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Social Media Data API: Posts, Profiles, Comments, Search and Mentions

Reddit post search

reddit_search
Read-only

Reddit Posts & Subreddit Search: search public Reddit posts by keyword, within one subreddit, or list a subreddit's newest posts. Per post the title, text, subreddit, author, upvotes, comment count, linked URL, time and permalink in the shared social schema; next_cursor gives the next page. Forum research and social listening. Bad input is free; not found or no match is not charged. Price: $0.02 per successful call, paid over x402 (USDC on Base); pass the payment in _meta["x402/payment"].

Input Schema

NameRequiredDescriptionDefault
qNoSearch text (1-200 characters). Give q, subreddit or both.
cursorNonext_cursor of the previous page.
subredditNoLimit to one community: a subreddit name: 2 to 21 letters, digits or underscores, with or without r/. Alone it returns the subreddit's newest posts.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare read-only and open-world, and the description goes well beyond them: exact cost ($0.02 per successful call), the x402 USDC-on-Base payment path via _meta["x402/payment"], and the billing rules that invalid input and no-match results are free. That is precisely the kind of non-schema, non-annotation context an agent needs before spending money.

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?

Front-loaded with capability and modes, then return payload, then cost. It is dense but every clause (fields, pagination, price, free-failure rules) carries operational weight; the payment mechanics sentence is long but necessary for a paid tool.

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?

With no output schema, the description compensates by enumerating the returned per-post fields and the pagination cursor. Combined with full param coverage and explicit cost/payment handling, an agent has everything needed to call this correctly.

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 coverage is 100%, so the schema already documents q, subreddit and cursor with constraints. The description adds only that next_cursor feeds the next page, which is marginal beyond the schema's own 'next_cursor of the previous page' wording. Baseline 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?

Names a specific verb+resource (search public Reddit posts) and enumerates all three operating modes: keyword search, single-subreddit filter, and listing a subreddit's newest posts. It does not explicitly distinguish itself from siblings like reddit_comments or social_search, but the resource scope is unambiguous.

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?

Gives clear context for use ('Forum research and social listening') and the mode-selection logic ('give q, subreddit or both' / subreddit alone returns newest posts). It stops short of naming alternatives — e.g. when to use reddit_comments for threading or social_search for cross-platform — so there are no exclusions.

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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