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list_agent_sessions

List captured AI coding agent sessions in reverse chronological order to identify recent work or which session a transcript came from. Shows capture coverage and token usage; use next_offset to page.

Instructions

List AI sessions captured from an agent's own transcript (Codex, Claude Code, OpenCode), newest first. Start here when the question is 'what session was this' or 'what work happened recently' and the agent's transcript was captured. Use find_agent_session instead when only the shell commands were recorded, and search_commands when you want individual commands regardless of which session ran them. Includes capture coverage and recorded token usage; unknown usage is not zero. No transcript paths are exposed. Follow next_offset for more results. Times are epoch milliseconds UTC.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses that capture coverage and token usage are included, that unknown usage is not zero, that no transcript paths are exposed, that next_offset continues the result set, and that times are epoch milliseconds UTC. These are non-obvious behavioral facts an agent would otherwise have to guess.

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?

Front-loads the purpose and routing guidance in the first two sentences, then appends caveats. It is dense with useful facts, though the trailing clauses (coverage, tokens, paths, offset, timezone) read as a list rather than fully organized prose.

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 list tool with no output schema, the description covers routing, result contents, pagination, and time encoding, so an agent could call it confidently. The only real gap is the uncharacterized limit/offset parameters, which the description neither documents nor maps cleanly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and neither parameter is explained: the description never says what limit controls or its 1-100 range, and it refers to 'next_offset' which does not match the actual 'offset' parameter name. The pagination hint is the only partial compensation, leaving the semantics of both params largely undocumented.

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?

States a specific verb+resource ('List AI sessions captured from an agent's own transcript') plus the supported sources (Codex, Claude Code, OpenCode) and ordering (newest first). It explicitly distinguishes itself from find_agent_session and search_commands, so an agent can route correctly without opening any schema.

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?

Gives an explicit entry-point rule ('Start here when the question is what session was this / what work happened recently') and names two alternatives with the exact conditions that select them (shell-only recording → find_agent_session; individual commands → search_commands). Nothing is left to inference.

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