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threads_user_posts

Get a single Threads (Meta's Threads app) user's recent posts by username. Returns post text, engagement metrics, media, timestamps, and permalinks. Billed $0.006 per request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesThreads username, with or without leading @ (max 100 characters)
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. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the disclosure burden. It explicitly states this is a read operation ('Get'), lists the returned content (post text, engagement metrics, media, timestamps, permalinks), and discloses the per-request cost. It does not mention auth, rate limits, or pagination, but the key behavioral facts for tool selection are present.

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 tight sentences: the core action is front-loaded, the return fields are listed, and the billing note earns its place. There is no redundancy, filler, or unnecessary detail.

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 description names the resource, returned fields, and cost, which is enough for basic selection. However, it does not specify how many posts are returned, the ordering, or any pagination behavior, and 'recent' is undefined—an important gap given there is no output schema to clarify the result shape.

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 parameters—username and get_sentiment—are already documented in the schema. The tool description adds no parameter-specific semantics beyond restating that the lookup happens by username, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Get') and resource ('a single Threads user's recent posts') and names the lookup key ('by username'). It is clearly distinguishable from sibling tools such as threads_user_profile (profile data vs posts) and other platforms' user-post tools because it explicitly names Threads and post content.

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 states the context clearly: use this when you need one Threads user's recent posts by username. However, it does not name any alternatives or when-not-to-use cases, such as pointing to threads_user_profile for profile metadata or search_threads_users for user discovery, so the guidance is implied rather than explicit.

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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