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aytzey

io.github.aytzey/showagent

list_sessions

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Search local AI coding-agent sessions by provider, workspace path, or free-text query and return newest matches, so you can locate prior work before reading or converting a transcript.

Instructions

List local AI coding-agent sessions (Codex, Claude Code, Gemini CLI, Antigravity, OpenCode, MiMoCode, jcode, Pi) newest first. Filter by provider, workspace path substring, or free-text query over workspace and first/last user message. Use this to find past work on a topic before pulling a session in with get_transcript or convert_session.

Input Schema

NameRequiredDescriptionDefault
limitNomaximum sessions to return, newest first (default 25, max 100)
queryNocase-insensitive free text matched against the workspace path and the first/last user message
providerNoonly return sessions of this agent; one of the provider ids reported in results (codex, claude, gemini, antigravity, opencode, mimocode, jcode, pi)
workspaceNocase-insensitive substring the session's workspace path must contain

Output Schema

NameRequiredDescriptionDefault
totalYessessions that matched the filters before the limit was applied
sessionsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and openWorldHint=false, so safety and locality are covered without the description. The description contributes the result ordering ('newest first') and the provider enumeration, but says nothing about result volume, truncation, or what happens when filters match nothing. With annotations carrying the safety profile, the added behavioral context is real but modest.

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?

Two sentences, front-loaded with the identity of the resource and its ordering, followed by filters and routing. The long provider parenthetical is dense but earns its place by telling the agent exactly what sources are covered; nothing else is padding.

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?

An output schema exists, so return values needn't be spelled out, and the description covers what remains: scope, ordering, filterable dimensions, and where to go next. For a zero-required-parameter read-only list tool, an agent has everything needed to 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?

Schema description coverage is 100%, so all four parameters (limit, query, provider, workspace) are already fully documented with defaults and matching semantics. The description restates the filter dimensions (provider, workspace substring, free-text query) at a high level but adds no syntax, defaults, or edge-case behavior beyond the 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 names a specific verb and resource ('List local AI coding-agent sessions') and immediately scopes it with the concrete provider list and the 'newest first' ordering. It also differentiates itself from sibling tools by naming get_transcript as the follow-up for pulling a session's content, so an agent can tell the two apart without opening either schema.

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 states the intended use case explicitly ('find past work on a topic before pulling a session in with get_transcript or convert_session'), which gives a clear when-to-use and names the downstream alternative. It stops short of any when-not guidance or a contrast with resume_command, so it is strong but not exhaustive.

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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