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get_tweet_replies_v2

Read-onlyIdempotent

Get replies to a tweet (v2). Up to ~20 per page. queryType: Relevance (default), Latest, or Likes.

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_v2"
  }
}

Input Schema

NameRequiredDescriptionDefault
cursorNoPagination cursor from a previous response next_cursor. Omit or "" for the first page.
tweetIdYesTweet id
queryTypeNoSort order. Default Relevance.

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds genuinely useful context with the ~20-per-page result size, but says nothing about rate limits, ordering guarantees, or what happens at the end of a result set.

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?

Two short sentences, front-loaded with the operation and followed by the practical page-size and sort details. The "(v2)" tag is the only element that doesn't earn its place, since it isn't explained.

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 simple read tool with full schema coverage and rich annotations, most of what an agent needs is present. The notable gap is the unexplained v1/v2 distinction against the sibling get_tweet_replies, which matters for correct tool selection.

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 all three parameters (tweetId, cursor, queryType) are already documented, including the enum values and default. The description's restatement of queryType options adds no meaning beyond the schema, 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") with a version marker, so the operation is unambiguous. However, it never explains how it differs from the sibling get_tweet_replies, leaving the agent to guess which version to call.

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

Usage Guidelines2/5

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

No when-to-use guidance is given: nothing says when to prefer this over get_tweet_replies, get_tweet_quotes, or get_tweet_thread_context. The only guidance is the queryType default, which is a parameter detail rather than usage context.

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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