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GrigoriLab

claude-mux-iterm

by GrigoriLab

list_sessions

List all active iTerm2 sessions to identify which Claude Code sessions are available for communication.

Instructions

List all registered active iTerm2 sessions.

Use this to discover which other Claude Code sessions you can communicate with.

Returns: List of active sessions with their task IDs.

Example: >>> list_sessions() ListSessionsResult( sessions=[ Session(task_id="task-a", ...), Session(task_id="task-b", ...), ], total_count=2, ... )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNoHuman-readable status message
sessionsNoList of active sessions
total_countNoTotal number of sessions
Behavior4/5

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

With no annotations provided, the description carries the burden. It discloses the return format via an example, mentions that it lists only active sessions, and indicates a list with total_count. It does not explicitly state that the operation is read-only, but the tool's name and 'list' semantics imply it. The example gives useful transparency into the result structure.

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 appropriately sized: a single clear summary line, a short usage note, and a structured example. Every sentence earns its place without fluff. The front-loaded main purpose makes it easy to scan.

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 simple zero-parameter list tool with an output schema, the description is complete. It explains what is listed, why to use it, and what the return looks like. There is no missing critical information for an agent to invoke and interpret the result.

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 has zero parameters, so the schema fully covers this aspect. The description does not need to add parameter details, and the baseline of 4 applies. The description's focus on the return value is appropriate.

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 clearly states the tool lists all registered active iTerm2 sessions, using the specific verb 'list' with a well-defined resource. It also explains the purpose ('discover which other Claude Code sessions you can communicate with'), which distinguishes it from sibling tools like register_session or send_message.

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 provides a clear context for when to use the tool ('Use this to discover which other Claude Code sessions you can communicate with'), implying it is the initial discovery step before communication. However, it does not explicitly mention alternatives or when not to use it, though the zero-parameter nature makes this less critical.

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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