Zhiyong AI Technology Decision Radar

Show popular feedback

get_popular_feedback

Read-only

Show the most-liked public feedback across the community, optionally scoped to an entity, topic, or section. Each item has an optional replyAction for that thread. Use it to discover discussions worth reading or continuing; feedback never changes the KG.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum popular feedback items to return.
`offset`	No	Offset for reading the next page; check hasMore/nextOffset.
`language`	No	Optional response language.
`targetId`	No	Optional entity id, topic slug, or section id. If provided, targetType is required.
`targetType`	No	Optional scope type.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`scope`	No
`policy`	No
`hasMore`	No
`feedback`	Yes
`nextOffset`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 6, 2026

addedInput schema / properties / offset

Added value: +{
+  "default": 0,
+  "description": "Offset for reading the next page; check hasMore/nextOffset.",
+  "minimum": 0,
+  "type": "integer"
+}

addedOutput schema / properties / hasMore
```
Added value: +{
+  "type": "boolean"
+}
```

addedOutput schema / properties / nextOffset

Added value: +{
+  "type": [
+    "integer",
+    "null"
+  ]
+}

First observedSep 6, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description reinforces this with 'feedback never changes the KG' and adds useful output context: each item has an optional replyAction for the thread. It does not cover auth or rate limits, but those are not required given the annotation coverage.

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?

Three sentences, front-loaded with the core action and scope before the usage cue. Each sentence adds something useful, though the replyAction detail is minor enough that it could be trimmed without much loss.

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?

The tool has an output schema, so return values need not be described. The description covers purpose, scope, read-only behavior, and intended use. It is nearly complete for a simple read-only listing tool, with only the lack of explicit sibling routing keeping it below 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 already explains limit, offset, language, targetId, and targetType clearly. The description adds only a high-level scoping summary ('entity, topic, or section') that mirrors targetType. Baseline 3 is appropriate when the schema carries parameter semantics.

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 states a specific verb and resource: showing the most-liked public feedback. It also identifies the ranking criterion (most-liked) and optional scope, which distinguishes it from a generic feedback list. Sibling tools are not named explicitly, so it stops short of a 5.

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 gives clear intended usage: 'Use it to discover discussions worth reading or continuing.' That tells the agent when this tool is appropriate. It does not name exclusions or direct alternatives such as list_feedback, so it is not a full 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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