aiterm-mcp
Aiterm-mcp is an MCP server that provides persistent PTY terminals and launches/drives other coding-agent harnesses (Claude Code, Codex CLI, Grok CLI, Cursor CLI) inside them, so an AI can orchestrate other AIs programmatically without a human at the terminal.
Persistent terminals:
pty_open/pty_send/pty_read/pty_key/pty_close/pty_list/pty_observemanage tmux (POSIX) or psmux (Windows) sessions that survive server/client restarts.Nested interactive access: drive
ssh,docker exec, REPLs, or any TUI just by sending text into the persistent PTY.Agent orchestration:
agent_launchstarts a chosen harness (claude-code,codex-cli,grok-cli,cursor-cli) with independentmodel/reasoning_effort, returning asession_idyou steer withpty_send.Model & auth management:
agent_modelslists live catalog models/efforts;agent_authstarts/checks/cancels official CLI logins;agent_configurechanges model/effort in a running session.Approvals:
agent_approval(Codex) andclaude_approvalinspect and answer permission prompts under a digest-bound one-time contract.Durable Claude turns:
claude_turnissues/recovers correlated operations with structuredpending/completed/unknownstates.Completion delivery: parent agents (Codex/Claude Code/Cursor) auto-receive answers; other parents use the
wait_processreceipt for push-style, non-blocking waits.Token-reduced reads:
pty_readstrips controls, collapses repeats, and folds long output head+tail; optionalrtkreducers for git/grep/pytest/etc.5-layer completion detection: process exit,
marksentinel,untilmatch, quiescence, timeout — plus per-harness turn observation for agents.Remote execution: pass
remoteto run the same PTY/agent operations on another machine over SSH.Diagnostics: read-only factory readiness and parent-hook status via
diagnostics.Legacy aliases:
claude_agent,codex_agent,grok_agentremain as compatibility launchers.
Allows spawning and interacting with Composer agents via persistent terminal sessions, enabling AI-driven orchestration of Composer's coding capabilities.
From any MCP client, launch Claude Code, Codex CLI, Grok CLI, or Cursor Agent CLI through one harness API inside a persistent interactive TUI.
Aiterm
(日本語: README.ja.md)
Let your AI orchestrate other AIs. One
agent_launchcall selects the execution harness separately from its model and hands you a persistent session to drive. Cursor can run GPT, Claude, or Grok while Cursor still owns the session, hooks, and transcript.What it is: one persistent MCP terminal your AI drives — and can launch other coding agents into.
ssh,docker exec, a REPL, or another agent's TUI all nest inside that one terminal as just text you send in. The mechanism is deliberately plain — your MCP client drives the other agent's terminal turn by turn: no hidden protocol, no separate aiterm-owned shared-memory layer, no autonomous negotiation. Launched agents still read the normal project and harness memory/configuration that a direct CLI launch would use.No human at a terminal required. aiterm is driven programmatically over MCP, so an AI can launch and drive another agent with no one sitting in the terminal — from an orchestration loop, a CI step, or a cron job.
MCP = Model Context Protocol — the open standard that lets tools like Claude Code plug capabilities into an AI.
Built and maintained by Quo at kitepon.dev.
Install in your MCP client
検出したClaude Code・Codex・Grok・Cursorのユーザー設定へ登録する標準入口:
npm install -g aiterm-mcp@latest
aiterm-setup --jsonaiterm-setupは端末の依存準備、MCP経由の端末実行、登録と読戻しまでを一回で行う。
WindowsはwingetでPowerShell 7・Git for Windows・psmux、macOSはHomebrewでtmux、
Ubuntu/Debianはsudoとaptでtmuxを準備する。必要な公式package managerと実行権限は事前に必要。
他のLinuxでも既存tmuxを利用できるが、自動導入はunsupportedで停止する。
既存設定の他サーバーを保持し、JSON設定は変更前の.aiterm-backupを残す。
結果のstatusはready/unsupported/failed/restart_required。未検出のAIはnot_detectedとし、全AI未検出は成功にしない。
登録先はglobal packageのNodeとMCP入口の絶対パスで、npm一時cacheやsource checkoutは登録しない。
global packageは、npmの現在のglobal rootか、実行中のNodeの既定のglobal rootにあるものを指す。npmのprefixを利用者ごとの場所へ向けた環境でも、共通の場所へ導入したAitermを登録できる。
CodexとGrokは、登録が同じなら公式CLIで作り直さず、利用者が足した項目(待ち時間など)を保つ。
HomebrewのNodeは更新後も有効なoptのパスをMCP登録とCodexのhookに使う。旧版の登録でNode更新後に起動できなくなった場合も、更新後のaiterm-setup --jsonで修復できる。
更新後も同じ入口を実行し、MCP clientを再起動する。npm install自体はユーザー設定を変更しない。
公開JSONはschema: "aiterm.setup-result.v1"、全体のstatus、端末のbackend、
AI別のintegrationsと選択機能のcodex_steerを持つ。失敗時はreason_codeを付け、終了コードはreadyなら0、再起動待ちは3、それ以外は2となる。
MCP登録を利用者や他の製品が管理する環境では、aiterm-setup --hooks-onlyでClaude Code・Cursorの親配送hookだけを登録できる。
依存準備、端末の実動作確認、MCP登録、Codex Steerには触れない。登録済みなら設定を書き換えない。
結果はschema: "aiterm.parent-hooks-result.v1"、全体のstatus(ready/unsupported/failed)、AI別のhooks(configured/unchanged/not_detected/failed)を持つ。終了コードはreadyなら0、それ以外は2となる。
CodexへSteerを有効にする(macOS・Windows・Linux)
対話実行のaiterm-setupで「Aiterm単品」と「Steer付き」を選べます。無人導入では明示します。
aiterm-setup --json --codex-steer enable公式キューと公式hookを使い、実行中の親には同じターンの次の推論へ回答を渡し、終了後は同じ会話を自動再開します。 Codexの起動プログラムと通常のstdio通信は変更しません。hookの実行ファイルが失われてもCodexの起動・応答は継続します。 終了後の再開は公式キューの監視周期に従い、約10秒かかる場合があります。
aiterm-setupはCODEX_HOME/hooks.jsonへ専用のPostToolUseとStopを追加し、公式APIでその2件だけを承認・読戻しします。
他のhookや承認は保持します。選択と配送の所有記録は~/.config/aiterm-mcp/codex-parent-hooks/へ保存します。
同じ設定で再実行しても既存hookの順序を変えず、新たな再起動要求を発生させません。
WindowsのhookはPowerShell 7で実行します。更新後のsetupで、既存のAiterm hookコマンドも更新します。
既存の中継は新しいhookの確認後に解除し、保存していたCODEX_CLI_PATHを復元します。macOSの専用LaunchAgentも解除します。
移行前から動いているCodexがあればrestart_required(終了コード3)を返します。完全終了・再起動後に
aiterm-setup --codex-steer statusでreadyを確認してください。旧設定は移行を実行するまで維持します。
hookはAiterm自身の配送記録と本文が一致する回答だけを取り出し、利用者がキューに入れた入力は保持します。
取り出し中断や出力失敗はparent_deliveriesにunknownとCODEX_HOOK_DELIVERY_UNCONFIRMEDで現れ、本文を保存します。
自動再送はしません。長い回答はCodexの公式hook処理で抜粋と全文ファイルへの参照になる場合があります。
解除・hook未対応の旧版への巻き戻し前はaiterm-setup --codex-steer disableを実行してCodexを再起動してください。
公式Codex Desktop(macOS・Windows・Linux)の同梱CLIを先に使い、Desktopが無い端末では通常のCodex CLI(公式キュー・hookに対応する0.154以上)を使います。
When a Desktop update moves the bundled Codex CLI, Aiterm finds it again at use time and updates its configuration. If it cannot, it returns CODEX_DESKTOP_BINARY_MOVED; start Desktop and rerun setup.
Aiterm単品の公式キュー配送は従来どおり利用できます。
No clone or build is required. Each client launches the published package with:
npx -y aiterm-mcpRequires Node.js ≥ 18 and a supported multiplexer backend: tmux on POSIX or psmux 3.3.8+ on native Windows. Driving Codex also requires the Codex CLI to be installed and authenticated.
Claude Code
Add it for your user account:
claude mcp add --scope user --transport stdio aiterm -- npx -y aiterm-mcpOr commit this as a project-scoped .mcp.json:
{
"mcpServers": {
"aiterm": {
"command": "npx",
"args": ["-y", "aiterm-mcp"]
}
}
}Claude Desktop
Add this server to claude_desktop_config.json:
{
"mcpServers": {
"aiterm": {
"command": "npx",
"args": ["-y", "aiterm-mcp"]
}
}
}Cursor
Save this as .cursor/mcp.json for the project, or ~/.cursor/mcp.json globally:
{
"mcpServers": {
"aiterm": {
"command": "npx",
"args": ["-y", "aiterm-mcp"]
}
}
}Ownership boundary: this repository owns installation, configuration, persistent PTYs, agent sessions, state/schema/migrations, diagnostics, recovery, updates, and releases. It can be cloned and operated on its own using this README and the product docs. dotagents optionally integrates Aiterm into the wider factory—host wiring, cross-product compatibility, and aggregate acceptance—but does not control Aiterm and is not a runtime dependency.
