PetalPal Plant Care

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

Annotations already declare the safe read-only, idempotent, non-destructive profile, so the description focuses on content: the fields returned, the original page and references, and editorial status. The cut-flower versus rooted-plant warning adds real behavioral context beyond the annotations, though pagination and response shape are not described.

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?

Two tight sentences with the action and required identifier front-loaded, followed by the returned fields and the scope caveats. Every clause carries information an agent needs.

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?

There is no output schema, so the description carries the burden of explaining the return value, and it does so by naming the guide sections, the original page, references, and editorial status. Combined with the stated caveats, an agent has everything needed to call it 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 100%, so the parameters are already documented. The description still adds value by stressing that plant_id must be the exact identifier returned by search_plants and by distinguishing cut-flower and rooted-plant identifiers such as rose versus rose-pot.

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 names a specific verb and resource (retrieve the PetalPal care guide), pins the input to an exact plant_id from search_plants, and enumerates the guide contents. It also states what the tool is not (photo identification or diagnosis), which cleanly separates it from the search_plants sibling.

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?

It explicitly routes the agent through search_plants to obtain the exact plant_id, then calls this tool for the guide. Exclusions are spelled out: not photo identification, not a diagnosis, and never substitute cut-flower care for a rooted plant.

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

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so safety is settled. The description adds real behavioral context beyond that: multilingual coverage across ten languages, that cut flowers and rooted potted plants are distinct entries, and how to handle multiple matches. Pagination/limit behavior is the only unaddressed trait.

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?

Four short sentences, front-loaded with purpose then returns then workflow. Every sentence carries information, though the language enumeration slightly overlaps the schema's language parameter description.

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?

No output schema exists, and the description compensates by naming the fields returned. The search-then-fetch workflow is spelled out end to end. Only the limit parameter's effect on result count is left unmentioned.

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 75%, with query, category and language each carrying their own descriptions, so the baseline is 3. The description's 'name, common alias or plant ID across ten languages' largely restates those schema descriptions, and the 'cut flowers and rooted potted plants are separate entries' note is the only genuinely additive hint for the category enum.

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?

States a specific verb and resource ('Find plants by name, common alias or plant ID across ten languages') and even previews the return payload (canonical plant IDs, category, care-page links). It also separates itself from the sibling by naming get_plant_care as the follow-up consumer of a plant_id rather than a search surface.

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?

Gives a clear routing rule ('Use a returned plant_id with get_plant_care') and a disambiguation policy ('if several plants fit, ask the user which one they have'). The cut-vs-potted note warns about a real selection pitfall. No explicit when-not-to-use case, though the schema's 'search the plant name rather than a whole care question' covers that gap.

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