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Blm Claims Summary

blm_claims_summary
Read-onlyIdempotent

Counts of US federal mining claims (BLM MLRS) within a radius of a point, broken down by claim type and status, with total recorded acres — how heavily staked is the ground around a deposit or project site, and how much of it is active versus closed.

Input Schema

NameRequiredDescriptionDefault
statusNoWhich claims: "open" (default — every claim not closed: Active, Filed, Under Review, On Appeal…), "active" (disposition exactly Active), "closed", or "all".
latitudeYesLatitude (WGS84)
longitudeYesLongitude (WGS84)
radius_kmNoRadius in km, 0.1–50 (default 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds useful context beyond that by specifying what the tool produces — counts partitioned by type/status plus aggregated acreage — which is the main behavioral fact an agent lacks given there is no output schema.

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

Conciseness4/5

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

It is a single sentence with the core verb lead ('Counts of...') front-loaded, followed by the breakdown and then the interpretive use case. It is slightly long and the em-dash clause is more narrative than strictly necessary, but nothing is wasted.

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?

With annotations covering safety and the schema covering all four parameters at 100% coverage, the only remaining burden is describing the return shape for the absent output schema — which the description does (counts by type and status, total recorded acres). It stops short of stating pagination or the exact response structure, but is sufficient to call 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 description coverage is 100%: latitude, longitude, radius_km (with range and default) and the status enum are all documented in the schema, including the non-obvious 'open' semantics. The description only restates the point-and-radius concept and adds no syntax or semantic detail beyond the schema, so the baseline 3 applies.

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?

The description states a specific resource (US federal mining claims, BLM MLRS) and output shape (counts broken down by claim type and status plus total recorded acres), which reads clearly as an aggregation tool. It does not, however, explicitly contrast itself with the sibling record-returning tools blm_claims_near or blm_claims_in_bbox, so the differentiation is only implicit.

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 phrase 'how heavily staked is the ground around a deposit or project site' implies a research/assessment use case, but there is no explicit when-to-use or when-not guidance and no named alternative. An agent can infer this is the aggregate view versus the list views, but must do the routing itself.

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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