stac_compute_index

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

With no annotations, the description carries the full burden. It explains that the tool automatically downloads required bands, computes the index formula, and stores the result as a single-band float32 raster. It also describes the return format (JSON with artifact_ref and value_range). No contradictions with annotations (none provided). Could mention potential storage implications, but overall transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat lengthy with full formulas and tips, but it is well-structured: summary, supported indices list, args, returns, tips, example. Every section adds value, though a few details (like exact formulas) could be condensed if redundancy is avoided.

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

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

Given 6 parameters, no output schema, and no annotations, the description is comprehensive. It explains inputs, outputs, usage context, and provides interpretation tips. It feels complete for an AI agent to invoke correctly.

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

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

Schema coverage is 0%, so the description must compensate. It provides detailed parameter descriptions: scene_id, index_name with list and formulas, bbox format, cloud_mask explanation, output_format vs output_mode, and interpretation guides. This adds significant meaning beyond the raw schema, making it easy for an AI to use correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool computes a spectral index like NDVI or NDWI for a scene. It specifies the verb 'compute' and the resource 'spectral index', distinguishing it from sibling tools like 'stac_download_bands' or 'stac_temporal_composite'.

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

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

The description provides usage context such as 'Only works for optical collections (Sentinel-2, Landsat)' and suggests using 'stac_capabilities' to see available indices. It advises enabling 'cloud_mask=True' for cleaner results and notes temporal change analysis. However, it does not explicitly state when not to use this tool or mention alternatives.

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