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

No annotations are provided, so the description carries the full disclosure burden. It does disclose the return format ('Returns the GeoJSON FeatureCollection as a JSON string') and the expected input encoding (base64-encoded .fgb), adding value beyond the schema. But it omits failure modes for invalid base64/non-FGB input, coordinate-system handling, and any processing or size constraints.

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

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

Three sentences, front-loaded with the primary action in sentence one, selection-relevant format context in sentence two, and the return type in sentence three. No filler, though the background sentence is slightly generous in length for a tool description.

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

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

For a single-parameter conversion tool with an output schema, coverage is solid: input format, encoding, output format, and ecosystem context are all present. The output schema already covers the return shape, so the description needn't elaborate. Remaining gaps are edge behaviors (error cases, CRS/property preservation) that would only matter during troubleshooting.

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

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 for the lone parameter, and it does: flatgeobuf_base64 is explained as base64-encoded .fgb content, with background on what FlatGeobuf is. It adds real meaning beyond the schema's bare title 'Flatgeobuf Base64', though it stops short of details like whitespace tolerance in the base64 or encoding instructions.

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

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

States a specific verb and resource: 'Convert a FlatGeobuf file (base64-encoded .fgb) to a GeoJSON FeatureCollection.' The named input format (.fgb) distinguishes it from the many sibling *_to_geojson tools (csv, dxf, kml, gpx, shapefile, wkt, mapinfo_tab), and the reverse sibling geojson_to_flatgeobuf is implicitly differentiated by direction.

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

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

Supplies format context ('used for fast HTTP-range-request streaming (e.g. deck.gl, MapLibre, QGIS cloud layers)') that signals when FlatGeobuf data might arise, and the base64-encoded requirement is an implicit precondition. However, it never explicitly states when to choose this converter over alternatives, gives no exclusions, and does not point to geojson_to_flatgeobuf as the reverse operation.

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