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AIsa Go-To-Market

Search User by Keyword

get_twitter_user_search
Read-onlyIdempotent

Search X user accounts by keyword and get back matching profiles. Use this when you know roughly who you are looking for — a company name, a topic, a partial handle — but not the exact @handle. Cursor-paginated; returns full user objects under users. This searches accounts, not posts; to search tweet content use get_twitter_tweet_advanced_search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe keyword to search.
cursorNoThe cursor to paginate through the results. First page is empty.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already signal read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context beyond that: it is cursor-paginated, returns full user objects under `users`, and searches accounts rather than posts. This enriches the agent's mental model without contradicting annotations.

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?

The description is concise and front-loaded with the core action, then adds only high-value details: usage scenario, pagination/return format, and the sibling alternative. Every sentence earns its place with no filler or repetition.

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

Completeness5/5

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

For a two-parameter, read-only tool with full schema coverage, an output schema, and rich annotations, the description covers everything needed to invoke it correctly: when to use it, what to pass, how pagination works, and what comes back. No critical information 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 the schema already documents both `query` and `cursor` clearly. The description reinforces the meaning of `query` with examples like 'a company name, a topic, a partial handle', which adds slight context, but it does not substantially elevate understanding beyond the schema.

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

Purpose5/5

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

The description states a specific action ('Search X user accounts by keyword') and a clear resource, and explicitly distinguishes itself from tweet search by saying 'This searches accounts, not posts'. It also names the sibling `get_twitter_tweet_advanced_search` as the alternative, making the tool's purpose unambiguous.

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

Usage Guidelines5/5

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

The description gives explicit use conditions: 'Use this when you know roughly who you are looking for... but not the exact @handle.' It also directly states when not to use it by pointing to `get_twitter_tweet_advanced_search` for tweet content searches, providing both positive and negative guidance.

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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