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Get tweet replies

get_tweet_replies
Read-onlyIdempotent

Get only the replies to a tweet, without the tweet itself or the tweets above it. Paginated.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tweetId": "<tweetId>"
    },
    "name": "get_tweet_replies"
  }
}

Input Schema

NameRequiredDescriptionDefault
cursorNoPagination cursor. Leave empty for the first page; pass the next_cursor from a previous result to get the next page.
formatNoResponse format (default simple). simple: compact JSON with flat camelCase tweets and users, about 60% fewer tokens. raw: X's full GraphQL JSON, only needed for fields simple leaves out (cards, polls, edit history, community notes).
tweetIdYesNumeric tweet ID.
max_charsNoMaximum characters of JSON to return (default 50000). Longer output is cut with a [TRUNCATED] marker. Lower it to save context, raise it if you need the full response.
rankingModeNoSort order. Default Relevance.
includePromotedContentNoInclude promoted replies (default false).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world, so the safety profile is covered. The description adds only 'Paginated', which is largely redundant with the cursor parameter, and says nothing about ordering defaults, page sizing, or how many replies come back per page.

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?

Two short sentences, zero filler, with the scope exclusion front-loaded before the pagination note. Nothing could be cut without losing information.

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

Completeness4/5

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

For a read-only list tool with a fully documented six-parameter schema and clear annotations, the definition is nearly sufficient. The remaining gap is default behavior detail such as default page size and sort order, though the schema's parameter descriptions already cover those defaults.

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 cursor, format, max_chars, rankingMode, and includePromotedContent all documented in the schema itself. The description contributes no additional parameter meaning, so the 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?

States a specific verb and resource ('Get ... replies to a tweet') and a precise scope exclusion ('without the tweet itself or the tweets above it'), which implicitly separates it from get_tweet_thread. It does not name the sibling tools it contrasts with, so an agent must infer the routing rather than read it.

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 exclusion phrase hints at when to prefer this over a thread fetch, but no alternative tool is named and no condition is spelled out. Usage is implied rather than stated, so the agent has to derive the choice from sibling names.

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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