Skip to main content
Glama
kitepon
by kitepon

agent_models

Fetch official model and reasoning-effort options for Codex, Claude Code, Grok, or Cursor without running inference. Use the returned IDs and efforts in launch or configure calls.

Instructions

harnessが今返すmodelとreasoning effortの候補を、そのharnessの公式の一覧から取得する。promptもturnも送らず推論を消費しない。Codexはapp-server model/list、Claude Codeはstream-json initializeのmodels、Grokはagent stdio initializeのmodelState、Cursorはcursor-agent modelsを素のmodel IDとeffortへ分けたもの。返るidとeffortsはagent_launch/agent_configureへそのまま渡せる。取得不能はMODEL_CATALOG_UNAVAILABLE、形式異常はMODEL_CATALOG_INVALIDのエラーで返し、別の一覧へfallbackしない。remoteを付けると別端末のharnessの候補を返す。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoCLIを実行する作業ディレクトリ(絶対パス・任意)。project設定で候補が変わるharness向け
remoteNo別端末のAitermで実行する時のSSH接続情報。hostだけならssh_configの接続名として使う。Aitermは接続情報を保存・管理しない。passphraseは会話記録に残るため、ssh-agentかpassphrase_env(環境変数名)を推奨する。
harnessYes候補を取得するharness
include_hiddenNoCodexが一覧で隠すmodelも返す(既定false)。他のharnessには隠すmodelが無い

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelsYes
schemaYes
sourceYes取得に使ったharnessの公式の入口
effortsYes全modelのeffortの和
harnessYes
default_modelYesmodel省略時にharnessが使うmodel。一覧のIDで表せなければnull
adapter_effortsYesharnessの一覧には無く、Aitermのadapterが足したeffortと理由
harness_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.45.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it names the per-harness implementation paths, states that no inference is consumed, specifies the two error codes (MODEL_CATALOG_UNAVAILABLE / MODEL_CATALOG_INVALID), and guarantees no fallback to another list. It does not cover auth/permission needs for remote execution or timing/latency, so it falls short of a 5.

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-loaded with the purpose and the non-consumption guarantee, then details per-harness mechanics and error behavior. It is a dense single block rather than segmented, so some sentences are long, but each carries information that is not repeated elsewhere.

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?

An output schema exists, so return values need not be explained; the description still covers error behavior, remote scoping, and non-inference cost. Given four parameters including a nested remote object with SSH concerns, the description is close to complete, missing only notes on remote authentication expectations.

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?

Schema description coverage is 100%, so the baseline is 3, but the description adds real semantics beyond the schema: it explains what passing remote does (別端末のharnessの候補を返す), which the schema's remote description (SSH connection info) does not state. include_hidden's harness-specific behavior is already in 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?

States a specific verb (取得する) and resource (harnessが今返すmodelとreasoning effortの候補), plus the authoritative source (そのharnessの公式の一覧). An agent can distinguish this catalog-lookup tool from agent_launch/agent_configure 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 Guidelines4/5

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

It explicitly clarifies the alternative it is NOT (promptやturnを送らず推論を消費しない) and routes the agent onward by saying the returned id/efforts can be passed straight to agent_launch/agent_configure. No explicit 'use when X instead of Y' exclusion block, but the context of use is clear.

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