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list_sessions

Lists all current recognition sessions with summaries, linked images, and iteration counts to review historical recognition records.

Instructions

查看当前所有识别会话的列表,包括每个 session 的简介、关联图片和迭代轮数。用于回顾历史识别记录。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_sessions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.3

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the shape of returned data (session summary, associated images, iteration count), which is genuinely useful. It does not state that the operation is read-only, whether results are paginated or sorted, or how large the list can grow — meaningful gaps for a zero-annotation tool, but not a serious misrepresentation.

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 short sentences: the first front-loads what the tool returns, the second gives the use case. No filler or repetition. It could be marginally tighter, but every clause carries 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?

For a parameterless list tool with no output schema, the description covers the essential question — what the list contains — and implies the purpose. Given the tool's low complexity this is nearly sufficient; only ordering, scope, and pagination behavior are left unstated.

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?

The tool accepts no parameters at all, so the schema (empty object, 100% coverage) leaves nothing to explain. The description correctly describes a parameterless listing operation and adds the return-content semantics instead of inventing input details.

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+resource (view the list of all current recognition sessions) and even enumerates what each entry contains: brief summary, associated images, iteration count. That is clearly distinct from the sibling tools (analyze_video, analyze_images, analyze_document), which perform analysis rather than listing history, though the description never explicitly contrasts itself with them.

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?

The clause "用于回顾历史识别记录" implies the usage context (reviewing past recognition records) but gives no explicit when-not guidance, no mention of ordering, pagination, or whether sessions are scoped to the current user or workspace. The reader can infer it is a retrospective listing tool, but no alternative is ever named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.