Lilambd Data for Agents

land

Land Use and Forest Loss by Region. What the ground of every state, province and prefecture is made of, and how it changed, counted from 30 m satellite pixels. One API for site screening, ESG and deforestation checks, urban growth, agriculture and climate apps and AI agents. Routes: /gaps (country, limit, offset); /world (thr); /nearby (lat*, lon*, radius_km, limit, offset); /classes (detail); /regions (country, q, limit, offset); /features (country, region_id, feature, limit, offset); /rankings (by, level, country, min_area_km2, min_tree_cover_km2, limit, offset); /countries (limit, offset); /regions/{id}; /countries/{code} (thr); /regions/{id}/soil; /regions/{id}/built; /regions/{id}/water; /regions/{id}/forest (thr); /regions/{id}/profile (thr); /regions/{id}/land-cover (min_km2). Paid $0.005 USDC per call via x402 (_meta["x402/payment"]); set sample=true for a free 3-row preview.

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": {
      "route": "<route>"
    },
    "name": "land"
  }
}

Input Schema

Name	Required	Description
`route`	Yes	One of: /gaps, /world, /nearby, /classes, /regions, /features, /rankings, /countries, /regions/{id}, /countries/{code}, /regions/{id}/soil, /regions/{id}/built, /regions/{id}/water, /regions/{id}/forest, /regions/{id}/profile, /regions/{id}/land-cover. Replace {placeholders} with a value, e.g. /search or /HND.
`params`	No	Query parameters, e.g. {"q":"tokyo","limit":"50"}
`sample`	No	Free preview, max 3 rows

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 3, 2026

TDQS

A3.6/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the two things an agent most needs: a cost of $0.005 USDC per call via x402 with the `_meta["x402/payment"]` mechanism, and a free escape hatch via `sample=true` capped at 3 rows. It omits rate limits, failure behavior, and what a response looks like.

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

Conciseness3/5

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

Front-loaded with the resource identity and the route table is compressed efficiently into a single dense sentence. However, the sentence "One API for site screening, ESG and deforestation checks, urban growth, agriculture and climate apps and AI agents" is keyword filler that occupies prime space without telling an agent anything actionable.

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?

For a 16-route gateway with a generic params bag and no output schema, the definition lists routes and their parameters but never says what any route returns, what units or time coverage apply, or how to choose among routes for a given question. Given the complexity, that leaves the agent to guess at the most consequential decision.

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 100%, but the `params` object is free-form `additionalProperties: string` with no enum, so the schema alone gives no clue which keys any route accepts. The description supplies that mapping per route (e.g. `/nearby (lat*, lon*, radius_km, limit, offset)`) and the asterisks signal required fields — a genuine addition. It falls short of explaining opaque names like `thr`, `by`, `detail`, and `feature`.

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

Purpose4/5

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

"Land Use and Forest Loss by Region" plus "what the ground of every state, province and prefecture is made of, and how it changed, counted from 30 m satellite pixels" states the resource and its resolution/coverage precisely. The verb is left implicit (it is a data-retrieval router, not an action), and nothing distinguishes it from the sibling `regions` tool, which is a real ambiguity.

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?

The use-case list (site screening, ESG, deforestation checks, urban growth, agriculture, climate) implies when to reach for it, and the enumerated routes imply which endpoint serves which question. But there is no explicit routing guidance, no when-not-to-use, and no reference to the sibling `regions` tool an agent might confuse it with.

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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