WebLens

search_autocomplete

Google Autocomplete suggestions for a partial query. Useful for keyword research and intent discovery. Price: $0.004

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_autocomplete"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Maximum results to return
`query`	Yes	Search query

Schema Changelog

Changes observed during successful MCP inspections.

Changed9 schema fields changedOct 13, 2026
- addedInput schema / properties / limit / default
```
Added value: +10
```
- changedInput schema / properties / limit / description
```
Previous value: -"Max suggestions (default: 10, max: 20)"New value: +"Maximum results to return"
```
- addedInput schema / properties / limit / example
```
Added value: +10
```
- addedInput schema / properties / limit / maximum
```
Added value: +20
```
- addedInput schema / properties / limit / minimum
```
Added value: +1
```
- changedInput schema / properties / query / description
```
Previous value: -"Partial query to complete"New value: +"Search query"
```
- addedInput schema / properties / query / example
```
Added value: +"x402 payment protocol"
```
- addedInput schema / properties / query / maxLength
```
Added value: +500
```
- addedInput schema / properties / query / minLength
```
Added value: +1
```
First observedAug 4, 2026

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses a per-call price of $0.004, which is valuable context, but does not describe return format, rate limits, or whether results are region/language dependent. The cost disclosure lifts it above a bare minimum, but significant behavioral gaps remain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the core purpose and followed by use case and price. No sentence is wasted, and the pricing detail is placed last where it does not obscure the primary description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter read-only lookup with no output schema, the description covers what it returns (suggestions), what input it expects (a partial query), and the cost. It could be slightly more complete by noting that suggestions are returned as a list, but nothing critical for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both the query and limit parameters are fully documented in the schema. The description adds no syntax, format, or constraint details beyond what the schema already provides. A baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: Google Autocomplete suggestions for a partial query. This clearly distinguishes it in kind from siblings like search_web or search_trends, though it does not explicitly name an alternative. The purpose is immediately understandable without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives implied usage context ('useful for keyword research and intent discovery') but does not say when to prefer this over search_trends or search_web, nor when not to use it. The guidance is enough to suggest a scenario but leaves the agent to infer alternatives.

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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