Antwork

reply_to_comment

Reply, in public and at once, to a comment on a published post, as the account that posted it.

Only after the user approved this exact text. Comment ids come from get_post(post_id, include_comments=True); without comment_id it is a comment on the post itself, e.g. a link under the user's own post. On Mastodon start the text with the comment's mention so its author is notified. Held to the network's character limit. X, Mastodon, Bluesky and LinkedIn company pages take replies; other networks answer comments_unsupported with the reason.

Args: post_id: The published post the comment is on. text: The reply, exactly as the user approved it. comment_id: The comment to answer. Omit to reply to the post. workspace_id: Workspace ID or name. Optional if user has only one workspace.

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": {
      "post_id": "<post_id>",
      "text": "<text>"
    },
    "name": "reply_to_comment"
  }
}

Input Schema

Name	Required	Description
`text`	Yes
`context`	No	The user's underlying goal for this call, in one sentence without personal details. Used for product analytics only.
`post_id`	Yes
`llm_model`	No	The model identifier of the calling assistant, or "unknown". Used for product analytics only.
`comment_id`	No
`workspace_id`	No
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Output Schema

Name	Required	Description	Default
`_mcp_instructions`	No	Server-issued metadata for this conversation.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 29, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true) it discloses that the reply is public and immediate, sent from the account's identity, subject to the network character limit, supported on X/Mastodon/Bluesky/LinkedIn company pages, and that other networks fail with a comments_unsupported reason. It even adds a platform-specific formatting requirement (prefix the Mastodon mention so the author is notified).

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?

The action and its safety precondition are front-loaded in the first two sentences, and the Args block adds information rather than restating titles. The prose body is dense and slightly run-on in places (the Mastodon aside is embedded mid-sentence), but nothing is wasted.

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?

An output schema exists, so return values need not be explained, and the description covers identity, visibility, timing, platform support, error behavior and the origin of comment ids. Coverage of the 7-parameter surface is partial, but the omitted parameters are analytics-only and self-documented in the schema.

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?

With 43% schema description coverage, the description must compensate and largely does: post_id and text are clarified, comment_id is given both its source and its omit-to-reply-to-post semantics, and workspace_id is described as optional when the user has one workspace. The analytics parameters (context, llm_model, conversation_id) are left entirely to the schema.

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?

"Reply, in public and at once, to a comment on a published post, as the account that posted it" gives a specific verb (reply), resource (comment on a published post), visibility (public), timing (immediate) and acting identity. It is clearly separable from create_post, publish_post and update_post among the siblings.

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?

It states a hard precondition ("Only after the user approved this exact text") and tells the agent where comment ids come from via get_post(post_id, include_comments=True). It also explains that omitting comment_id replies to the post itself and that unsupported networks return comments_unsupported. It does not say what to use instead when a network is unsupported, keeping it just short of a 5.

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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