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by IBM

stac_mosaic

Combines overlapping satellite scenes into a single seamless raster. Ideal when your area of interest covers multiple tiles.

Instructions

Create a mosaic from multiple scenes.

Combines overlapping scenes into a single seamless raster. Useful when your area of interest spans multiple satellite tiles.

Args: scene_ids: List of scene identifiers to mosaic (from stac_search) bands: Bands to include (e.g., ["red", "green", "blue"]) bbox: Output bounding box [west, south, east, north] in EPSG:4326. Defaults to union of all scenes if not specified output_format: "geotiff" (default, lossless) or "png" (8-bit preview) cloud_mask: Apply SCL-based cloud masking per scene before merge (Sentinel-2 only) method: Merge method: - "last" (default): later scenes overwrite earlier in overlap areas - "quality": SCL-based best-pixel selection — picks the clearest pixel from overlapping scenes (Sentinel-2 only) output_mode: Response format - "json" (default) or "text"

Returns: JSON with artifact_ref for the mosaic raster

Tips for LLMs: - Use stac_coverage_check first to verify scenes cover the target area - Use method="quality" for cloud-free mosaics from Sentinel-2 data - Use method="last" for quick mosaics or non-optical data - For temporal compositing (e.g., seasonal median), use stac_temporal_composite instead

Example: mosaic = await stac_mosaic( scene_ids=["S2B_001", "S2B_002"], bands=["red", "green", "blue"], method="quality" )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bboxNo
bandsYes
methodNolast
scene_idsYes
cloud_maskNo
output_modeNojson
output_formatNogeotiff
Behavior5/5

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

With no annotations, the description fully discloses behavior: combines scenes, defaults (bbox union, method='last'), Sentinel-2 limitations for cloud_mask and quality method, and output format. Discloses that output is JSON with artifact_ref.

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?

Well-structured with intro, parameter list, tips, and example. All sentences add value, but parameter explanations are slightly verbose. Still appropriate for the complexity.

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?

Covers all 7 parameters, required and optional, explains behavior, provides usage guidelines, tips, and an example. Output format is described. Complete for a tool with no annotations or output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, but the tool description explains every parameter in detail, including defaults and usage examples. Completely compensates for missing schema descriptions.

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 clearly states 'Create a mosaic from multiple scenes' and explains it combines overlapping scenes into a seamless raster. It distinguishes from siblings like stac_temporal_composite by specifying it's for when area spans multiple tiles.

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?

Includes explicit 'Tips for LLMs' that advise using stac_coverage_check first, choosing method='quality' for cloud-free mosaics, and redirecting to stac_temporal_composite for temporal compositing. Provides clear when-to-use and alternatives.

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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