get_management_recommendations

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

With no annotations provided, the description carries the full burden and discloses important behavioral traits: coverage is limited to a curated Mesoamerican table and the tool is not a global database. The instruction to avoid inventing measures is especially valuable. It does not describe response formatting or matching details, but an output schema exists and the main limitation is clearly exposed.

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 two concise, front-loaded sentences. The first states the core purpose and scope, while the second adds the critical limitation and fallback behavior. There is no filler or redundant information.

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?

For a single-parameter retrieval tool with an output schema, the description covers the main essentials: what the tool returns, where the data comes from, and how to behave when no match is found. It could clarify the `covered_species` matching nuance further or add an example, but an agent has enough information to invoke the tool 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?

The schema has one required parameter, `scientific_name`, with 0% schema description coverage, so the description needed to compensate. It adds some meaning by framing the input as a 'known invasive species' and implying it must match a species in `covered_species`. However, it does not explain expected format, synonym handling, or exact-match behavior, leaving the compensation incomplete.

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 identifies the resource as 'control and management measures' and adds useful scope: 'known invasive species' and 'curated table focused on Mesoamerica.' It distinguishes the tool from sibling tools like identify_plant_from_photo and list_country_alien_species, though it does not state an explicit verb such as 'retrieves' or 'returns.'

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 gives clear context for when the tool applies by stating it only covers species listed in `covered_species` and is not a global database. It also tells the agent to say so rather than inventing measures when no match exists, which is strong usage guidance. It does not explicitly name sibling alternatives or say when to prefer another tool.

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