gisgp

detect_coordinate_order

Detect whether [x, y] pairs are [lon, lat] or [lat, lon] — resolves a genuinely common real-world confusion (one of the most-viewed GIS StackExchange questions ever, 550k+ views). Certain when any value exceeds ±90 (only longitude can); honestly reports 'inconclusive' otherwise, never a fabricated guess. Pure computation, no external API. Returns JSON: {ok, order, confidence, 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": "detect_coordinate_order"
  }
}

Input Schema

Name	Required	Description	Default
`points`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedJul 28, 2026

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description fully discloses behavior: only longitude can exceed ±90, so certainty when values exceed that; otherwise returns 'inconclusive' without guessing. It also notes pure computation and no external API, plus the return format.

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?

The description is extremely concise and front-loaded: the first sentence states the purpose. Every sentence adds value, no fluff.

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

Completeness5/5

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

Given the simple single-parameter input and the presence of an output schema (mentioned but not shown), the description provides sufficient context: explains input semantics, behavioral certainty, and return JSON structure. No gaps.

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 coverage is 0%, but the description explains that the tool takes [x,y] pairs and detects their order, adding context beyond the schema's raw array definition. It clarifies the semantic meaning of the input.

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 uses specific verb 'detect' and clearly states the resource: coordinate order. It distinguishes itself from siblings like convert_coordinates by focusing on order detection, not conversion.

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?

The description conveys when to use the tool: when there is confusion about coordinate order, a common real-world problem. It does not explicitly state when not to use it, but the context is clear.

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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