Free-text search across the full catalogue — use for open queries like 'blockout for bedroom' or 'wood venetian'. Returns id, name, category, description, and product_url. For filtering by category, colour, or dimensions use lookup_catalog instead. Pass the returned id to get_product or get_price.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Free-text query, e.g. 'blockout' or 'venetian' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It discloses the return fields (id, name, category, description, product_url) and the scope ('full catalogue'). However, it does not mention potential large result sets, pagination, or whether the query parameter is optional, leaving minor gaps in behavioral disclosure.
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 sentences, each earning its place: purpose with examples, return fields, and usage alternatives/next steps. It is front-loaded and free of redundancy, making it easy for an agent to parse quickly.
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 one-parameter tool with no output schema, the description is quite complete: it explains purpose, return fields, when to use vs. alternatives, and integrates with downstream tools. It lacks only minor details like response format or result limits, which are not critical given the tool's simplicity.
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 value by clarifying that the query is for open, natural-language searches (e.g., 'blockout for bedroom'), going beyond the schema's simple example. It reinforces the free-text nature and provides richer usage examples, which aids parameter understanding.
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 the tool's function: 'Free-text search across the full catalogue' with examples of valid open queries. It distinguishes itself from the sibling tool lookup_catalog by explicitly directing filtered queries there, and it names downstream tools (get_product, get_price) for continued use.
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 says when to use this tool ('use for open queries') and explicitly points to an alternative for structured filtering ('For filtering by category, colour, or dimensions use lookup_catalog instead'). It also provides a clear next step ('Pass the returned id to get_product or get_price'), giving the agent actionable usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools have distinct purposes, but the presence of three search tools (search_catalog, search_products, lookup_catalog) and legacy tools (create_order, submit_enquiry) creates minor overlap. Descriptions help differentiate, but an agent might initially confuse them.
All 26 tool names follow a consistent verb_noun snake_case pattern (e.g., cancel_cart, configure_product). No mixed cases or irregular verbs are present.
26 tools is slightly high for a blind shop, but the domain requires many operations (search, pricing, cart, checkout, recommendations, etc.). Some legacy tools could be removed, but the count is still reasonable.
The tool surface covers the full customer journey from product discovery (search, recommendations) to purchase (cart, checkout, payment) and post-purchase (orders, swatches, price match, delivery estimates). No obvious gaps for the stated purpose.