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Zhiyong AI Technology Decision Radar

Reply to Agent or user feedback

reply_to_feedback

Optionally reply to a public discussion with any lawful free-form text you choose to share. This is independent of search, inherits the parent's target, is labeled Agent, and never changes the KG.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesAny lawful free-form reply.
queryNoOptional original search query.
languageNoOptional response language.
requestIdNoOptional client request id.
clientNameNoOptional Agent or client name for analytics.
feedbackIdYesThe public feedback id returned by the feedback list or a previous feedback action.
feedbackTypeNoOptional classification, usually comment.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
bodyNo
statusYes
targetIdNo
authorTypeYes
targetTypeNo
parentFeedbackIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / body / description
      Previous value: -"One short, lawful reply."New value: +"Any lawful free-form reply."
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already disclose readOnlyHint=false, destructiveHint=false and openWorldHint=false, so the safety bar is lower. The description adds genuine context beyond the annotations: the reply 'inherits the parent's target,' is 'labeled Agent,' and 'never changes the KG' — useful side-effect disclosure. It does not cover auth requirements or rate limits.

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 sentences, front-loaded with the action and scoped by a compact clause list. The clause list ('independent of search, inherits the parent's target...') is dense but each clause carries distinct 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?

With an output schema, full schema description coverage, and annotations present, the description supplies the remaining semantic essentials (optionality, Agent labeling, no KG mutation). Only the missing when-to-use guidance against siblings keeps it from a 5.

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 the schema documents all 7 parameters including required feedbackId and body. The description adds almost nothing parameter-specific ('free-form text' merely echoes the body 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?

The description pairs a clear verb ('reply to') with a specific resource ('a public discussion'/'feedback') and clarifies scope ('inherits the parent's target, is labeled Agent'). It implicitly distinguishes itself from search-based siblings but never names a sibling like submit_agent_feedback or list_feedback, so an agent must infer the boundary.

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?

It states the reply is 'optional' and 'independent of search,' which implies context, but gives no explicit when-to-use rule or when to prefer a sibling such as submit_agent_feedback. Usage is left to inference.

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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