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get_patch_data

Retrieve patch variables as a 2D grid for heatmaps or spatial analysis. Optionally get summary statistics or downsample large worlds.

Instructions

Get patch data as a 2D grid (useful for heatmaps / spatial analysis).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
attributeYesThe patch variable to report (e.g. 'pcolor', 'grass').
max_cellsNoUpper bound on the number of grid cells returned in full-grid mode. When the world exceeds the cap, rows and columns are evenly downsampled (nearest-neighbor) to fit; the response includes a ``downsampled_from`` field so the AI knows it's seeing a subsample. Default 10000 (≈ 100×100). Set to 0 to disable the cap (not recommended for large worlds).
summary_onlyNoIf True, return shape + min/mean/max/std/unique-count instead of the full 2D grid. For a 100×100 world this trims ~10k cells of JSON to ~6 numbers — useful when you just want to know "is this attribute distributed widely?" without enumerating every patch.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states the output format, omitting any mention of side effects, permission requirements, or that it is a read-only operation. The schema covers parameter behavior, but the description itself lacks transparency.

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 a single, front-loaded sentence that immediately communicates the core function and use-case. It contains no filler or redundant information; every word earns its place.

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?

Given the existence of an output schema and complete parameter documentation, the description is adequate but leaves gaps. It does not explain that only one attribute is returned per call (implied by 'attribute' parameter), nor does it provide usage context relative to 37 sibling tools. Overall, it meets minimum viability for a simple retrieval tool.

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% per context signals, so baseline is 3. The description adds no extra parameter meaning beyond '2D grid' output hint; all parameter semantics are already fully documented in the input schema. The description does not compensate for any gaps.

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?

Description clearly states the tool retrieves patch data formatted as a 2D grid, explicitly noting its utility for heatmaps and spatial analysis. This verb+resource+use-case formulation distinguishes it from siblings like get_agent_sample or get_world_state, which serve different purposes.

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 implies usage for spatial/heatmap analysis via the parenthetical remark, but provides no explicit guidance on when to use versus alternatives, no exclusions, and no prerequisites. The context is implied but not systematically stated.

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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