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Reply in a business conversation

reply_to_business
DestructiveIdempotent

Send a customer reply in an open Direct conversation and notify the business. Use it after get_replies shows the business answered or asked something; to start a new conversation use send_to_business, and to answer a question during a live phone call use answer_call_question. Pass the thread_id that send_to_business returned and the reply text (1 to 500 characters); sign in as the original requester with direct:tasks, or supply the private thread_token instead. message_id is the retry key: reuse it unchanged when retrying. Returns the A2A {task} for the reply: read its state before telling anyone it was delivered. A delivered reply cannot be recalled and is billed the same way as a take_message task; closed conversations refuse replies. Example: thread_id='th_7c1', text='Thursday after 2pm works, thank you.', message_id='rep-1'.

Input Schema

NameRequiredDescriptionDefault
textYesThe customer’s reply to the business.
thread_idYesThe thread_id returned by send_to_business.
message_idNoYour id for this reply; reuse it unchanged when retrying.
thread_tokenNoThe private thread_token; required unless signed in as the requester who started the thread.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true and idempotentHint=true; the description goes further by saying the reply cannot be recalled, is billed like a take_message task, that closed conversations refuse it, and that message_id is the retry key to reuse unchanged. It also tells the agent to read the returned {task} state before claiming delivery, which is valuable behavioral context. Only gap: it doesn't say what happens on partial failure or how billing/side effects interact with a retried message_id, so it's strong-but-not-exhaustive rather than a full 5.

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 purpose, then routing, then parameters, then a worked example — every part earns its place. The parameter sentence is dense (thread_id, text length, auth, retry key in one breath) and could be split for readability.

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?

With no output schema, the description compensates by naming the return value (A2A {task}) and warning to read its state before asserting delivery. Combined with auth, billing, and closed-conversation constraints, an agent has what it needs; only failure-mode details are thin.

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 all four parameters are already documented; the description corroborates thread_id provenance (from send_to_business) and reinforces message_id as a retry key. It adds the auth choice (sign in as requester with direct:tasks, or supply thread_token) which is meaningfully beyond the schema text.

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?

States a specific verb and resource ('Send a customer reply in an open Direct conversation') and immediately distinguishes itself from send_to_business (new conversation) and answer_call_question (live phone call). An agent can route correctly without opening any schema.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('after get_replies shows the business answered'), names two alternatives with the conditions that select them, and adds a prerequisite-style constraint that closed conversations refuse replies.

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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