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chat_list_sessions

View all saved conversation sessions to resume work, manage session data, or audit token usage. Returns session metadata including timestamps and token counts.

Instructions

List all saved conversation sessions.

Returns a list of session metadata: session_id, creation timestamp, last-activity timestamp, cumulative token usage, and whether the session currently owns a spec.

When to use: Resuming prior work, cleaning up abandoned sessions, or auditing session token spend.

Behavior: Pure disk read — no LLM, no network. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: 'Pure disk read — no LLM, no network. Read-only.' This clearly indicates it's a safe, local operation with no side effects, though it doesn't mention performance characteristics like speed or potential limitations.

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 perfectly structured and concise. It begins with the core purpose, details the return format, provides usage guidelines, and ends with behavioral notes. Every sentence adds essential information without redundancy or fluff.

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 (0 parameters, read-only behavior) and the presence of an output schema (which handles return value documentation), the description provides complete context. It covers purpose, usage, behavior, and output structure adequately for this straightforward tool.

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 0 parameters with 100% schema description coverage, so the baseline would be 3. However, the description adds value by clarifying that no filtering parameters are needed ('List all saved conversation sessions'), which helps the agent understand this is a comprehensive listing operation without input constraints.

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 verb ('List') and resource ('all saved conversation sessions'), making the purpose specific and unambiguous. It distinguishes this tool from siblings like chat_create_session and chat_delete_session by focusing on retrieval rather than creation or deletion operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides usage scenarios: 'Resuming prior work, cleaning up abandoned sessions, or auditing session token spend.' This gives clear guidance on when to use this tool versus alternatives, though it doesn't name specific sibling tools as alternatives.

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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