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create_monitored_area

Set up continuous satellite monitoring for a fixed area: choose a location and a metric (ships, fires, water, vegetation), and each new Sentinel-1/2/VIIRS image is measured automatically.

Instructions

Put a place under continuous satellite measurement: pick an area and what to count, and every new Sentinel-1 / Sentinel-2 / VIIRS acquisition over it is measured automatically from then on. Use this when the question is about a quantity at a fixed place over time ("how many ships are alongside", "how much has burned", "is the water receding") rather than about events, which is create_standing_order. Creating is free; each automatic check costs a small number of tokens only when it finds new imagery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxYesThe area to measure, [west, south, east, north] in WGS84. Must be under 5,000 km² — measurement is per-pixel over the area, so a country-sized box is rejected rather than silently sampled.
nameNoLabel for the area (default "Monitored area").
metricYesWhat to count. Plain words work: ships, fires, vegetation, water, burn, snow, built_up, moisture, night_lights. Index names are also accepted: ship_detection, fire_count, ndvi, evi, savi, ndmi, ndwi, mndwi, ndbi, ndsi, nbr, dnb, vv, vh, rvi, rfdi, cr. The sensor is chosen from the metric.
start_dateNoYYYY-MM-DD to begin the history from. Defaults to 30 days ago — a longer backfill measures more scenes and therefore costs more on the first check.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaYes
summaryNoOne-line natural-language summary of the result, ready to relay to a user.
meteringNo
Behavior4/5

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

Annotations declare readOnlyHint=false and destructiveHint=false, and the description adds cost behavior ('Creating is free; each automatic check costs...') and the automatic monitoring behavior ('every new acquisition... measured automatically'). It does not contradict annotations.

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 main function, and includes decision guidance and cost context without redundancy. Every clause adds value.

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?

Given the 4-parameter schema with 100% description coverage, plus an output schema, the description provides sufficient context: it explains the persistent monitoring behavior, cost model, and when to use it. There is no missing critical information.

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 schema description coverage is 100%, with detailed descriptions for bbox, name, metric, and start_date, including cost implications. The description only adds a high-level mapping ('pick an area and what to count') without new parameter semantics.

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 uses the specific verb 'Put a place under continuous satellite measurement' and clarifies the resource (area + metric). It distinguishes from create_standing_order by explicitly contrasting quantities at a fixed place over time versus events. This clearly communicates the tool's core function.

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

Usage Guidelines5/5

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

It provides explicit when-to-use guidance: 'Use this when the question is about a quantity at a fixed place over time' and names the alternative 'create_standing_order' for events. This gives an agent clear decision criteria.

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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