tb_suggestGenerates up to eight autocomplete search phrases from typed text, correcting Finglish and colloquial wording so you can choose accurate queries before searching.
Torob's autocomplete: up to 8 search phrases for typed text (fixes Finglish and colloquial wording).
Use before tb_search. Works even while other calls are blocked.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Typed text, e.g. 'ayfon' or 'لپ'. |
Changes observed during successful MCP inspections.
v0.2.0Input schema / properties / text / descriptionPrevious value: -"Typed text, Persian or Finglish (e.g. 'ayfon', 'لپ')."New value: +"Typed text, e.g. 'ayfon' or 'لپ'."v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world). The description adds real behavioral context beyond that: a hard cap of 8 results and that it normalizes Finglish/colloquial input into canonical phrases, plus the availability note about blocked calls.
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 filler, with the core capability front-loaded and the workflow hint second. Nothing is redundant or buried.
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 single-parameter read-only autocomplete tool with full schema coverage and rich annotations, the description supplies enough to call it correctly, including the result cap. Only the exact return shape (bare strings vs. structured suggestions) is left implicit, which is minor here.
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% with an example provided, so the baseline is 3. The parenthetical about fixing Finglish and colloquial wording adds meaning about what the 'text' parameter tolerates, which the schema's plain example does not convey.
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?
Names a specific verb+resource ('autocomplete: up to 8 search phrases for typed text') and adds scope details (max 8 results, Finglish/colloquial normalization). This clearly separates it from tb_search, which consumes the phrases rather than producing them.
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?
'Use before tb_search' gives explicit sequencing guidance relative to the most likely alternative. It also notes it remains available while other calls are blocked. No explicit when-not-to-use condition is given, but the intended workflow is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.