproducibility.

Dimension	Reasoning	Score
Conciseness	The body is dense and assumes Claude's expertise — no 'what is GeoPandas' padding — and time-sensitive version pins sit alongside a dedicated deprecated-patterns migration checklist, so every token earns its place.	3 / 3
Actionability	Provides executable `uv pip install` pins, runnable Python snippets, and exact CLI invocations with real flags (e.g. `--predicate within --left-id point_id`), all copy-paste ready.	3 / 3
Workflow Clarity	Eight numbered correctness gates sequence the work with explicit validation checkpoints ('validate before and after repair/overlay', 'reopen the artifact, and compare counts/types'), plus feedback loops for destructive PostGIS operations.	3 / 3
Progressive Disclosure	SKILL.md is a concise overview that signals one-level-deep references to six verified reference files, a CLI table, and a reference index, with content appropriately split and easy to navigate.	3 / 3
	Total	12 / 12 Passed

Description

82%

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 specific, distinctive description with strong natural trigger terms, written in correct third-person voice. Its only gap is the missing explicit 'when to use' guidance, which limits completeness.

Suggestions

Append an explicit trigger clause such as 'Use when working with GeoPandas GeoSeries/GeoDataFrame, performing spatial joins or overlays, reprojecting vector data, or auditing vector I/O.'

Add common user phrasings like 'GeoDataFrame', 'spatial join', 'reproject', or 'geoparquet' to broaden natural-keyword coverage.

Dimension	Reasoning	Score
Specificity	Names multiple concrete capabilities — 'GeoPandas GeoSeries, GeoDataFrame, spatial operations, or vector-data I/O' plus 'local audit tools' — rather than vague abstractions.	3 / 3
Completeness	It clearly answers 'what does this do' (guidance and local audit tools for GeoPandas workflows) but lacks any 'Use when...' clause or equivalent explicit trigger guidance, capping it at 2.	2 / 3
Trigger Term Quality	Natural user-facing terms like 'GeoPandas', 'GeoSeries', 'GeoDataFrame', 'spatial operations', and 'vector-data I/O' match what a user would actually say when they need this skill.	3 / 3
Distinctiveness Conflict Risk	The niche is tightly scoped to GeoPandas vector workflows, with triggers unlikely to collide with non-geospatial skills.	3 / 3
	Total	11 / 12 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
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning

	Total	15 / 16 Passed

Repository: K-Dense-AI/scientific-agent-skills
Path: skills/geopandas/SKILL.md
Commit: 757b63b

Reviewed: about 12 hours ago

Table of Contents

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