blinkit_autosuggest

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

No annotations are present, and the description does not disclose behavioral traits such as read-only nature, required user state, or rate limits. For a suggestion tool, more behavioral context would help, e.g., whether it depends on location or cart contents.

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 extremely concise with one sentence, no unnecessary words. However, it may be too succinct for full clarity, but conciseness is generally positive.

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 no output schema and no annotations, the description is minimal. It does not explain expected output (e.g., list of strings, objects), error handling, or behavior for empty or invalid queries. For a simple tool, it may be borderline adequate, but missing details reduce completeness.

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 single parameter 'query' is only described as 'partial query' without format, constraints, or examples. Schema description coverage is 0%, so the description should provide more detail (e.g., minimum length, encoding) but fails to do so.

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 provides 'Typeahead suggestions for a partial query,' indicating the purpose of autocomplete functionality. It implies a verb (suggest) and resource (query suggestions), and it distinguishes from siblings like blinkit_search which handles full queries.

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?

No guidance is provided on when to use this tool versus alternatives like blinkit_search or blinkit_recommendations. The description implies use during partial query entry but lacks explicit when-not or context.

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