Kopern

kopern_list_sessions

Read-only

Retrieve conversation sessions for an agent, displaying purpose, source, token usage, cost, and timestamps without incurring LLM cost.

Instructions

List conversation sessions for an agent. Shows purpose, source, token usage, cost, timestamps. No LLM cost.

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": {
      "agent_id": "<agent_id>"
    },
    "name": "kopern_list_sessions"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Max sessions to return (1-50). Default: 20
`agent_id`	Yes	The agent ID or name

Schema Changelog

Changes observed during successful MCP inspections.

Addedv2.0.5Apr 12, 2026

TDQS

A4.3/5.0

Behavior4/5

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

The readOnlyHint annotation already covers the non-destructive nature, and the description adds 'No LLM cost' and enumerates the output fields (token usage, cost, timestamps), which is useful behavioral context beyond the annotation. It does not describe pagination or sorting, but that is not critical for a 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences, front-loaded with the main action and then adding the return value summary and cost note. Every word earns its place.

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 list tool with a readOnly annotation and fully documented parameters, the description covers the output contents (purpose, source, token usage, cost, timestamps) and the no-LLM-cost behavior, compensating for the lack of an output schema. It is complete enough for an agent to select and invoke it correctly.

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?

Both parameters are fully described in the schema (agent_id and limit), so the description does not need to add parameter semantics. It adds no extra information about parameters beyond the schema, hence baseline score of 3.

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 uses a specific verb ('List') and resource ('conversation sessions for an agent'), and specifies the returned fields (purpose, source, token usage, cost, timestamps). This clearly distinguishes it from sibling tools like kopern_get_session, which presumably returns a single session.

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?

The description clearly indicates this tool is for listing sessions, implying it's the right choice when you need an overview of multiple sessions. However, it does not explicitly name alternatives or exclusion criteria, such as when to use kopern_get_session or kopern_get_usage instead.

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