HortOS (Canada)

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

Annotations already mark readOnlyHint and openWorldHint, and the description adds important behavior beyond those: it does not place an order, returns a link on HortOS, and requires the person to review and send before grower confirmation. This meaningfully clarifies the workflow without contradicting the 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 focused sentences: core action, return value, and the critical non-ordering caveat. It is front-loaded and every sentence earns its place.

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 simple 3-parameter tool with readOnly/openWorld annotations and no output schema, the description covers the input, the matching behavior, the return link, and the post-call workflow. An agent has enough to invoke the tool and set expectations for the user.

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?

With 100% schema description coverage, the schema already documents job, list, and near effectively. The description adds contextual flavor such as 'growers near the job preferred' but does not materially expand parameter semantics beyond what the schema provides.

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-resource pair: 'price a whole plant list or planting schedule' from wholesale growers, and states the matching outcome and returned link. It distinguishes itself from sibling search_plants by focusing on list pricing and order hand-off, not plant search.

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 gives clear context for use: the tool accepts a plant list or planting schedule, matches lines to growers, and returns a link for the user to review and send. It does not explicitly say when to prefer this over search_plants, so it misses the top score.

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 the operation read-only and open-world, covering the safety profile. The description adds behavioral context beyond that: results reflect a 'live' market, prices are 'CAD, ex tax', and common names are accepted—each a useful disclosure not present in the 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?

Three sentences accomplish a lot: core function, output scope, intended use cases, and query flexibility. It is front-loaded with the verb and resource and contains no filler or redundant phrases.

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, the description carries the burden of explaining return values, and it does so explicitly (growers, pot sizes, trade price). Combining this with the readOnly annotation and the stated use cases, an agent has everything needed to select and 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 already documents all three parameters thoroughly (query, size, state) with examples, so the baseline is 3. The description's note that 'Botanical or common names both work' merely restates the schema's query description, and the CAD/ex-tax detail relates to output, not parameter meaning.

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 opens with a specific verb and resource: 'Search Canada's live wholesale plant market', then enumerates exactly what results are returned (growers, pot sizes, trade price in CAD ex tax). It is clearly distinct from its sibling price_plant_list because it is a cross-grower search rather than a standalone price list.

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 explicitly states when to invoke the tool: 'Use it for "who grows X" or "what does X cost wholesale"'. This gives clear context but does not name exclusions or alternatives, so it stops short of a full 5.

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