Measured, not claimed: in the recorded 203-test benchmark, a pty_read puts ~7.1× fewer tokens in your context than the raw log — and the pass/fail verdict survives the fold. → When to reach for it vs. the built-in shell
18 tools: seven PTY tools — pty_open / pty_send / pty_read / pty_key / pty_close / pty_list / pty_observe — to open, drive, read, and observe one persistent terminal; one canonical agent launcher, agent_launch, which selects claude-code, codex-cli, grok-cli, or cursor-cli as the execution harness; three deprecated launcher aliases kept for migration; agent_models; agent_configure; agent_auth; agent_approval; claude_turn; claude_approval; and diagnostics. The backend is tmux on POSIX and psmux on native Windows, so sessions survive even if the MCP server or the AI client restarts.
v0.28.0 separates the execution harness from the model. The harness owns the agent loop, authentication, hooks, session, and transcript; model is what that harness runs. Cursor Agent CLI can therefore select GPT, Claude, or Grok without changing the completion contract from Cursor hooks to another harness's. Composer is one of Cursor's models, not a harness and not a Grok model: use harness: "cursor-cli", model: "composer-2.5-fast" (or composer-2.5). The old launcher tools are thin compatibility aliases over the same implementation.
v0.25.2 stabilizes repeated in-place configuration changes, including Grok 4.6. If Grok Build
1.0.3 redraws before its /model success notice can be observed, aiterm confirms the requested model/effort
from the persistent footer when that state was absent before the command. Callers do not retry, restart, or
round a failure into success; explicit grok-4.6 launch and configuration still pass the live catalog check.
v0.25.0 gives Grok and Composer the same shared launcher controls. Their launchers now pass
reasoning_effort, enforce write_scope: "read-only" with --sandbox read-only, and support
in-place model/effort changes through agent_configure. Before creating a PTY, aiterm checks an
explicit Grok/Composer model—and Composer's default model—against the live grok models catalog.
An unavailable model fails visibly instead of letting the harness CLI fall back to another model.
Composer has since left the Grok CLI and is now one of Cursor's models.
v0.24.3 forwards explicitly selected launcher environment variables from the current MCP process.
Pass variable names in env_vars; aiterm reads their current values at launch and injects only the
present ones into that agent. This works even when the persistent multiplexer server predates the MCP
process, so a stale backend-server environment cannot erase per-seat identity or workflow variables.
It also recognizes Codex v0.147's optional fast token in long-lived model/effort footers, keeping
agent_configure available on an idle medium fast · session without redraw, retry, or restart.
v0.24.2 keeps in-place configuration working in long-lived Codex sessions. Once the startup header has scrolled out of the captured pane, aiterm recognizes Codex by its persistent model/effort footer together with the input prompt. An idle session is therefore configured directly; callers do not need to redraw the TUI, retry, or restart the agent.
v0.24.0 adds in-place agent configuration. agent_configure uses each harness's
native controls to change the model and/or reasoning effort of a running Codex or Claude
session while preserving its PTY, harness session, and conversation context.
v0.23.0 adds a local, cross-harness portable fork. Pass throughline_source_session
with a mission in prompt to any launcher, and aiterm asks the locally installed Throughline
for that session's read-only handoff context before creating the PTY. The exact returned memory
is prepended to the mission without moving or copying the source session's database ownership.
If Throughline is missing or returns an invalid/empty result, launch fails visibly with no clean
fallback. Omitting the field preserves the ordinary clean launch.
v0.22.0 makes launched agents full project collaborators. All four launchers now use the
same normal HOME, working tree, harness home, project/user/local configuration, MCP servers,
plugins, skills, permissions, trust, memory, and session history as a direct CLI launch. Aiterm
isolates only its own per-launch completion correlation state. Every child is told that it is a
sub-agent and receives its parent session, delegation depth, lineage, and
delegation_allowed=true; a child may delegate further, while the lineage makes reflexive
self-copy loops visible and avoidable. The historical managed_completion receipt field remains
for API compatibility and means “completion correlation enabled,” not environment isolation.
v0.21.3 removes Codex Stop hooks from the completion path. Codex completion and
final-message attribution now come from the root rollout transcript's durable
task_complete.turn_id, observed after the dispatch byte boundary. A broken or stale
hook executable can no longer strand aiterm-wait. v0.21.0 added explicit
write_scope declarations for external-agent launchers; v0.21.3 also fixes their
structured launch receipts so a supplied scope and its enforcement status are retained.
v0.20.3 prevents concurrent
correlated Claude/Fable sessions from turning one broken login into many competing login
flows. Every new Claude launch verifies the
harness-owned shared credential store before creating a PTY, while healthy credentials
remain reusable across concurrent and repeated sessions. The v0.20 line also distinguishes
a non-blocking aiterm-wait --timeout 0 observation (running, exit 5) from a real timed-out
wait. The v0.19 line added the correlated Claude approval relay,
preserved multiline shell delivery, and extended factory diagnostics on native
Windows. As of v0.16/0.17 a parent agent never blocks on aiterm:
agent sessionへの送信は非ブロックdispatchであり、Codex/Claude Code親には回答本文を自動配送する。
それ以外の親はreceiptのprocess起動情報でaiterm-waitを実行する。
終了コードは0=done、3=timeout、4=closed、待機しない照会の5=runningを表す。
Factory diagnostics and the local runtime-error store collect only when
canonical dotagents config explicitly sets collection.enabled: true;
collection is off by default and performs no network I/O. It ships via
tag-triggered CI with npm provenance (OIDC Trusted Publishing); the GitHub
Release re-registers the Official MCP Registry entry.
Status: actively maintained · current public release v0.57.2 · runs on Linux · WSL2 · macOS · native Windows (tmux on POSIX, the tmux-CLI-compatible psmux on native Windows — no WSL required) · MIT · see the CHANGELOG.
Update and rollback
The npm package is the standalone distribution; dotagents is not involved. For a global install,
update with aiterm-update. It reinstalls the requested version into the same npm prefix, then reruns the new version's
aiterm-setup --json to re-register and re-verify.
aiterm-update # this machine to latest
aiterm-update --host rabbit --host win-test # this machine and SSH hosts to the same version
aiterm-update --version 0.39.0 --check # report current and target versions without changing anything--host takes an ~/.ssh/config alias or host name; hosts are not stored. The version is resolved once on the calling
machine so every host lands on the same version. Hosts older than aiterm-update get it through npm first. When the
npm prefix is not writable, the result is permission_required with the command to run as an administrator. aiterm-mcp
servers that were already running keep the old code until their MCP client restarts (running_servers); tmux/psmux
sessions survive. Versions without aiterm-update use npm install -g aiterm-mcp@latest and aiterm-setup --json. To roll back, install a known-good immutable version,
for example npm install -g "aiterm-mcp@<known-good-version>", then restart the MCP client. setupを持つ版では再起動前にaiterm-setup --jsonを再実行する。For an npx configuration,
use aiterm-mcp@latest to update or replace it with aiterm-mcp@<version> to pin or roll back.
Check the CHANGELOG for state/schema compatibility before downgrading. Maintainer
release and artifact rollback are specified in the product-owned release procedure.
Related MCP server: claude-tmux
Why now
A lot of 2026's agent tooling is converging on orchestration: a lead model delegating a mechanical refactor to Codex, running Composer on a bulk edit while it reviews the diff, fanning one task across several agents to spare its own context window. All of those agents already live in a terminal. aiterm makes that terminal a first-class, MCP-native tool — so the model doing the orchestrating can spawn and steer the others without a human wiring up panes.
Built with Codex and GPT-5.6 for OpenAI Build Week 2026
aiterm predates Build Week, so the event work is kept visible in dated commits. During the submission window (July 14–16, 2026), I extended it with safe serialized delivery for long PTY input, correlated operation IDs and bounded result recovery, machine-readable launch and idempotent close receipts, and a hardened readiness gate that prevents prompts from disappearing during TUI startup redraws. The public comparison from the pre-event release is v0.12.2...main.
I used Codex with GPT-5.6 as an engineering collaborator: it inspected the implementation, challenged the API and recovery contracts, generated focused regression cases, and helped verify race, security, timeout, and malformed-event paths. I reviewed the diffs and test evidence and retained the final product and architecture decisions. At that Build Week checkpoint, the regression suite contained 262 tests covering normal operation as well as failure and recovery behavior; current release receipts live in the CHANGELOG and release ADRs.
ClaudeがAPIエラーや安全判定の拒否で終了した時は、Stop hookが発火しなくても次のpty_sendを新しいturnとして扱う。現在のturn開始後のエラー記録だけを確認し、過去のエラーで実行中のturnを解除しない。上流の拒否はエラーのまま返す。
Codexがサービスの誤りや通信の失敗でturnを打ち切った時は、完了待ちがdoneではなくerrorを返す(aiterm-waitはexit 7、親への配送はoutcome=error)。errorは応答の本文とURLを落とした1行の文で、Codexが記録した種類(internal_server_error・http_connection_failedなど)はerror_kindに載る。利用上限は今までどおりrate_limited。誤りで終わった後の席は、次のpty_sendを新しいturnとして受ける。
Two ways to use it
1. Drive SSH, containers, and REPLs in one persistent terminal — the primitive
This is the base, and it works with just the platform backend — tmux on POSIX or psmux on native Windows. pty_open grabs one local terminal; ssh host, docker exec -it x bash, or a REPL are just text you pty_send into it — once. Every command after that rides the same already-authenticated session. Session kind is never a tool-level distinction.
pty_open() → grab one local terminal
pty_send(id, "ssh 192.168.1.2") → authenticate once, inside that terminal
pty_send(id, "uname -a") → every later command rides the SAME session
pty_read(id, { wait: true }) → read the token-reduced output, completion detectedOrigin. I built aiterm for exactly this. Driving my homelab from Claude Code one command at a time meant every SSH command became its own connect → authenticate → disconnect: re-typing the passphrase and one-time code each time, short-lived sessions piling up, and eventually my own defenses (fail2ban, MaxStartups/MaxSessions, account lockout) locking me out — the security meant to stop attackers ended up stopping me. Holding one authenticated session fixes all three at once. That pain is why the persistent terminal exists; launching whole other agents inside it is what it grew into.
2. Launch other coding agents into that terminal — the orchestration flagship
The same primitive hosts another agent's TUI. agent_launch starts a selected execution harness inside a fresh persistent terminal and returns a session_id. harness names the component that owns the agent loop, authentication, hooks, session, and transcript; model remains an independent choice. The launched process sees the same project and user environment as a direct CLI invocation: normal configuration, MCPs, plugins, skills, permissions, trust decisions, memory, and history are not copied, filtered, or replaced. Aiterm adds only completion correlation and a non-user sub-agent context containing role=subagent, the parent session, delegation depth, lineage, and delegation_allowed=true.
