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publish_reply

Destructive

PUBLISH a reply to this review's public Google profile. This is a public, customer-visible action - call it ONLY when the user has explicitly approved this exact text. If Google refuses the request, the text is preserved in ReputeMap with a manual fallback (status 'manual_required') - words are never lost. Google also moderates replies: google_state 'pending' = it is checking the reply before showing it; status 'rejected_by_google' = it will not show it (policy_violation and detail say why) - write a different reply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesthe exact reply text the user approved
review_idYesUUID from list_reviews

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already flag destructiveHint=true and openWorldHint=true, and the description adds substantial context beyond them: the action is publicly visible, refused text persists in ReputeMap under 'manual_required', and Google moderation produces 'pending' and 'rejected_by_google' states with policy_violation detail. This is exactly the kind of outcome behavior an agent needs before calling.

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?

Front-loaded with the action and its public nature, then conditions, then failure modes. Every sentence carries distinct decision-relevant information with no repetition.

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?

For a 2-parameter mutation with no output schema, the definition covers approval precondition, external visibility, fallback persistence, and moderation outcomes — everything an agent needs to call it safely and interpret the result.

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 both parameters (text, review_id) are already documented, including the 'exact approved text' and 'UUID from list_reviews' notes. The description adds no syntax or format detail 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (PUBLISH) and resource (reply to this review's public Google profile) with clear scope, and the 'public, customer-visible' framing separates it from the draft_reply sibling without needing to name it.

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 an explicit precondition — call ONLY when the user has explicitly approved this exact text — plus guidance to write a different reply when Google rejects it. It stops short of naming draft_reply as the alternative for un-approved text, which is the one inference left to the agent.

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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