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entity_change

Read-only

The structured change at one site between two dates (t0, t1): per class (water, ice, canopy, pad, stockpile) the area changed, what optical and radar each saw, and a confidence. Read height_class first: only repeat_surface supports a volume change. Slow (about 15–60 s): start=true answers at once with a job_id for job_status. Agent keys only. Metered: see CHARGING in the server instructions; quote first with billing_quote.

Input Schema

NameRequiredDescriptionDefault
idNoThe entity's numeric id (with entity_type).
t0YesThe earlier date, YYYY-MM-DD, on or after 1984-03-16. Required.
t1NoThe later date, YYYY-MM-DD. Default today.
latNoLatitude in decimal degrees, -90 to 90 (WGS84).
lngNoLongitude in decimal degrees, -180 to 180 (WGS84).
startNotrue: answer at once with a job_id (the same reservation, settled when the measurement is done)
radius_mNoFootprint radius in metres, 50-2500, overriding the site's held footprint (else a 500 m circle).
max_cloudNoMaximum cloud cover of a scene, 0-100 percent. Default 40.
entity_typeNoEntity kind: deposit | infrastructure | company | project. With id; or pass lat + lng.
same_seasonNoFor spans of 300+ days, take the t0 frame at t1's day of year. Default true.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / start
      Added value: +{
      +  "default": false,
      +  "description": "true: answer at once with a job_id (the same reservation, settled when the measurement is done)",
      +  "type": "boolean"
      +}
  2. Changed17 schema fields changed
    • removedInput schema / properties / entity_type / default
      Removed value: -null
    • removedInput schema / properties / entity_type / title
      Removed value: -"Entity Type"
    • removedInput schema / properties / id / default
      Removed value: -null
    • removedInput schema / properties / id / title
      Removed value: -"Id"
    • removedInput schema / properties / lat / default
      Removed value: -null
    • removedInput schema / properties / lat / title
      Removed value: -"Lat"
    • removedInput schema / properties / lng / default
      Removed value: -null
    • removedInput schema / properties / lng / title
      Removed value: -"Lng"
    • removedInput schema / properties / max_cloud / title
      Removed value: -"Max Cloud"
    • removedInput schema / properties / radius_m / default
      Removed value: -null
    • removedInput schema / properties / radius_m / title
      Removed value: -"Radius M"
    • removedInput schema / properties / same_season / title
      Removed value: -"Same Season"
    • removedInput schema / properties / t0 / title
      Removed value: -"T0"
    • removedInput schema / properties / t1 / default
      Removed value: -null
    • removedInput schema / properties / t1 / title
      Removed value: -"T1"
    • removedInput schema / title
      Removed value: -"entity_changeArguments"
    • removedOutput schema / title
      Removed value: -"entity_changeDictOutput"
  3. Changed1 schema field changed
    • changedInput schema / properties / id / anyOf
      Previous value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "integer"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
  4. Changed9 schema fields changed
    • addedInput schema / properties / entity_type / description
      Added value: +"Entity kind: deposit | infrastructure | company | project. With id; or pass lat + lng."
    • addedInput schema / properties / id / description
      Added value: +"The entity's numeric id (with entity_type)."
    • addedInput schema / properties / lat / description
      Added value: +"Latitude in decimal degrees, -90 to 90 (WGS84)."
    • addedInput schema / properties / lng / description
      Added value: +"Longitude in decimal degrees, -180 to 180 (WGS84)."
    • addedInput schema / properties / max_cloud / description
      Added value: +"Maximum cloud cover of a scene, 0-100 percent. Default 40."
    • addedInput schema / properties / radius_m / description
      Added value: +"Footprint radius in metres, 50-2500, overriding the site's held footprint (else a 500 m circle)."
    • addedInput schema / properties / same_season / description
      Added value: +"For spans of 300+ days, take the t0 frame at t1's day of year. Default true."
    • addedInput schema / properties / t0 / description
      Added value: +"The earlier date, YYYY-MM-DD, on or after 1984-03-16. Required."
    • addedInput schema / properties / t1 / description
      Added value: +"The later date, YYYY-MM-DD. Default today."
  5. Added

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already cover safety (readOnly/destructive/openWorld), and the description layers on the operational facts an agent cannot get elsewhere: 15–60 s latency, the async escape hatch (start=true returns a job_id resolved via job_status), and that it is agent-key-only and metered. That is exactly the beyond-annotation context this dimension rewards.

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?

Five dense sentences, each doing distinct work: output shape, class precondition, latency, async pattern, auth, billing. The critical constraints (precondition, cost, latency) are stated before the agent would commit to a 60-second call.

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

Completeness5/5

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

For a metered, slow, async-capable read tool with an output schema already covering return shape, the description supplies everything an agent needs to call it correctly: cost gating, auth, latency, job handling, and the class validity rule. No material operational gap remains.

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 coverage is 100%, so the schema already documents t0, t1, radius_m, max_cloud, same_season, and entity_type/lat-lng alternatives in detail. The description only adds value on `start` by naming job_status as the follow-up; it says nothing extra about same_season or the footprint override that the schema doesn't already carry.

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 names a precise resource and scope: the structured change at one site between t0 and t1, broken down per class (water, ice, canopy, pad, stockpile) with per-sensor evidence and confidence. That distinguishes it from snapshot tools like entity_state, but it never contrasts with the closer sibling entity_history, leaving a small ambiguity for an agent choosing among time-based tools.

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

Usage Guidelines4/5

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

It states a hard prerequisite ('Read `height_class` first: only repeat_surface supports a volume change') and a billing precondition ('quote first with `billing_quote`'), which are real routing decisions. It stops short of explicit when-not-to-use guidance relative to entity_state or entity_history.

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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