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kinhunt

twitterapi-mcp

by kinhunt

search_users

Find Twitter users matching a query. Specify count to limit results up to 50.

Instructions

Search for Twitter users

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of users to retrieve (default: 10, max: 50)
queryYesSearch query for users

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, and the description gives no behavioral details such as authentication requirements, rate limits, pagination, or the shape of returned data. 'Search' implies read-only behavior, but that is not explicitly disclosed, leaving the full burden on the description unfulfilled.

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

Conciseness4/5

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

The description is a single concise sentence with no wasted words. However, it is so brief that it borders on restating the tool name, which slightly limits its value even though it is structurally clean.

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

Completeness3/5

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

The schema fully documents parameters, but there is no output schema and no description of what a 'user' result contains or how this tool fits among the exact-lookup siblings. For a low-complexity tool this is adequate yet leaves noticeable gaps in selection and interpretation.

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%, with both 'query' and 'count' already described in the schema. The tool description adds no additional meaning about parameters, so the baseline of 3 applies.

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 ('Search') and resource ('Twitter users'), making the core action clear. It distinguishes itself from search_tweets by targeting users rather than tweets, but does not explicitly contrast with get_user_by_username or get_user_by_id for exact lookups.

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

Usage Guidelines2/5

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

No guidance is given for when to use this tool versus sibling tools like get_user_by_username, get_user_by_id, or search_tweets. The agent must infer from the name that this is query-based search, which is not explicitly stated.

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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