Search Australian wholesale plant growers' live stock lists and price a whole plant list. Read-only.
Scored across 2 tools
The two tools have broadly distinct purposes: price_plant_list bulk-prices an existing plant list, while search_plants discovers which growers list a given plant and at what price. There is minor overlap since both surface trade pricing, but the input shape (list vs. single plant) and intent (price my schedule vs. who grows X) make them separable.
Both names use snake_case with a verb-first structure (price_plant_list, search_plants), which reads consistently. price_plant_list is a three-word verb+compound-noun form that is slightly less parallel with search_plants, but the convention is still clear.
Two tools is thin for the domain, though the server's scope (pricing and market lookup for Australian wholesale plants) is narrow enough that it is defensible. It sits at the borderline where a couple more operations (e.g. listing a grower's full stock) would feel warranted.
The stated purpose—search the wholesale market and price a plant list—is covered end-to-end, and the deliberate exclusion of order placement is disclosed. Minor gaps remain, such as retrieving a grower's complete catalogue or saving/comparing priced lists, but agents can work around them.
Price a whole plant list or planting schedule from wholesale growers' live stock lists: each line matched to a grower, size and trade price, with the growers near the job preferred. Returns the priced lines and a link to the priced list on HortOS, which the person opens, checks and sends themselves. This tool does not place an order.
| Name | Required | Description | Default |
|---|---|---|---|
| job | No | Optional: a name for the job or site. | |
| list | Yes | The plant list as text, one plant per line with quantity, name and pot size, e.g. '40 x Lomandra Tanika 140mm'. | |
| near | No | Optional: the job's suburb, town or postcode, so growers near the job are used. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only cover safety flags (readOnlyHint=false, openWorldHint=true, idempotentHint=false), so the description must and does add real behavior: it returns priced lines plus a link to a priced list on HortOS that a human opens, checks and sends themselves, and it explicitly does not place an order. This human-in-the-loop model and the non-mutating-in-practice boundary go well beyond the annotation set, though it says nothing about failure modes when a line cannot be matched to a grower.
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 dense sentences: the first front-loads what is produced and the matching behavior, the second covers the return artifact and the workflow boundary. No filler and nothing repeated from the schema or annotations.
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 return-value burden and does so ('the priced lines and a link to the priced list'), plus the human follow-up step and the no-order boundary. Combined with 100% schema coverage and present annotations, 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 baseline is 3. The description adds a meaningful nuance beyond the schema by saying growers near the job are 'preferred' rather than required, clarifying that `near` is a soft preference and not a hard filter. It does not add format details beyond the schema's own example.
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 and resource ('price a whole plant list or planting schedule from wholesale growers' live stock lists') and scopes it to per-line matching of grower, size and trade price. It is clearly distinct from the one sibling (search_plants), though it never names that alternative to route the agent explicitly.
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 establishes context (a plant list or planting schedule to be costed) and an explicit boundary ('This tool does not place an order'), so the agent knows this is pricing, not procurement. It stops short of naming when to prefer it over search_plants or any prerequisite for a successful run.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search Australia's live wholesale plant market: which wholesale growers list a plant, in which pot sizes, and from what trade price (AUD, ex GST). Use it for "who grows X" or "what does X cost wholesale". Botanical or common names both work.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Optional pot size, e.g. 140mm, 45L or Tube. | |
| query | Yes | Plant name, botanical or common, e.g. 'Lomandra Tanika' or 'lilly pilly'. | |
| state | No | Optional state or province code to limit growers, e.g. QLD, NSW, FL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description correctly aligns and doesn't contradict. The description adds behavioral context by specifying the geographic scope ('Australia'), the data source ('live wholesale plant market'), and the nature of results (which growers, pot sizes, and trade prices). It also implicitly notes that it returns a list of growers, which is not in the annotations. This goes beyond what annotations provide, so a 4 is appropriate.
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 brief and front-loads the core purpose in the first sentence, then adds usage guidance in the second. Every sentence earns its place. It avoids unnecessary details and is well-structured for quick comprehension by an agent.
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?
Given the tool's simplicity (one required param, no output schema) and the annotations covering read-only and open-world hints, the description is fairly complete. It explains the data source, scope, and usage scenarios. It does not mention output format or pagination, but for a search tool without an output schema, this may not be critical. However, a bit more on how results are ordered or what information each result includes could be beneficial, so a 4 rather than a 5.
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 description coverage is 100%, meaning all three parameters are described in the schema. The description adds semantic value by explaining the purpose of the query parameter ('who grows X or what does X cost wholesale') and notes that common names work, which is not in the schema. It also implies that 'size' and 'state' are optional filters, aligning with the schema but adding context. This pushes beyond the baseline 3.
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 starts with a specific verb ('search') and a clear resource ('Australia's live wholesale plant market'), and immediately clarifies the core use cases: 'who grows X' and 'what does X cost wholesale'. It explicitly mentions both botanical and common name support, and distinguishes itself from the sibling by focusing on market search rather than a price list. This is specific and clearly differentiates from price_plant_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 provides explicit guidance on when to use this tool: 'Use it for "who grows X" or "what does X cost wholesale"'. While it doesn't explicitly state when to use the alternative, it does not need to since the purpose is so clearly scoped. It also mentions that both botanical and common names work, which is a useful usage hint. The context is clear enough that an agent would know when to choose this over price_plant_list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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