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gisgp

by io.github.uponex
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guess_crs_from_coordinates

Best-guess candidate CRS for raw [x, y] coordinates with no metadata (e.g. a shapefile with a missing .prj) — real demand signal (79k+ views on GIS StackExchange). Genuinely ambiguous by nature — returns ranked candidates with an honest 'not a certain identification' caveat, never a single confident answer. Pure computation, no external API. Returns JSON: {ok, x_range, y_range, candidates, note}.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "points": "<points>"
    },
    "name": "guess_crs_from_coordinates"
  }
}

Input Schema

NameRequiredDescriptionDefault
pointsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

No annotations, but description fully discloses behavior: returns ranked candidates with uncertainty caveat, never a single answer, pure computation no API, and lists JSON return fields. No contradictions.

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 plus return format: every sentence earns its place. Front-loaded with purpose, followed by caveats, safety, and output structure. No redundancy.

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?

Covers purpose, usage, behavior, and returns. Missing input size limits or error handling, but the tool is simple and description is sufficient for an agent to use correctly.

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

Parameters3/5

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

Schema has zero description coverage, but description adds 'raw [x, y] coordinates', implying each point is a 2-element array. Could be more explicit about required shape, but provides essential context.

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?

Clearly states it guesses a CRS from raw coordinates with no metadata, using a specific example (missing .prj). Distinguishes from siblings by focusing on coordinate-only CRS identification.

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

Usage Guidelines4/5

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

Provides clear context for when to use (shapefile with missing .prj) and sets expectations about ambiguity. Lacks explicit exclusions or alternatives, but the specialized use case is well-defined.

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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