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gisgp

by io.github.uponex

grade_service

Grade an ArcGIS FeatureServer layer A–F across 5 categories (schema quality, data completeness, performance, maintenance, configuration).

Returns JSON: {grade, score, categories:[{key, label, score, note}], archetype,
insight, percentile, share_url} — share_url is a public scorecard page you can
send to a human. token: only for private layers (never stored in the scorecard).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenNo
service_urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden. It discloses output structure and token privacy, but does not explicitly state whether the tool is read-only, its impact on the service, rate limits, or authentication requirements beyond the token hint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. The main action is front-loaded, and output fields are listed clearly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a grading tool with detailed output, the description covers the output schema fields and token behavior. It does not explain the 5 categories or grading criteria, but the output schema likely handles that. Good overall.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description adds essential meaning: token is 'only for private layers (never stored in the scorecard)' and service_url is implied by context. It compensates well for two parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Grade' and the resource 'ArcGIS FeatureServer layer' with specific grading scale (A–F) and 5 categories, distinguishing it from siblings like audit_service which has a different focus.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides context for when to use the token parameter ('only for private layers') and notes that share_url can be sent to a human. However, it does not explicitly compare to similar tools like audit_service or explain when grading is preferred over auditing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation2/5

Many assess_* composite tools (datacenter, ev_charging, renewable, telecom, due_diligence) share the same building blocks of grid proximity, land cover, and terrain, making their boundaries fuzzy. assess_property_hazard_x402 also duplicates assess_property_hazard with only a payment-method difference, and bundle_* tools intentionally overlap with the free primitives they replace.

Naming Consistency3/5

There is a mix of verb_noun tools (query_features, geocode_address), noun-first geometry tools (centroids_geojson, envelope_geojson), and inconsistent _geojson suffix usage (buffer_geojson, fix_geometry, geometry_stats). The assess_* and bundle_* prefixes offer some grouping, but no single naming pattern is followed across the set.

Tool Count1/5

With 85 tools, the surface is extreme for an MCP server and far exceeds the typical well-scoped 3-15 range. Many tools are convenience bundles or variants that could be consolidated, making the count a significant usability burden.

Completeness4/5

The toolkit covers a broad range of GIS tasks: format conversions, GeoJSON analysis, FeatureServer query/inspection, geocoding, site assessment, and sharing. Minor gaps exist (e.g., no Excel-to-GeoJSON, no FeatureServer update/delete), but most missing functionality can be worked around by chaining existing tools.

Resources