起動結果には正規harnessを含むaiterm.agent-launch-result.v1が付き、旧providerは互換fieldとして残る。同じharnessはagent dispatch、aiterm-wait、agent_configure、pty_listにも載る。Codexは通常rollout、Grokは通常session event、Claudeはlaunch固有Stop hook、Cursorは通常agent transcriptのturn_endedを完了正本に使う。agentへの送信はpty_sendだけで行い、Aitermが送る時点で子の状態を見て振り分ける。Claudeは画面の実行中表示ではなくStopまで残るturnの印で判定する。実行中のturnへは差し込み(mode=agent_steer、新しいevent_cursorと配送は作らない)、それ以外は非ブロックdispatch(mode=agent_dispatch)で、harnessごとの完了境界を表す整数event_cursorを返す。Codex親は選択に応じて公式Steerまたはqueue、Claude Code親は公式非同期hookで本文を自動受信する。他の親はaiterm-waitを使う。CursorのsubmitはadapterがCLIのextended keyboard protocolへ変換し、送信本文がcomposerへ残る場合は明示errorにする。
Set require_agent:true on pty_send when the integration requires agent delivery. If the agent registration is missing, Aiterm refuses before sending any text and returns AGENT_SESSION_REQUIRED with an explicit unsent message. The default preserves ordinary PTY sends; combining it with force:true is rejected before sending.
pty_send to an agent session accepts an optional preface: one line placed before the text, so the message reads "preface, blank line, text". For a Claude Code session Aiterm enters the preface without the terminal's paste markers and pastes the blank line and the text in one paste. Claude Code wraps long pasted text in <pasted_content> and follows instructions inside it only where the user's own words outside the tags ask it to, so this keeps an integration's header (who the message is from) outside the wrapper. For Codex, Grok and Cursor sessions the three parts are joined and pasted as before. The preface must be a single line of at most 200 characters with no control characters, must not start with a symbol or whitespace, and must not contain @; otherwise Aiterm returns AGENT_PREFACE_INVALID and "文字列は送信していません。" before sending anything. It cannot be used with ordinary PTY sends, force:true, or remote.
Overlapping pty_send calls to the same agent session are handled one at a time. A later call picks its route only after the earlier one has been sent, so the result matches calls made in sequence (a call that overlaps the first send to a freshly started Claude Code session returns mode=agent_steer). It returns later by however long the earlier call waits for the session to accept input. If its turn does not come within the limit (60 seconds on POSIX, 180 seconds on Windows), Aiterm refuses before sending any text and returns AGENT_SEND_BUSY with an explicit unsent message. A lock left by a process that exited mid-send is cleared by the next send.
agent_launch and pty_send (to an agent session) accept an optional image: an array of absolute paths to image files (png/jpg/jpeg/gif/webp). Aiterm appends an attachment block to the prompt, and every harness opens the path with its own file-reading tool and sees the image; the caller never learns harness-specific attachment tricks. Invalid paths are rejected before anything is sent.
agent_launch accepts an optional write_scope: either "read-only" or a human-readable description of writable paths. Codex/Grok use --sandbox read-only; Cursor uses its official read-only --mode ask. A path description remains declaration-only because these CLI launch surfaces provide no equivalent path allowlist flag.
Grokの無人起動は公式--trustで指定された作業フォルダを信頼登録し、確認画面を完了してから初回promptを送る。この登録はGrok CLIの信頼ストアへ保存され、フォルダ内のhook・MCP・LSPにも適用される。read-only sandboxの制限は維持する。画面に残る完了済みhookの結果は実行中と判定しない。
Grokで終了済みターンのweekly-limitパネルが残っている場合、次の通常pty_sendがShift+Xで一度閉じ、入力受付を確認して今回の本文を送る。同じsessionと会話を保ち、receiptのpane_input_recoveryにgrok_rate_limit_dialog_dismissedを記録する。ターン未終了・harness不在はGROK_RATE_LIMIT_RECOVERY_BLOCKED、解除後の入力受付失敗はGROK_RATE_LIMIT_RECOVERY_FAILEDとなり、本文は未送信。上限の継続はrate_limitedとして返し、過去promptは再送しない。Grokの上限観測には現在の画面だけを使う。Claude Codeの上限は現在の画面の入力欄の下に出る知らせで、Codexの上限はturnを終えた記録(task_completeのcodex_error_info: "usage_limit_exceeded")で見分ける。pane logや道具の出力に残る上限の文字では判定しない。
When a Cursor pre-submit hook (beforeSubmitPrompt, or a Claude Code UserPromptSubmit hook that Cursor loads for compatibility) rejects the prompt, Cursor drops it and no turn or completion follows. Aiterm recognizes the rejection: an initial prompt returns initial_prompt=failed, and pty_send returns an error instead of a success receipt, both with USER_HOOK_BLOCKED and the hook's output. A rejection that comes after the 3-second start check is reported by the completion wait as outcome=error (aiterm-wait exit 7).
Grokがread-only sandboxの適用を拒否した場合、prompt送信時にGROK_SANDBOX_STARTUP_FAILEDとCLIの原因を返す。hookパスのシンボリックリンクなど、CLIが示した原因を設定の管理元で修正し、対象sessionをpty_closeして起動し直す。Aitermはsandboxを解除したりhookをコピーしたりしない。
この判定はGrok専用アダプターが所有する。初回prompt付きのagent_launchと通常のpty_sendで、入力受付待ち中に拒否を検出すると未送信のエラーを返す。promptなし・trust_project指定なしの起動応答は入力受付を保証しない。trust_project:trueでは入力受付まで確認し、startup.statusを返す。Grokのprivacy notice起動設定も同アダプターが所有する。実装の責務分担はDESIGNを参照。
Codex 0.155.1の「Approaching rate limits」model切替dialogは、通常のpty_sendとagent_configureで同じsessionのまま一時的な2. Keep current modelだけを選ぶ。入力受付を再確認してから本文または設定変更を進め、dispatch receiptのpane_input_recoveryにはcodex_rate_limit_model_switch_kept_currentを記録する。model切替と今後の表示抑止は選ばない。入力受付へ戻らなければCODEX_RATE_LIMIT_MODEL_SWITCH_RECOVERY_FAILEDとなり、本文・設定変更は未送信。このdialogはagent_approvalの対象ではなく、inspectはreason="rate_limit_model_switch"だけを返し、prompt digestとchoicesを出さない。
For a correlated Claude turn stopped at Do you want to proceed?, use claude_approval(action: "inspect", ...) to capture the active operation and SHA-256 screen digest, review the displayed command, then call respond with that exact digest and either approve_once or deny. The relay rechecks the operation and screen under the send lock, never exposes arbitrary input or permanent approval, keeps the active marker intact, and records a prompt-free owner-only receipt. pty_send(force: true) does not bypass this boundary.
agent_launch({ harness: "codex-cli", session_name: "codex1", cwd: "/repo",
prompt: "port test/legacy.py to vitest",
model: "gpt-5.6-sol", reasoning_effort: "high",
write_scope: "test/ only; no commit" })
→ { session_id: "codex1", … } # Codex now live in a persistent terminal
pty_read("codex1", { screen: true }) → read what it's doing (token-reduced)
pty_send("codex1", "also fix the imports it broke")
→ non-blocking dispatch; receipt carries event_cursor
# Codex/Claude Code親には回答が自動で届く。それ以外の親:
$ aiterm-wait --session codex1 --cursor <event_cursor> # never in the parent's foreground; exit 0=done, 3=timeout (not done), 4=closed, 7=error (turn aborted by an API error)
pty_read("codex1", { agent_transcript: true }) → collect the full answerThe canonical harness choices are:
| Launches | Notes |
| Claude Code CLI | Claude model and effort controls; correlated Stop hook |
| Codex CLI | OpenAI model and effort controls; durable rollout completion |
| Grok Build CLI | Grok model selected with |
| Cursor Agent CLI | GPT, Claude, Grok, or another Cursor catalog model; normal transcript completion |
A new terminal gets the environment of the MCP process that opened it (since 0.50.0, ADR 0081).
Values from another caller that happened to start the tmux server first no longer appear in it.
AITERM_SESSION_ID and AITERM_AGENT_* are not inherited; aiterm sets them per terminal. If a harness
passes only a few variables to its MCP process, the terminal has only those (Codex passes HOME, PATH,
SHELL, and TERM by default; forward more with env_vars under [mcp_servers.aiterm]).
env_vars is an allowlist of environment-variable names, not a name/value map. At launch,
aiterm reads each valid name from its current MCP process, shell-quotes present values, and places
them on that one harness launch command. Missing names are omitted; invalid shell variable names
fail before session creation. Only the named values can be read back with env_keys in pty_list.
Values do not enter the MCP tool arguments, but they are delivered through the
PTY launch command and retained in aiterm's per-session .lastcmd; the launched harness and other
processes with access to the same OS user may read them. Use this for non-secret seat identity and
workflow variables, not as a secret transport.
The selected harness CLI must be installed and authenticated. Aiterm resolves CLAUDE_BIN / CODEX_BIN / GROK_BIN / CURSOR_AGENT_BIN, then the documented default binary, then PATH. Cursor resolution deliberately uses cursor-agent, never the ambiguous agent name. Claude and Cursor authentication are checked before a PTY exists, so a failed preflight leaves no session. All harnesses use their normal harness-owned credential and configuration stores in place.
For Grok, Aiterm does not lock, inspect, or modify the credential. A non-empty inherited
GROK_AUTH_PATH must be absolute and exist; Aiterm passes it unchanged to Grok. Grok owns its
contents, permissions, and link handling. Absence of the default auth file is accepted only when
XAI_API_KEY is set.
