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get_user_profile_context

Retrieve a Twitter user's complete profile including bio, metrics, pinned tweet, and recent posts to evaluate credibility and decide on engagement actions.

Instructions

Fetches a comprehensive Twitter/X user profile including bio, profile metadata, public metrics (followers, following, tweet count), the pinned tweet (if set), and the 5 most recent original tweets. Use this tool when the LLM needs to understand who a user is before engaging with them—for example, checking credibility, reading their bio, reviewing their recent activity, or deciding whether to reply, retweet, or quote. Input is the @username (without the @ symbol). Returns a rich combined JSON object with all profile context in one call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesThe Twitter/X username (handle) to look up. Do NOT include the @ symbol. Example: "elonmusk", "twitter". The username is case-insensitive and will be resolved to the canonical Twitter user profile.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesIndicates the outcome of the operation: "success" or "error".
messageYesA human-readable summary of the result.
dataYesContainer holding the user profile data, bio, metrics, pinned tweet, and recent tweets.
Behavior4/5

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

No annotations provided, so description carries burden. It details all fetched content and input format. Lacks mention of rate limits or auth requirements, but for a read-only tool this is adequate.

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?

Well-structured and front-loaded with purpose. Slightly wordy but each sentence provides useful info. Could be tighter, but still efficient.

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?

Given single parameter and output schema, description fully covers what the tool returns and when to use. Complete for a profile lookup context.

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

Parameters4/5

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

Schema coverage 100% with clear description. Description adds value beyond schema by specifying no @ symbol, case-insensitivity, and examples.

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?

Description clearly states it fetches a comprehensive user profile including bio, metadata, metrics, pinned tweet, and recent tweets. Distinguishes from siblings (post_tweet, search_tweets) as a read-only profile tool.

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

Usage Guidelines4/5

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

Explicitly states when to use: when LLM needs to understand a user before engaging. Provides examples like checking credibility or deciding to interact. Could mention alternatives but sufficiently clear.

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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