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triangulate_geometry

Create a triangulation of a geometry to enable accurate geospatial analysis and spatial measurements for GIS operations.

Instructions

Create a triangulation of a geometry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
geometryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The primary handler function for the 'triangulate_geometry' MCP tool. It accepts a WKT geometry string, uses Shapely's triangulate operation to generate triangles, and returns a dictionary with the resulting geometries in WKT format and a success message.
    @gis_mcp.tool()
    def triangulate_geometry(geometry: str) -> Dict[str, Any]:
        """Create a triangulation of a geometry."""
        try:
            from shapely import wkt
            from shapely.ops import triangulate
            geom = wkt.loads(geometry)
            triangles = triangulate(geom)
            return {
                "status": "success",
                "geometries": [tri.wkt for tri in triangles],
                "message": "Triangulation created successfully"
            }
        except Exception as e:
            logger.error(f"Error creating triangulation: {str(e)}")
            raise ValueError(f"Failed to create triangulation: {str(e)}")
  • A resource endpoint that lists 'triangulate_geometry' among available advanced GIS operations, serving as a catalog or indirect registration reference for the tool.
    @gis_mcp.resource("gis://operations/advanced")
    def get_advanced_operations() -> Dict[str, List[str]]:
        """List available advanced operations."""
        return {
            "operations": [
                "triangulate_geometry",
                "voronoi",
                "unary_union_geometries"
            ]
        }
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions creation but doesn't disclose behavioral traits like whether it modifies input, requires specific geometry types, has performance considerations, or what the output entails. This is inadequate for a mutation tool with zero annotation coverage.

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 a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for the tool's apparent complexity, though this conciseness comes at the cost of detail.

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

Completeness3/5

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

Given the tool has an output schema (which should cover return values), the description's minimalism might be acceptable. However, with no annotations, low schema coverage, and many sibling tools, it lacks context on behavior and usage, making it incomplete for effective agent decision-making.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It doesn't add any meaning beyond the schema's 'geometry' parameter—no details on format (e.g., GeoJSON, WKT), constraints, or examples. With 1 undocumented parameter, this leaves significant gaps.

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

Purpose3/5

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

The description states the action ('Create a triangulation') and the target ('of a geometry'), which is clear but vague. It doesn't specify what type of triangulation (e.g., Delaunay, constrained) or the output format, and it doesn't distinguish from siblings like 'voronoi' or 'convex_hull' that also process geometries.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. With many sibling tools for geometry processing (e.g., 'voronoi', 'convex_hull', 'simplify'), the description lacks context on specific use cases, prerequisites, or comparisons, leaving the agent to infer usage.

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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