autosuggest

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It states that it returns suggestions, category-scoped searches, and sometimes product matches, which is helpful. However, it does not mention whether the tool is read-only, any side effects, or limitations, so it leaves some behavioral aspects implicit.

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 concise and front-loaded with the core purpose, followed by usage context and expected results. Every sentence serves a purpose, and there is no redundant information.

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?

An output schema exists, so return details are covered externally. The description explains what the tool does, when to use it, and what it returns at a high level. It lacks explicit mention of edge cases or query formatting, but for a single-parameter tool with an output schema, it is reasonably complete.

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 must compensate. It only implies the query is the shopper's raw input by saying 'wording is messy', but it does not elaborate on format, length, or any constraints. The description adds minimal meaning beyond the parameter name 'query'.

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 a specific verb ('Correct and complete') and resource ('Flipkart search query'), and distinguishes the tool's purpose from siblings like search_products and amazon_autosuggest by emphasizing it's for messy queries. The mention of 'first' also implies a distinct role in the search flow.

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 says 'Use this first when the shopper's wording is messy (typos, missing brand/model)', which gives clear when-to-use guidance. However, it does not explicitly list when not to use it (e.g., when the query is already clean, use search_products directly), so it's strong but not fully exhaustive.

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