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putervision
by putervision

query_entities

Read-onlyIdempotent

Find entities in a spatial world model by keyword, type, region, proximity, tags, or status. Look up a specific entity's location and movement history with its ID.

Instructions

Find entities by keyword query (FTS5 search), type, region, spatial proximity, tags, or status. Alternatively, provide entity_id for single-entity location and historical trajectory lookup.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFilter by matching tags
typeNoFilter by entity type
limitNoMaximum number of entities to return (default: 50)
queryNoFull-text search query across entity names, tags, and properties
statusNoFilter by status
projectNoOptional project identifier
entity_idNoSpecific entity ID to look up directly (returns location and state)
region_idNoFilter by region ID
max_distanceNoMaximum distance radius from near_position
history_limitNoMaximum number of history events to return when include_history is true (default: 20)
near_positionNoCenter position for proximity distance search
min_confidenceNoMinimum confidence score (e.g. 0.5 to filter out decayed entities)
include_historyNoIf true and entity_id is specified, returns recent movement/event history

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the description carries a lower burden here. It does add context: FTS5 search, spatial proximity, and an alternative trajectory-lookup mode. However, it does not mention default limits, result ordering, pagination, or how much history is returned, which are behavioral details an agent might need.

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 two sentences, front-loaded with the primary action and the main filtering modes, and the second sentence covers the direct entity_id path with a clear 'Alternatively'. No surplus wording or repeated structured data.

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?

For a 13-parameter tool with a well-described schema and no output schema, the description covers the two main calling patterns: bulk search and individual entity lookup. It does not explicitly state the return envelope (array vs single record) or global constraints like limits and pagination, but the description and schema together are enough for most common invocations.

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?

The input schema describes all 13 parameters with 100% coverage, which sets a baseline of 3. The description groups related filters (keyword, type, region, spatial proximity, tags, status) and highlights the entity_id/history path, adding modest semantic value beyond schema descriptions but not deeply explaining any individual parameter.

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 states the action 'Find entities' and then enumerates the search dimensions (keyword/FTS5, type, region, spatial proximity, tags, status), followed by a distinct second path for entity_id lookup. This clearly differentiates it from mutation or simulation siblings like update_entity, set_relation, and simulate_movement.

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 description makes clear when to use the tool (to find/query entities, or to get a single entity's location/trajectory) but does not explicitly exclude other sibling tools, name alternatives, or state conditions for when another tool is more appropriate. The use-cases are implied but not compared against the rich sibling set.

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