Portable fork is optional. When throughline_source_session is present, prompt is the required
new mission and launch_operation_id cannot be combined with it. aiterm resolves Throughline via
THROUGHLINE_BIN and then PATH, runs throughline handoff-context --session <id> --json, and
places its returned context before a fixed separator and the mission. This route requires
throughline >= 0.9.0; throughline_supplement_file requires Throughline 0.10.8 or later. Aiterm appends
--supplement-file <path> without reading or interpreting the file. Throughline owns its project
binding, validation, and shared context budget. The route reads source memory without changing database session
ownership. No Throughline dependency is needed when the field is omitted.
Harness adapters translate model and reasoning_effort into each CLI's public controls. Explicit Grok models are checked against grok models; Cursor combines a base model such as gpt-5.6-luna with a separate effort such as high, checks the resulting current catalog ID, and uses Cursor's standard model picker for in-session changes. Missing models are errors, with no cache, retry, or fallback. Claude adds only launch-local Stop-hook settings, Codex reads its normal rollout store, Grok reads its normal session event/history, and Cursor binds its normal agent transcript with the launch ID. Pass an absolute cwd; ~ is not expanded.
There is no hidden protocol between agents: every launched harness is another user-visible persistent terminal session. The MCP client drives that TUI with ordinary PTY operations, and a human can attach to watch or take over.
Demo
Real captured output — each block below was just run through aiterm in this repo; the numbers, the elision marker, and every is_complete verdict are the tool's own, not mocked. The bracketed meta line is what pty_read appends; its labels are Japanese in the actual output, translated here for readability (the Japanese README shows them verbatim).
A long output folded head+tail — the middle is elided by the reducer, not by me (166 → 56 tokens):
→ pty_send("demo", "seq 1 150")
→ pty_read("demo", { wait: true })
← 1
2
3
⋮ (head runs to line 29 — abbreviated in this README)
… ⟨102 lines elided · full=true, or line_range="A:B"⟩ … ← the tool's own marker
⋮ (tail resumes at line 132 — abbreviated in this README)
149
150
[aiterm demo: 51 lines / ~56 tok (raw 152 lines / ~166 tok); 102 lines hidden] [is_complete=True via quiescent]A grep comes back exactly as grep printed it while it stays within rtk's caps (200 lines in all, 25 per file). Past a cap, the per-command reducer groups the hits by file and says what it left out:
→ pty_send("demo", "grep -rn session src/")
→ pty_read("demo", { wait: true, rtk: true })
← 550 matches in 23 files:
src/agent-resolver.ts:211:// …(long lines keep ~80 chars around the pattern)
…
src/remote.ts:268:session_id: session, agent_transcript: true, raw: true,
+4 more in src/remote.ts
+7 more files
[aiterm demo: rtk:grep applied / ~4286 tok (raw ~12546 tok)] [is_complete=True via quiescent]Nesting is just text you send in — here a Python REPL inside the same PTY (an ssh host, a docker exec -it … bash, or a launched coding-agent TUI nests exactly the same way):
→ pty_send("demo", "python3")
→ pty_read("demo", { until: ">>>" }) # nested prompt = "the inner shell is ready"
→ pty_send("demo", "print(sum(range(1_000_000)))")
→ pty_read("demo", { wait: true, until: ">>>" })
← 499999500000 [is_complete=True via until]The only edits to the captures above are the two ⋮ lines (a long head/tail run abbreviated for the README) and one over-long grep line truncated to fit — the ⟨…⟩ marker, the token counts, and every is_complete verdict are exactly what the tool printed. (Use until: ">>>" without a trailing space — the captured prompt is trimmed, so ">>> " would miss and fall through to timeout.) While nested, pass until (the inner prompt) or mark: true, because quiescence cannot fire there by design — see Completion detection and Known constraints. A human can attach to the same multiplexer backend and watch any of this live (see A human can watch).
First run (≈60 seconds)
aiterm-setup --jsonがreadyになったら、利用するMCP clientを再起動して接続を確認する。Claude Codeの場合:
/mcp # aiterm should show as connected, exposing 18 toolsYour first session — four calls, one persistent terminal:
pty_open() → { session_id: "t1", attach: "<platform attach command>" }
pty_send("t1", "echo hello") → command sent into the PTY
pty_read("t1", { wait: true }) → "hello" (token-reduced, completion detected)
pty_close("t1") → terminal releasedpty_close is idempotent and returns a structured closed / already_closed
receipt, so durable callers can retry the same session_id after losing the MCP response.
On Windows, closing a Claude Code session first asks Claude Code to exit on its own (Ctrl-C twice, then a wait of up to 4 seconds)
so that its SessionEnd hooks run; psmux stops a session without the hangup signal that tmux sends on POSIX. The session is stopped
afterwards either way.
That's it. The terminal in t1 is real and persistent — ssh, docker exec, a REPL, or a launched agent's TUI are just things that live inside it. To launch a worker agent instead, one call does it: agent_launch({ harness: "codex-cli" }) returns a session_id you drive with the same pty_read / pty_send.
Prefer a global install, or a different client?
# install globally, then register the command name
npm i -g aiterm-mcp
claude mcp add --scope user --transport stdio aiterm -- aiterm-mcpThis registers it in ~/.claude.json; you'll get an approval prompt the first time. For client-specific JSON, see Install in your MCP client.
Headless: no human at the terminal
Because an MCP client drives aiterm programmatically over stdio, everything above can run with nobody sitting at the terminal. Any MCP-capable orchestrator can call agent_launch — including a harness matching itself — then pty_read the result and act on it unattended. That makes aiterm a fit for exactly the places a human-driven terminal isn't:
Multi-agent orchestration — an orchestrator hands sub-tasks to Claude Code / Codex / Grok / Cursor harnesses, each in its own persistent session, and reads them all back. Composer is one of the models Cursor selects (
composer-2.5-fast).CI — a job step can spin up an agent, drive it, and tear it down.
cron — a scheduled run can launch an agent and collect its output.
The terminal is real and shared, so a human can jump in (A human can watch) — but nothing requires one to.
How it works
flowchart LR
AI["AI / MCP client<br/>(the orchestrator)"] -->|"pty_send · pty_observe · agent_launch · agent_models · agent_configure · agent_auth · agent_approval · claude_turn · claude_approval<br/>legacy launcher aliases · diagnostics"| S["aiterm-mcp<br/>stdio MCP · 18 tools"]
S -->|"pty_read<br/>token-reduced"| AI
S -->|"tmux / psmux<br/>send · capture"| P["persistent PTYs<br/>survive restarts"]
P -->|"ssh · docker · repl"| R["nested<br/>remote · container · REPL"]
P -->|"launches a fresh PTY per agent"| A["another coding-agent harness<br/>Claude Code · Codex CLI · Grok CLI · Cursor CLI"]One PTY is the only primitive. Everything else — SSH, containers, REPLs, and the launched agent TUIs — is just something interactive running inside a persistent terminal, driven with the same pty_send / pty_read. Each launcher opens its own fresh PTY. Because the PTYs live in tmux on POSIX or psmux on native Windows, sessions outlive the MCP server and the AI client.
When to reach for it vs. the built-in shell
Your MCP client already has a shell tool, and it wins on some jobs. aiterm wins on others. We measured both on the same commands in this repo, counting tokens the same way on each side (characters ÷ 4, aiterm's own estimator), so the comparison is apples-to-apples.
Start with the built-in tool for a light one-shot. git log --oneline -5 is one round-trip; aiterm is two — pty_send then pty_read — and that second round-trip costs more than a light command saves (~7 s vs ~13 s).
The second round-trip pays for itself once the output runs long, or the state has to outlive the call.
Command | Built-in shell | aiterm | Verdict |
| 1 call, ~7 s | 2 calls, ~13 s | shell (fewer round-trips) |
| ~4,292 tok | ~607 tok | aiterm (~7.1× fewer, verdict kept) |
| ~500 tok¹ | ~456 tok | tokens tie; aiterm keeps head and tail + |
| ~2,989 tok | ~1,096 tok | aiterm (~2.7×; long lines get clipped²) |
In the recorded 203-test benchmark the reduction is real and safe. The built-in tool drops the whole 223-line log — ~4,292 tokens — into context. aiterm folds its own capture of the run down to ~607:
[aiterm demo: 51 行 / ~607 tok (raw 223 行 / ~4292 tok); 172 行 hidden] [is_complete=True via mark]行 = lines; the meta line is quoted verbatim from aiterm's real output.
That is about 7.1× fewer tokens reaching the model, and the verdict survives the fold: the tail still carries ℹ tests 203 / ℹ pass 203 / ℹ fail 0. The reduction drops the noise and keeps the line you opened the log for. Wall-clock effectively ties, so on a run this long the extra round-trip is a small part of the total.
aiterm also holds state across calls. The built-in tool runs each call in a fresh shell, so cwd resets between calls and the environment doesn't carry. Send cd /tmp && export BENCH_VAR=hello123, then read it back in a second, separate call:
built-in shell → var= # empty; env dropped, cwd back at project root
aiterm → cwd=/tmp var=hello123 # one persistent PTY holds bothcd then set env then build, ssh once then run ten commands on the authenticated session, drive a live REPL or a launched agent's TUI turn by turn — one persistent PTY holds all of it. Reach for aiterm when the terminal has to remember something.
