agent4.io

list_user_sessions

List one end user's sessions — metadata only: agent, title (AI summary), message count, tokens, timestamps.

**Message bodies are not returned.** Transcripts are rendered in the console: each session
carries a `console_url` that **deep-links straight to that conversation, auto-opened** (no
digging through the detail page when there are many), plus `user_console_url` to the user's
detail page as the general entry. Hand the link to the tenant — a human reads the original
there. Pagination: pass next_cursor back as cursor.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "uid": "<uid>"
    },
    "name": "list_user_sessions"
  }
}

Input Schema

Name	Required	Description	Default
`uid`	Yes
`limit`	No
`cursor`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 28, 2026

TDQS

A4.6/5.0

Behavior5/5

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

With no annotations, the description carries full burden. It discloses that message bodies are not returned, that console_url deep-links and auto-opens, that pagination requires passing next_cursor as cursor, and that links should be given to the tenant. This is exceptional transparency for a read-only list tool.

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?

The description is moderately long but every sentence contributes: scope, metadata fields, console link behavior, and pagination. It is front-loaded with the core purpose and uses bold formatting for emphasis. No filler or redundant clauses.

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?

Given the tool's simplicity (3 params, no nested objects) and presence of an output schema, the description covers all essential aspects: what it returns, what it doesn't return, how to access transcripts, and how to paginate. It is complete enough for an agent to select and invoke correctly.

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?

Schema provides no parameter descriptions (0% coverage), so the description must compensate. It explains cursor semantics via 'pass next_cursor back as cursor' and implies uid identifies the end user. Limit is not explicitly described but is self-evident with a default. It adds meaningful context beyond the raw schema.

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?

The description opens with 'List one end user's sessions' — a specific verb, resource, and scope. It explicitly notes metadata-only and distinguishes from sibling tools like list_end_users by targeting sessions for a single user. The purpose is unambiguous.

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 provides clear usage context: how to obtain the console_url and hand it to the tenant for human reading. It also describes pagination usage. However, it does not explicitly state alternatives or when not to use this tool, so it stops short of a perfect score.

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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