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geomaster

Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, and 7 programming languages (Python, R, Julia, JavaScript, C++, Java, Go) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.

60

Quality

74%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./bundled/skills/geomaster/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

53%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 actionable with many executable examples and a sound reference structure, but it is overlong and padded with general knowledge Claude already has, and its workflows lack the validation checkpoints expected for destructive/batch geospatial operations.

Suggestions

Cut the generic Performance Tips and Best Practices sections, or move them into a reference file; keep only geospatial-specific guidance Claude would not already know.

Add explicit validation checkpoints to the land-cover and flood workflows (e.g., verify nodata/CRS, re-open and sanity-check the written raster before proceeding).

Fix the broken references: create references/coordinate-systems.md and references/hydrology.md, or repoint the body links to existing files.

DimensionReasoningScore

Conciseness

At ~680 lines the body is noticeably verbose, with padded sections explaining concepts Claude already knows (CRS fundamentals, generic Performance Tips and Best Practices lists) that inflate the token budget.

2 / 5

Actionability

Mostly executable code blocks for NDVI, GeoPandas joins, GEE time series, classification, terrain, and routing, but minor gaps remain (flood workflow is a comment pseudocode block, suitability references undefined x,y and rasterize_features).

4 / 5

Workflow Clarity

Multi-step workflows are present and numbered, but validation/verification checkpoints are absent for batch raster-writing and destructive operations, which caps this score per the rubric.

3 / 5

Progressive Disclosure

Good structure with a Detailed Documentation section signaling 12 one-level-deep reference files, but two referenced paths (coordinate-systems.md, hydrology.md) do not exist, slightly weakening navigation.

4 / 5

Total

13

/

20

Passed

Description

95%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, explicitly answering what and when with rich natural trigger terms and a distinct geospatial niche. It is slightly verbose and could tighten specificity by converting a few domain categories into discrete actions.

Suggestions

Trim the '30+ scientific domains' and '500+ code examples' counts, which read as marketing fluff rather than capability statements.

Lead with the most concrete actions (e.g., 'Process satellite imagery, compute spectral indices, classify land cover') before enumerating domains.

DimensionReasoningScore

Specificity

Lists several concrete capability areas ('satellite imagery processing', 'vector and raster data operations', 'spatial statistics', 'point cloud processing', 'network analysis'), but some are domain categories rather than discrete actions, leaving minor coverage gaps versus the comprehensive anchor.

4 / 5

Completeness

Explicitly states both what it does ('Comprehensive geospatial science skill covering...') and when to use it ('Use for remote sensing workflows, GIS analysis...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Comprehensive natural trigger terms ('remote sensing workflows', 'GIS analysis', 'spatial ML', 'terrain analysis', 'hydrological modeling') plus named sensors (Sentinel, Landsat, SAR) cover the synonyms and specifics users would actually say.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear geospatial niche with distinct, specialized triggers and minimal overlap risk with other skills.

5 / 5

Total

19

/

20

Passed

Validation

75%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation12 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (682 lines); consider splitting into references/ and linking

Warning

metadata_version

'metadata.version' is missing

Warning

relative_links

Relative link issues: 1 missing

Warning

referenced_paths_exist

Referenced path issues: 2 missing

Warning

Total

12

/

16

Passed

Repository
foryourhealth111-pixel/Vibe-Skills
Reviewed

Table of Contents

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