get_notable_observations

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only gives a high-level purpose and does not mention whether results are limited to recent sightings, how 'notable' is determined, or any response format or pagination details.

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 a single, well-structured sentence with no unnecessary words. It is front-loaded with the key action and resource, making it easy to parse.

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?

With no output schema and no annotations, the description should provide more context. It fails to clarify the distinction from sibling tools like get_recent_observations or get_nearby_notable_observations, and does not explain limits, interpretation of results, or any additional behavior.

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 100% with descriptions for all three parameters, so the baseline is 3. The tool description adds no extra meaning beyond the schema, such as how 'back' interacts with rarity or how maxResults is applied.

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 'Get rare/unusual bird observations in a region' with a specific verb and resource, and the qualifier 'rare/unusual' distinguishes it from general observation tools like get_recent_observations. The phrase 'great for finding rarities' reinforces its unique value.

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 offers a use case ('great for finding rarities') but does not explicitly compare to alternatives like get_nearby_notable_observations or explain when not to use it. The guidance is implied via the rarity focus rather than stated as a selection rule.

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