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codex-subagent-mcp

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List Codex models

list_codex_models
Read-only

Discover available Codex models and their reasoning-effort levels before delegating a task. Reads the installed CLI catalog to help you choose a model explicitly.

Instructions

List the Codex models available on this machine, with the reasoning-effort levels each one supports. Read from the installed Codex CLI, with a warned static fallback if its catalog cannot be read. Call this before codex_delegate when choosing a model explicitly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refreshNoBypass the cache and re-read the catalog from the CLI.
working_dirNoAbsolute directory to read the catalog in. A project you have trusted in Codex can set its own catalog, so pass the directory a delegation would use. Defaults to this server's own.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.0
    • addedInput schema / properties / working_dir
      Added value: +{
+  "description": "Absolute directory to read the catalog in. A project you have trusted in Codex can set its own catalog, so pass the directory a delegation would use. Defaults to this server's own.",
+  "type": "string"
+}
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark the tool read-only, and the description adds useful behavioral context: it reads from the installed Codex CLI and has a 'warned static fallback' if the catalog cannot be read. This goes beyond the annotation in a meaningful way, though caching behavior is left to the schema.

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?

Three sentences, each earning its place: the core purpose, the fallback behavior, and the usage guidance. It is front-loaded with the essential information and contains no filler.

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 simple read-only listing tool, the description covers the key context: what is listed, where it is read from, the fallback behavior, and when to call it. It does not describe the return format, but no output schema exists and the purpose makes the return shape largely predictable.

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 the schema fully documents both parameters. The description does not add parameter-level meaning beyond the schema, which makes the baseline 3 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 names a specific action ('List'), a precise resource ('Codex models available on this machine'), and additional detail ('reasoning-effort levels each one supports'). It also distinguishes itself from a sibling by pointing to codex_delegate, so an agent can tell why this tool exists.

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 gives explicit usage context: 'Call this before codex_delegate when choosing a model explicitly.' It clearly states when the tool should be used, though it does not name alternatives to avoid or describe when not to use it.

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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