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searchSearch Cocktailline recipes. Returns ids, titles and URLs; use fetch for the full recipe.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
searchSearch Cocktailline recipes. Returns ids, titles and URLs; use fetch for the full recipe.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the description's value-add is disclosing the response shape: ids, titles, and URLs rather than full content. That is useful behavioral context absent from any structured field, though it says nothing about result caps, ranking, or empty-result behavior.
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 short sentences, zero waste, with the core purpose front-loaded and the routing hint second. Every clause 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?
With no output schema, the description correctly compensates by naming the returned fields, and annotations cover safety. It is nearly complete for a simple one-parameter search, missing only sibling disambiguation and result-limit/pagination behavior.
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 description coverage is 0%, so the description carries the burden for the single 'query' parameter, and it never explains what the query accepts (keywords, phrases, filters). Mitigating this, a lone required string named 'query' on a search tool is largely self-evident, so the practical gap is small.
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 ('Search Cocktailline recipes') and adds the return shape (ids, titles, URLs). However, it does nothing to distinguish itself from the near-identical siblings 'search_cocktails' and 'find_cocktails', which is exactly where an agent needs differentiation. Clear, but sibling ambiguity remains.
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 to 'fetch' for the full recipe, which is a genuine when-to-use-else signal. But it gives no guidance for choosing between this generic 'search' and the overlapping siblings 'search_cocktails'/'find_cocktails', leaving the most consequential selection decision to inference.
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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