¹ Today's harness auto-offloads the ~192 KB dump to a file and previews only a ~2 KB head, so the token counts nearly tie; aiterm reports the accurate line count and lets line_range="A:B" pull any slice later, head or tail. ² The rtk grep reducer returns grep's output unchanged while it fits rtk's caps (200 lines, 25 per file). Past a cap it groups by file, keeps ~80 chars of each long line around the pattern, and folds the rest into +N more in <file> / +N more files; use the built-in tool when you need every full line of a large search.
vs. the alternatives
aiterm sits at the intersection of two families: terminal-driving MCP servers, and the newer "agents talk to each other through a shared terminal" idea (see Where aiterm fits). Here's how the axes line up — honestly, including where the others are strong.
aiterm-mcp | one-shot shell MCP(e.g. | terminal / SSH / tmux MCPs(e.g. | shared-tmux agent-to-agent(e.g. | |
Persistent session | ✅ tmux / psmux, survives restarts | ❌ new shell every call | ⚠️ varies | ✅ tmux |
SSH / containers / REPLs | nest with one | reconnect every command | ⚠️ often separate tools | ✅ tmux (human drives) |
Launch another agent in one call | ✅ | ❌ | ❌ | ⚠️ agents join a human-run tmux via a CLI + skills |
Headless (no human at a tmux) | ✅ MCP-driven, programmatic | ✅ | ⚠️ varies | ❌ built around a human in the tmux |
MCP-native (any MCP client) | ✅ one | ✅ | ✅ (they are MCPs) | ❌ tmux config + CLI + Agent Skills |
Token-reduced reads | ✅ per-command reducers | ❌ raw output | ⚠️ rarely | ❌ raw tmux |
Completion detection | 5-layer: exit / | n/a (blocks per call) | ⚠️ prompt-match, fragile | ❌ agent reads the pane |
Human can co-drive | ✅ shared socket / namespace ( | ❌ | ⚠️ varies | ✅ (its core model) |
Where aiterm fits
"AIs talking to each other through a shared terminal" is becoming its own category — and it's a genuinely good idea. The terminal is a universal interface every coding agent already speaks, so no bespoke agent-to-agent protocol is needed; the shell is the shared surface. smux (by @shawn_pana) popularized this framing as a one-command shared tmux environment a human sets up, that agents then join via a tmux-bridge CLI and Agent Skills. It's good at the in-the-loop, shared-pane workflow it's built for, and it has real traction.
aiterm takes the same core insight — the terminal as the meeting point — and makes three deliberate, different choices:
Headless by construction. Because aiterm is driven programmatically over MCP, an AI can launch and drive another agent with no human sitting in the tmux — from an orchestration loop, a CI step, or a cron job. The shared-tmux tools lead with a human at the keyboard (their docs center on interactive pane navigation), so unattended operation isn't their native mode; aiterm's is.
MCP-native, not a workflow you adopt. aiterm is a stdio MCP server: one
claude mcp addline and it works as structured tools in any MCP client that speaks stdio (tested in Claude Code; Cursor, Cline, and Claude Desktop speak the same protocol and should work the same way). It doesn't ask you to adopt a tmux config, learn pane navigation, or install skills into your setup — the client already knows how to call tools.Launching an agent is one tool call — an orchestration primitive.
agent_launch({ harness: "codex-cli" })spawns Codex in a persistent terminal and returns a session you drive immediately. You don't arrange panes or paste between them by hand; the launch, the steering, and the reads are all tool calls the orchestrating model can make on its own.
On top of that sits a productized layer a raw tmux bridge doesn't have: token-reduced reads and 5-layer completion detection. None of this makes the human-in-the-tmux model wrong — it's a different, complementary bet on where the human is standing.
Tools
Session observation and startup
pty_open defaults to bash on POSIX and PowerShell 7 on Windows. Ordinary terminals and agents receive
AITERM_SESSION_ID. A terminal inherits the environment of the MCP process that opened it. Pass names in env_vars to register them on the session.
pty_list({ env_keys: ["JOB_OWNER"] }) returns only registered non-secret values in environment; unregistered and missing values are null.
Its aiterm.pty-list-result.v1 receipt contains observed_at and sessions, whose entries include session_id,
current_command, attached, width, height, harness, and environment. Existing text remains available.
pty_observe({ session_id, cursor? }) returns aiterm.pty-observe-result.v1 with exists, observed_at, state
(busy/idle/blocked/dead/missing/unknown), reason, pane_alive, and harness_alive. pane_process and harness_process
are separate identities. process_identity selects the harness for agents, or the unique child process-group leader
for an ordinary terminal, using the pane when no child leader exists. An identity contains pid, process_group_id,
started_identity, and argv_digest; unresolved identities are null. Windows PIDs are native and its process-group field
is null. Start identity uses POSIX LC_ALL=C ps lstart or Windows UTC ISO milliseconds; the argv digest is SHA-256 hex.
Pass activity.cursor into the next observation to obtain output_changed and cpu_delta_seconds; first observations and
recreated panes return null differences. cpu_seconds is the current subtree's cumulative CPU. If a process disappeared
between observations, the delta covers only observed increments and cpu_delta_complete is false.
background_cpu_seconds, background_cpu_delta_seconds, and background_cpu_delta_complete apply the same measurement
only to descendants created at least 60 seconds after the pane, excluding startup MCP processes. token_hint is the latest
displayed token count or null. Callers do not need raw argv or pane-text parsing.
Two fields tell a caller what closing an agent session would lose. activity.post_startup_process_count is the number of
processes in the session that did not exist when agent_launch finished startup (before the first prompt), so background work
started in the first minute is counted too. Two kinds of process are not counted: Codex's own codex-code-mode-host helper, and
the direct children of an mcp-lazy relay (the MCP server it starts on first use and its wake predicate). What runs below them
is counted. A startup process that the harness restarted (a process with the same parent and the same arguments as a startup
process that has exited, such as a reconnected MCP server) is not counted either, and neither are the processes Aiterm itself
starts to read the process table (ps, or PowerShell and its console host on Windows). pending_child_deliveries
is the number of sub-agent results this session is still waiting for as a parent, whoever the caller is. Both are null when
Aiterm cannot tell (ordinary terminals, agents launched by 0.48.0 or earlier for the process count, or an unresolved harness
process), and may be absent when a remote host runs an older Aiterm. Treat null or absent as unknown, not as zero.
Another product that needs to deliver an answer to a Codex parent can ask Aiterm with aiterm-parent-delivery instead of registering its own hooks.
Aiterm's registered hooks and the official queue deliver it. codex verify --thread <uuid> checks the parent and reports configuration in steer
(enabled: the hooks are registered and trusted and the parent started after they were installed; disabled: official queue only, so the text arrives
after the turn ends). codex submit --thread <uuid> --delivery <uuid> --text-file <file|-> hands the text over once and returns the queue's acceptance id.
codex state --thread <uuid> --delivery <uuid> reports how it arrived (hook:"emitted" with turn_id: the hook put the text into that turn; queued:
whether it is still in the official queue). Each result is one JSON line; failures are {ok:false, code, message, outcome_unknown} with exit 1, and a
reused delivery id is refused with PARENT_DELIVERY_DUPLICATE. Only Codex parents are supported. aiterm-setup records the command's location in
~/.config/aiterm-mcp/delivery-provider.json. Node products can call it through aiterm-steer-delivery (0.3.0 or later), for example
submitCodexParentAnswerViaAiterm.
When Aiterm is registered behind a relay that starts the MCP server only on first use, a sleeping server cannot take over the
deliveries of an owner that has exited. aiterm-delivery-wake --parent <codex|claude|cursor> answers whether one needs to start:
exit 0 when an exited owner still holds a delivery for that parent kind, exit 1 otherwise, exit 2 for bad arguments. It prints
nothing, starts no child process, and marks the delivery so that only one of the seats running the same check starts its server
(the mark is retaken after 30 seconds if nobody took the delivery over). For mcp-lazy, pass it as the wake predicate with the
same environment as the server:
MCP_LAZY_WAKE_COMMAND='["/absolute/path/to/node","/absolute/path/to/aiterm-mcp/dist/delivery-wake-cli.js","--parent","claude"]'.
Owner start times are checked through /proc on Linux; elsewhere an existing PID is treated as a live owner.
aiterm-setup does not rewrite a registration that wraps the same server in the mcp-lazy relay. When the registered command is an executable whose name starts with mcp-lazy and its args are the direct registration's command followed by its args (relay flags before -- are allowed), the Claude Code, Codex, Grok, and Cursor registrations are left as they are. If the wrapped server path differs, setup writes the direct registration.
agent_launch({ harness, cwd, trust_project: true }) completes known workspace, project-hook, and project-MCP startup
consent even without a prompt, then verifies input readiness and harness liveness before returning startup.status="ready".
For Claude Code's first-run text-style menu, it confirms the item already selected on screen before continuing startup.
If the CLI then requests an account login method, the launch reports vendor_onboarding_required; complete that choice in the official interactive Claude Code CLI.
The input-readiness wait is 30 seconds. Only when it expires while the agent has not drawn anything yet (a busy host), the launch
waits up to 50 seconds from startup. If nothing is drawn by then, it still returns initial_prompt=not_sent and keeps the session.
A prompt-free launch without this option retains startup.status="not_checked". initial_prompt.status distinguishes
not_requested, not_sent, submitted_unconfirmed, and started. Failure responses retain structured session information.
WindowsのCodexもhook確認を認識し、npm shim経由の起動を一つのharnessとして識別する。
submitted_unconfirmed (the prompt left the composer, but the turn start was not observed within the confirmation window) is
not a tool error: isError is not set, the text carries an unconfirmed-start note, the session is alive and the parent
delivery stays registered. Do not resend an unconfirmed prompt or relaunch the agent; observe with pty_observe or wait
using its returned cursor.
For a live Codex approval, inspect with agent_approval({ action: "inspect", session_id }), review prompt and choices,
then respond with observed_prompt_digest and approval_choice (approve_once or deny). Unknown or changed dialogs return
status="blocked" and isError:true without sending input. Permanent approval is not exposed. Correlated Claude approvals
continue to use claude_approval.
