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search_twitter

Search Twitter/X posts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pagesNoNumber of pages to fetch, 1-20 (default: 1)
queryYesSearch keyword (max 500 characters)
sort_byNoSort order: "most_recent" or "relevance"most_recent
get_sentimentNoAdd AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / get_sentiment / description
      Previous value: -"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small per-page surcharge."New value: +"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints."
  2. Changed1 schema field changed
    • changedInput schema / properties / pages / description
      Previous value: -"Number of pages to fetch, 1-10 (default: 1)"New value: +"Number of pages to fetch, 1-20 (default: 1)"
  3. First observed

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It states the action but does not mention pagination behavior, rate limits, authentication needs, or what the response contains. The schema hints at pagination via 'pages' and sentiment analysis via 'get_sentiment', but the description itself adds no behavioral context beyond the basic search action.

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 short sentence that is front-loaded and to the point. It wastes no words and is appropriately sized for a simple search tool, though it could arguably include a bit more context without becoming verbose.

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?

For a search tool with a well-documented schema, the description is minimally adequate. It lacks explicit guidance on result format, pagination limits, or when to use sibling tools, but the schema covers parameters and the tool's purpose is clear. Given no annotations and no output schema, a bit more context would improve completeness, but it is not critically incomplete.

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 all four parameters. The description adds no additional meaning beyond what the schema provides. Baseline 3 is appropriate since the schema does the heavy lifting and the description doesn't need to compensate.

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 'Search Twitter/X posts' clearly states the verb (search) and resource (Twitter/X posts), which distinguishes it from sibling tools like search_twitter_users or twitter_tweet_details. It is concise and unambiguous, though it doesn't elaborate on scope or features beyond the basic action.

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?

The description implies usage for searching posts on Twitter/X, and the sibling list shows related tools like search_twitter_users and twitter_tweet_details, but there is no explicit guidance on when to choose this over alternatives. The schema parameters (query, pages, sort_by, get_sentiment) provide some context, but the description itself offers no when-to-use or when-not-to-use instructions.

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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