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

Annotations already cover read-only and idempotent safety. The description adds valuable behavioral detail beyond that: the batch costs one upstream request, missing IDs are reported per-id in 'unresolved' rather than failing the batch, and the call fails only when nothing resolves. This gives the agent clear expectations for error handling and cost, exceeding the baseline provided by annotations.

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 three sentences, each carrying essential information: the core purpose, the cost efficiency of batching, and the error-handling behavior. It is front-loaded with the primary function and contains no filler or redundancy.

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?

The description covers the key aspects an agent needs: what the tool returns (identification thread and consensus), batch behavior, and failure conditions. The output schema exists, so return format is documented elsewhere. The schema parameter descriptions handle parameter details. Nothing critical is missing for correct invocation.

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 description coverage is 100% – both parameters (observation_id and include) have descriptive text, including guidance on the include array. The main description does not add parameter-specific semantics beyond what the schema provides, but it doesn't need to given the high coverage. Baseline 3 is appropriate.

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 states a specific verb ('Fetch'), resource ('observations by id'), and adds concrete detail about the community identification thread (who identified, agreement status, consensus taxon). This distinguishes it clearly from sibling tools like search_observations or get_species_counts, leaving no ambiguity about what the tool does.

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 implies the use case (fetching observations by known IDs) and explicitly notes batch efficiency ('far cheaper than ten separate lookups'). The schema parameter description for observation_id further routes the agent to inaturalist_search_observations for finding IDs, but the main description itself does not explicitly exclude other tools or state 'use when you have IDs'. This is a minor gap.

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