Tool | Role | Key args |
| Open one terminal and return a |
|
| Send text. On an agent session Aiterm picks the route when it sends: if the child's turn is running, it steers the text into that turn ( |
|
| Read output, token-reduced (incremental by default) |
|
| Send a control key |
|
| Close idempotently; return |
|
| Text and structured session list, with explicitly requested non-secret environment values |
|
| Pane/harness liveness, native process identity, state, and activity |
|
| Canonical agent launch; harness and model are independent |
|
| 公式CLIの認証を開始・確認・取消し、公式URL・device code・入力待ちを返す |
|
| List the models and reasoning efforts a harness offers now, read from that harness's own catalog without sending a prompt |
|
| Inspect a Codex approval and submit a one-time approval or denial |
|
| Deprecated compatibility aliases ( | legacy launcher arguments |
| Change model/effort in a running Claude, Codex, Grok, or Cursor session without restarting it |
|
| Issue (dispatch-only) or recover one correlated Claude operation |
|
| Inspect or answer the current correlated Claude approval prompt |
|
| Read-only factory readiness as machine-readable JSON | (none) |
diagnostics never starts a PTY or agent. It reports package version, MCP call readiness, a read-only PTY-list summary, bounded runtime-error-store status, and optional vendor-launcher availability. It deliberately excludes paths, environment values, credentials, command text, PTY output, and raw logs; normal unset optional dependencies are not_applicable, while an indeterminate probe is unverified.
The result carries two text items. The first is the factory JSON described above (aiterm-mcp.factory-diagnostics.v1), whose fields are fixed. The second reports the parent-delivery hooks (aiterm-mcp.parent-delivery-diagnostics.v1): a status (ready / setup_required / not_applicable / unverified) and reason_code for Claude Code and Cursor, plus caller_status for the calling client. When caller_status is setup_required, agent dispatch from that client is rejected; run aiterm-setup. Hook status is not folded into overall in the first item.
Local runtime error snapshot
snapshotのproduct_versionは各recordの最終実発生時の版を表す。store v2は旧v1を読み取り、単発記録の版を保持し、複数回の旧集約の版はunknownにする。読取りでは状態JSONを書き戻さず、次のロック内更新でv2を保存する。consumerを先に更新し、旧writerの終了後に新writerを使う。v2保存後の旧版への切替は、製品のバックアップ復元を伴う。
aiterm-runtime-errors snapshot exposes a machine-readable, product-owned local snapshot for the dotagents factory adapter. Collection is fail-closed unless the canonical dotagents factory-reporter config is schema-exact, its host profile matches the executing OS, and it contains the JSON boolean collection.enabled: true; reporting fields are schema-validated but endpoints and credential files are never contacted, and the store performs no network I/O. The only accepted observations are three fixed codes owned by the core boundary (PTY dependency, persistence, and optional vendor launcher). Stored data is limited to fixed templates and aggregate metadata (SHA-256 fingerprint, count, first/last seen, status, and monotonic sequence); exceptions, stderr/stdout, stacks, prompts, terminal/transcript/event bodies, paths, and arbitrary context cannot enter the API. Persisted JSON is revalidated with exact top/record fields and a recomputed fingerprint before explicit DTO projection.
Consumer flow is aiterm-runtime-errors snapshot, then aiterm-runtime-errors ack --cursor N after durable ingestion. Operators can use resolve|reopen --fingerprint SHA256. MCP collection and diagnostic reads run in timeout-bounded child processes, so a FIFO or stalled filesystem cannot block terminal work; child failure emits only the fixed store diagnostic. Store mutation uses a bounded bakery ticket queue: every waiter owns a never-reused ticket containing PID, process-start identity, and an owner token, so dead owners are removed by unique filename without fixed-path reclaim ABA. The queue deadline measures lack of progress by the same head owner, not total wait behind healthy predecessors; normal polling uses the native process-liveness check and validates process-start identity only when a blocker stalls. Worker deadlines use forced termination so a SIGTERM-ignoring child cannot mutate state after timeout. POSIX state is atomically replaced under $XDG_STATE_HOME/aiterm-mcp/ (default ~/.local/state/aiterm-mcp/) with owner/mode rechecked on every read. Windows native uses %LOCALAPPDATA%\aiterm-mcp\; each DACL is rebuilt and read back as one non-inherited FullControl ACE for the current SID. Windows path/DACL/timeout behavior is covered by pure tests in this change; no new Windows integration success is claimed.
Reporting to BugHub is off by default. Aiterm sends runtime errors nowhere unless both hold: the user ran
aiterm-runtime-errors reporting enable, and a credential file placed by the BugHub owner exists
(~/.config/bughub/product-credentials/aiterm-mcp.json, or %LOCALAPPDATA%\bughub\product-credentials\aiterm-mcp.json on Windows;
it is read only when it is a regular file readable by its owner alone). The destination comes from that file. The payload is the
cumulative error codes, counts, first/last timestamps, versions, severity, and resolution marks; prompts, paths, and stacks are neither
stored nor sent. A separate process does the sending, never the MCP process, and there is no polling: a report is attempted when an error
is recorded, when a record is resolved or reopened, and when the MCP server starts (only while something is unreported, at most once per
hour), or on aiterm-runtime-errors report (once, at most once per minute). A record becomes acknowledged only after the response
signature is verified; otherwise the next attempt resends the then-current totals. aiterm-runtime-errors reporting status shows the
switch, the credential state, the unreported count, and the last attempt; reporting disable turns it off. Enabling reporting also
enables collection on that host.
Interactive agent harnesses
agent_launch starts a selected harness's interactive coding-agent TUI inside a fresh persistent PTY and returns its session_id. The harness owns the agent loop, authentication, hooks, session, and transcript; model is independent. The TUI is a full-screen app, so read it with pty_read({ screen: true }) for the rendered view.
agent_configure({ session_id, model?, reasoning_effort? }) changes a running Claude, Codex, Grok, or Cursor TUI through the harness's standard controls, preserving the PTY and conversation context.
agent_auth({ harness, action:"start"|"status"|"cancel", session_id?, cwd?, env_vars?, relogin? })は、各harnessの公式CLIで認証を進める。Claudeはclaude auth login、CodexとGrokはlogin --device-auth、CursorはNO_OPEN_BROWSER=1 cursor-agent loginを使い、資格情報は各CLIだけが保存する。Aitermは資格情報を読取り・copy・編集せず、独自OAuthも実装しない。remoteは他toolと同じ標準対応。
startは、公式の状態が認証済みなら何も起こさずauthenticated(session_id:null)を返す。relogin:trueを付けると、認証済みに見えても公式ログインを開始し、session_id付きの結果を返す。別のアカウントへ入り直す時と、ログインの期限切れを状態から見抜けない時に使う。Aitermは資格情報を消さず、置き換えは公式CLIが行う。ただし、公式CLIがログインを始めた時点で元のログインを消す事がある(Codex 0.160.0のcodex login --device-authは、始めた時点でauth.jsonを消す。途中でcancelしても戻らない)。Claude CodeとCursorは、途中でcancelすれば元の資格情報が残る(無効な資格情報で確認)。
status(sessionなし)は、公式CLIに今の状態を聞く。
harness | 聞き方 | 期限が切れたログイン |
Codex |
|
|
Claude Code |
| 見抜けない(公式の答えが |
Grok |
|
|
Cursor |
|
|
結果はaiterm.agent-auth-result.v1。statusはwaiting/authenticated/blocked/failed、session_id・url・user_code・input_required・messageを返す。startのsession IDを保存してstatusへ渡す。公式HTTPS URLと明示device codeだけを返し、CLIの生出力・token・OAuth callback codeを結果へ載せない。input_required:trueなら同じsessionのpty_read(screen:true)で公式画面を表示し、pty_send/pty_keyで人の入力を中継する。
Grokには公式認証status commandが無いため、session付きの確認は公式loginのexit 0を正本にし、session無しの確認はblockedを返す。他harnessは公式statusも照合する。Claudeは認証後の公式初回案内を同じsessionで進め、選択待ちはblocked/input_required:trueで返す。authenticatedは認証結果であり、agent_launchの起動準備完了は別途確認する。cancelは指定した認証sessionだけを閉じ、資格情報を削除しない。
PTYが消失した場合は、相関記録の有無にかかわらずstatusがfailed、cancelが既に終了・取消済みを示すblockedを返し、どちらもsession_id:nullとなる。保存したsession IDを解除してstartで再開始できる。生存中の通常PTYやharness不一致、記録の破損・読取り失敗はエラーを返す。
agent_models({ harness, cwd?, include_hidden? }) returns the model IDs and reasoning efforts the installed harness offers right now, so a UI can build its choices from the machine that actually runs the agents. It reads each harness's own catalog and never sends a prompt or starts a turn:
| Source | Notes |
| App Server | Per-model efforts and default effort. |
| stream-json | Hooks and MCP servers are disabled and the session is not persisted. |
|
| Per-model efforts; no session is created. |
|
| Split into base model IDs and the efforts Aiterm can append as |
The result (aiterm.agent-models.v1) is { harness, source, harness_version, default_model, efforts, adapter_efforts, models: [{ id, display_name, efforts, default_effort, hidden }] }. Every id and effort can be passed to agent_launch and agent_configure as is; efforts at the top is the union across models. An unavailable catalog is MODEL_CATALOG_UNAVAILABLE and a malformed one is MODEL_CATALOG_INVALID; Aiterm never falls back to another list. With remote, the catalog comes from the harness on that host.
{ "name": "agent_models", "arguments": { "harness": "grok-cli" } }
| Launches | Model behavior |
| Claude Code CLI | Claude catalog model; native effort controls |
| Codex CLI | OpenAI catalog model; native effort controls |
| Grok Build CLI | Grok catalog model |
| Cursor Agent CLI | Cursor catalog model, including GPT/Claude/Grok; effort uses model parameter override |
The selected harness CLI must be installed and authenticated. Use each product owner's official installer and updater; Aiterm does not distribute alternate CLI tarballs. For Cursor Agent CLI, use curl https://cursor.com/install -fsS | bash on macOS/Linux/WSL or irm 'https://cursor.com/install?win32=true' | iex on native Windows, authenticate once with agent login, and update with agent update; Aiterm invokes the unambiguous cursor-agent binary. Missing binaries, invalid model/effort values, unavailable Grok catalog models, and nonexistent cwd fail before a session exists.
Set throughline_source_session together with a non-empty mission in prompt to prepend
Throughline's read-only handoff context. This optional route requires throughline >= 0.9.0,
cannot be combined with launch_operation_id, and leaves the source session's database ownership
unchanged. Optional throughline_supplement_file is passed unchanged to Throughline and requires
throughline_source_session and Throughline 0.10.8 or later; Aiterm does not read or classify the supplement. Throughline is resolved through THROUGHLINE_BIN and then PATH; a missing or invalid
export fails before the PTY exists instead of silently launching clean.
When an agent's answer is longer than the on-screen tail (pane height ≈ 24 lines), callers recover it in full with pty_read({ agent_transcript: true }). It returns the most recently completed turn's final assistant message in plain text with no re-prompting. The existing human-readable content keeps its diagnostic suffix; machine callers read the answer alone from structuredContent.text in aiterm.pty-read-result.v1. Claude reads the bounded owner-only result captured by the launch-correlated Stop hook and verifies its digest/byte count; it never reads Claude's private transcript. Durable machine callers should use claude_turn: issue sends once, recover never sends, pending is distinct from unsafe or malformed state, and only completed carries the exact verified raw_output. Codex uses the normal rollout transcript's task_complete.turn_id; Grok returns the last non-empty assistant message after the last real user row, excluding tool-use preambles; Cursor uses the normal agent transcript bound to the launch ID and current turn. A turn that completed with an empty answer is not an error: text is the empty string and answer_empty is true, so callers can tell it apart from an answer that could not be read. Missing or ambiguous attribution, including an answer that cannot be located in the record, remains an explicit error.
Completion detection (5 layers)
For PowerShell over SSH, mark:true recognizes the current standard PS ...> prompt and emits PowerShell syntax even when Aiterm runs on macOS or Linux. A prompt left in earlier output is not used to select the syntax.
pty_read({ wait: true }) decides "is the command done?" via five layers: process exit / a mark:true sentinel / an until match / output quiescence with shell return / timeout. mark emits the shell's exit status on POSIX shells and 0 (success) or 1 (failure) on PowerShell; fish/csh/tcsh are rejected before send because they do not share either status syntax. When mark or until is active, that requested evidence takes precedence and a momentarily quiet shell cannot complete the read as quiescent. Agent sessions add a sixth exact layer: Codex observes normal rollout task_complete; Grok observes normal session turn_ended; Claude observes its additive launch-correlated Stop event; Cursor observes turn_ended(status:"success") in the launch-bound normal agent transcript. aiterm-wait --cursor performs that harness-specific observation without the parent blocking or polling. Pre-send readiness failures are MCP errors, and late completion remains recoverable without resending.
Completion push for parent agents (aiterm-wait)
Codex/Claude Code/Cursor親には子の回答本文が自動で届く。 Codex/Claude Codeでは、子を起動・dispatchした後は別作業へ進むか親のturnを終える。Aitermが完了を観測し、加工前の本文を保存して親へ渡す。waiter、pty_readによる回答回収、子への返送指示は不要。子は全対応harnessから選べる。
Codex/Claude Codeの自動配送ではreceiptにparent_deliveryが付き、wait_process/wait_commandはnullになる。pty_observeのparent_deliveriesでwaiting、ready、sending、submitted、failed、unknownを確認できる。submittedはCodexの公式受信口での受付またはClaudeのhookへの本文出力を示し、modelの読了ではない。MCP再接続後は未送信の記録を再開し、出力中断で結果が分からない場合は本文を保持してunknownとする。自動再送はしない。
For queue delivery, use a Codex runtime that supplies MCP _meta.threadId and the official thread/queue API (verified with Codex CLI 0.154.0). aiterm-setup checks the installed queue entry point; Aiterm verifies the requesting thread before each dispatch. Codex native sub-agents reject external queue input and cannot be automatic-delivery parents. Steer相当の選択時も公式キューへ投入し、専用hookが同一ターンへ取り込みます。
Claude Codeは2.1.259以上の対話sessionに対応する。aiterm-setupが専用のPreToolUse、PostToolUse、SessionEndを登録するため、Channelsの起動flagは不要。公式asyncRewake hookだけが裏で待ち、親はその間も次のturnへ進める。回答はStop hook feedbackとして届く。hookのexit 2は親の再開信号であり、子の成功・失敗は本文のoutcomeで区別する。
/clear等の会話終了後は未送信の旧回答を送らず、本文を保存する。受信hookの上限は24時間。hookの終了・出力失敗・無効化を成功扱いせず、別の待機経路へ黙って切り替えない。Claude Desktopのチャット、Web、agent_id付きの会話(--agent起動とnative subagent)はこの受信契約に含めない。
hookを持たない旧版、または0.52.2以前へ戻す時は、install前にaiterm-setup --remove-claude-parent-hooksを実行する。Aiterm専用hookだけを解除し、他製品のhookと設定は保持する。
Cursor parents (clientInfo.name of cursor-vscode) use the same completion capture. aiterm-setup adds afterMCPExecution and postToolUse to ~/.cursor/hooks.json and keeps every other hook and its position. A missing registration fails the dispatch with CURSOR_PARENT_HOOK_UNAVAILABLE before the child is sent. While the parent keeps calling tools, the answer is injected through additional_context on the next tool result. If the parent ends the turn, start the receipt wait_process in the background first; that receiver exits when the answer arrives. wait_command is null. submitted means the hook or the receiver claimed the text, not that the model has read it. No claim within 24 hours is failed, the text is kept, and nothing is resent. Remove only Aiterm's entries with aiterm-setup --remove-cursor-parent-hooks. Cursor Cloud Agents and Background Agents are outside this contract.
Claudeをリンク経由のcwdから起動した場合も、実体パスに対応する会話記録を参照する。
For other parent hosts, dispatch and start the receipt's waiter in a separate process:
Launch the child with
agent_launch({ harness: ... }); every launch shares the normal project/user environment and adds only completion correlation plus lineage. Send a turn with plainpty_send(orclaude_turn issuefor durable Claude operations). The call returns immediately with anevent_cursorin its structured receipt. If the child is still working when you send, Aiterm steers the text into the running turn instead (mode: "agent_steer"); the original request's completion then covers it, so no new cursor or delivery is created.Pass the receipt's
wait_process.executableandwait_process.argsunchanged to a true argv process API. PowerShell 7'sStart-Processis the exception because it joins-ArgumentListarrays; passwindows_start_process_argument_listas its one ready-made argument string instead. This invokes the bundled waiter through the exact Node runtime that is already running aiterm, including on native Windows where npm's human-facing bin is a PowerShell script shim and install paths may contain spaces.wait_commandremains a compatibility display string for humans. The waiter observes the harness-owned completion source, plus Claude's additive launch hook, as a pure reader and exits with a one-lineaiterm.agent-wait-result.v1receipt. Exit ≠ done: the receipt'soutcomeis authoritative (0=done,3=timeout,4=closed,1= error).親自身のforegroundでwaiterを実行しない。 receiptのprocess起動情報を、そのhostが持つバックグラウンドprocess APIへ渡す。親は別作業へ進むかturnを終え、process終了の通知で続行する。
Collect the result exactly as before:
pty_read(agent_transcript: true), orclaude_turn recoverfor durable Claude operations. The waiter carries the signal, never the payload.
If your host has no completion push (no mechanism that re-invokes the agent when a background process exits), --timeout 0 is a one-shot check instead of a wait: it scans the event file once and returns running (exit 5) when the turn is still in flight, done (exit 0) when it finished, closed (exit 4) when the session is gone. It is deliberately absent from the receipts and tool descriptions — a host that does get pushed should be woken, not poll. An unknown session name is an error, never running, so a typo cannot masquerade as a child that is still working.
aiterm-wait takes no locks, never writes session state, and never dispatches — any number can run beside the MCP server and each other, and pty_close/concurrent sends are unaffected.
Launch an agent on another machine in one call (remote)
Add remote to agent_launch and the same launch runs in the Aiterm of another machine reached over SSH. Entering the machine and starting its agent become one call, and completion reaches the parent exactly as it does for a local child. The intended use is sending the same task to Linux, macOS, and Windows machines in parallel.
agent_launch({ "harness": "codex-cli", "remote": { "host": "rabbit" }, "cwd": "/home/kite/project", "prompt": "..." })remotetakeshost,user,port,identity_file,passphraseorpassphrase_env, andssh_options(Key=Value). A barehostis used as an~/.ssh/configalias. Aiterm does not store or manage destinations; the caller owns where to connect and with which key.A plain
passphrasestays in the calling AI's conversation log. Prefer ssh-agent orpassphrase_env(an environment variable name). A received passphrase lives only in the MCP process memory and reaches ssh throughSSH_ASKPASS; it is never written to state files or logs.The remote machine needs
aiterm-mcp, tmux (psmux on Windows), and the harness CLI. The remote shell family (POSIX, PowerShell, or cmd) is detected on first contact. On POSIX machines Aiterm takes only PATH from the login shell, so CLIs under~/.local/bin, Homebrew, or nvm are found; on Windows it startsaiterm-mcpwith the user's PATH as is.Pass the same
remoteto laterpty_send,pty_read,pty_close,pty_observe, and so on. Session names belong to the remote machine and never collide with local sessions of the same name.Codex, Claude Code, and Cursor parents receive the answer automatically, as with a local child. Completion is observed with
ssh <host> aiterm-wait, reconnecting at the same cursor if SSH drops. Other parents get an ssh-basedwait_process.Calls to the same destination share one SSH connection through ControlMaster.
imageattachments andclaude_turn issueare not yet supported withremote.POSIX SSH control sockets use a short private directory even with a long TMPDIR. Connections stay isolated by state root; OpenSSH closes idle masters and removes their sockets after 600 seconds.
Token reduction
pty_readby default strips control characters, collapses repeated lines, and folds long output into head+tail (with a restore hint and a meta line).pty_read({ rtk: true })further shrinks the observed output with a per-command reducer (git status/git log/grep/pytestand more) — a self-contained reimplementation that needs nortkbinary.pty_send({ rtk: true })rewrites a known command intortkform before sending, so reduction happens at the source ifrtkexists there (passthrough otherwise).
Input and output
pty_send does not interpret command or prompt meaning; it delivers the requested text to the terminal. By default it sanitizes ESC and bracketed-paste terminators, while pty_read neutralizes control characters in returned output (raw: true keeps them unchanged). The shell, remote endpoint, or launched harness owns command authorization.
Each pty_send accepts at most 64 KiB of UTF-8 text. Sends to the same session are serialized across aiterm processes so chunks cannot interleave. Every OS pastes through its multiplexer in UTF-8-safe 256-byte chunks with a 10 ms drain interval; macOS, Linux, and WSL2 have all demonstrated silent middle/trailing loss when a long input is pushed without that boundary. Sanitized multiline text sent while a POSIX shell or PowerShell is in the foreground is encoded as one newline-free input (eval for POSIX shells; a dot-sourced, UTF-8 Base64-decoded scriptblock for PowerShell): the shell receives the complete script before it runs the first line, so a pager or REPL started mid-script cannot consume later lines as interactive keystrokes. Single-line input, raw:true, and non-shell frontends remain direct PTY pastes. Agent dispatches additionally wrap the whole text once in ESC[200~/201~ and stream the wrapped text in the same chunks, so the agent TUI sees one paste (an image path is never split across pastes), hardening prompt injection against mid-word key-interpretation corruption and dropped submits. If a later chunk fails, aiterm reports the partial-send state and does not press Enter automatically. A lock left by a terminated sender fails closed before sending; use pty_list to confirm the affected session, close it with pty_close, then recreate the same session ID. There is no public kill-all tool.
A human can watch
Sessions live on a shared tmux socket on POSIX or a shared psmux namespace on native Windows. The attach line printed by pty_open and agent_launch lets a human attach to the same terminal and intervene, including a Claude/Codex/Grok/Cursor harness session: tmux -S … attach -t <id> on POSIX, or psmux -L <namespace> attach -t <id> on native Windows.
Requirements
Node.js >= 18
tmux or psmux (platform runtime prerequisite)
macOS / Linux / WSL2 run tmux directly. On macOS install it with
brew install tmux(stock macOS ships none). If your MCP client is launched from the GUI rather than a terminal, Homebrew's bin (/opt/homebrew/binon Apple Silicon,/usr/local/binon Intel) may be off itsPATH; aiterm auto-searches those locations, or setAITERM_TMUX=/path/to/tmuxto point at it explicitly.Native Windows has no tmux, so aiterm drives psmux — a tmux-CLI-compatible native terminal/session multiplexer — with a per-install
-Lnamespace. psmux is not a shell.pty_opendefaults to PowerShell 7 (pwsh.exe) and never falls back to Windows PowerShell 5.1, PowerShell 6, orcmd.exe; if only 5.1 is installed, use Microsoft's official installer or package manager first. Install psmux 3.3.8 or newer (winget install marlocarlo.psmux; 3.3.8 is the first release whosepipe-panefile sink, byte-exactpaste-bufferwire, and foreground#{pane_current_command}behave the way aiterm's capture/dispatch paths rely on). Git for Windows remains required for the explicit Bash shell used internally by harness launchers; System32'sbash.exeis the WSL launcher and is deliberately not used. Override multiplexer/Bash resolution withAITERM_PSMUX/AITERM_BASH. Other products consume persistent terminals through Aiterm's public API instead of depending on psmux directly.
For agent harnesses: the selected CLI, installed and authenticated through its product owner's official path —
claude,codex,grok, or Cursor'scursor-agent. Portable fork additionally needsthroughline >= 0.9.0; ordinary clean launch does not. (Not needed if you only use the PTY tools.)Optional: the
rtkbinary (used bypty_send'srtk: truedelegation; works fine without it)
Known constraints (by design, not bugs)
While nested (ssh / docker / REPL / a launched agent TUI), quiescence cannot fire by design, because the foreground command is no longer in the shell set (bash/sh/zsh/fish/dash). When nested with no
untiland nomark,pty_read({ wait: true })returns early asis_complete=False via nested(rather than burning the fulltimeout, since no signal can confirm completion there) with a note to passuntil(a literal substring by default;until_regex: truefor a regex) ormark: true(an exit-code sentinel, auto-detected) for a confirmed completion. For a full-screen agent TUI, read{ screen: true }once its output settles.is_complete=Falseis not a failure. It means "completion was not observed withintimeout." For long commands, raisetimeoutor useuntil/mark.Agent harnesses run their real TUI; aiterm doesn't proxy the model API. The selected harness owns model choice, authentication, and behavior. There is no hidden inter-agent protocol; the MCP client drives the Claude/Codex/Grok/Cursor TUI with ordinary send/read operations.
pty_send({ rtk: true })is single-line only and needs the externalrtkbinary (passthrough without it). Thepty_read({ rtk: true })reducer, by contrast, is self-contained and rtk-independent.The
pytestreducer matches rtk 0.50.0 on test counts andFAILURES-block formatting (locked by regression tests). It deliberately preserves the full failure reason on theFAILEDsummary lines (emitted under-ra/-rf), whereas rtk 0.50.0 truncates the reason at the first" - "— a readability choice, so those lines are intentionally not byte-identical to rtk. The[full output: …]recall-pointer line rtk appends on large output is not reproduced on the read side.The
grepreducer matches rtk 0.50.0: within the caps it returns the output unchanged, and past a cap its grouped form is byte-identical tortk grepwithout the recall hints.git logkeeps every commit when you set a count (-n) or a range (A..B); otherwise it shows 10 and ends with[+N more commits]. Like rtk'snever_worse, a reducer whose result would cost more tokens than the output is skipped.tmux is started with
-f /dev/null, so it does not read~/.tmux.conf(to keep behavior reproducible across machines).All sessions share one multiplexer endpoint (
claude.sockon POSIX, one psmux namespace on native Windows). The platform'skill-servercommand removes them all.
Development
npm install
npm run build # tsc → dist/
npm test # build, then the node:test regression suite (requires tmux or psmux)
npm link # put `aiterm-mcp` on PATH locally開発中は変更に直結する試験を先に実行する。GitHub Actionsは共通実装・CI自身・未分類の変更をMac・Linux・Windowsで検証し、
Windows固有だけの変更はLinuxとWindowsを選ぶ。版番号だけの変更はLinuxの配布情報・pack確認、文書だけなら文書検査を行う。
試験内容とOSの選択、週次・手動実行の範囲は公開手順に従う。
npm run release -- <version> syncs the version, commits, tags, and publishes the GitHub Release in
one command; tag-triggered npm publishing checks only that the tagged commit is on origin/main and does not
wait for another CI run. The native
Windows runner needs psmux ≥ 3.3.8 and Git for Windows on its PATH, and must run as an
interactive Windows user; NETWORK SERVICE lacks the per-user environment the pane shell and
harness CLIs rely on and is not a valid runner identity.
Logic lives in src/core.ts (tmux control, reduction, completion detection, safety, agent launch) and src/rtk.ts (per-command reducers); src/index.ts is the MCP surface. The current architecture is in docs/DESIGN.md, the release procedure is in docs/RELEASE.md, and prototype/python/ remains the reducer's historical porting source (the pytest and grep reducers are ported to match upstream rtk 0.50.0, except the deliberate FAILED-line difference noted above, and is locked by regression tests).
Try it
公開packageを導入して、検出したAIへ登録する。cloneやビルドは不要:
npm install -g aiterm-mcp@latest
aiterm-setup --jsonIf aiterm let your AI hand a task to another agent — or saved you a round-trip of tokens — star the repo. It's the cheapest way to help others find it.
Issues / bug reports: https://github.com/kitepon/aiterm-mcp/issues
Shared agent environment
All harnesses use the caller's normal project and user environment. Aiterm does not copy, symlink, filter, or replace harness configuration, authentication, MCP, plugin, skill, permission, trust, memory, or history stores. Cleanup removes only aiterm-owned launch metadata and completion correlation files.
The ordinary environment comes from the MCP process that opened the terminal, not from whichever caller
started the persistent multiplexer server (since 0.50.0). Every harness still accepts
env_vars: ["NAME", ...]; those names are placed on the launch command and registered on the session.
License
MIT
Available Tools
18 toolsagent_approvalA
Codexの現在の承認をinspectし、digestへ束縛した単発許可または拒否をrespondする。恒久許可は選ばない。Claudeは既存claude_approvalを使う。未知dialogはblockedのtyped errorで返す。
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| remote | No | 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。 | |
| session_id | Yes | ||
| approval_choice | No | ||
| observed_prompt_digest | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| at | Yes | |
| kind | Yes | |
| action | Yes | |
| prompt | Yes | |
| reason | Yes | |
| schema | Yes | |
| status | Yes | |
| choices | Yes | |
| harness | Yes | |
| launch_id | Yes | |
| session_id | Yes | |
| prompt_digest | Yes | |
| selected_choice | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It reveals that approvals are one-time, bound to a digest, permanent approval is not chosen, and unknown dialogs return a blocked typed error. These are meaningful behavioral traits beyond what the schema exposes, though it omits effects like whether 'respond' mutates state or requires authorization details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, each carrying distinct information: the core operation, the permanent-approval exclusion, and the Claude routing plus error behavior. It is front-loaded with the primary purpose and contains no filler or redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has five parameters, a nested object, and an output schema, the description covers the main flow but leaves some operational details implicit. It does not explicitly map required parameters to each action (e.g., which parameters are needed for 'respond'), nor does it explain how to obtain or interpret the digest, session_id, or the inspect result. The output schema likely documents return values, but the description alone is not fully self-sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 20% (only 'remote' is described), so the description must compensate. It adds semantic detail to 'approval_choice' by explaining it binds to a digest and is one-time, and clarifies 'action' as inspect/respond. However, 'session_id' and 'observed_prompt_digest' are left without further explanation in the description, leaving gaps for an agent to infer their role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb-resource pair: inspect Codex's current approval and respond with a one-time approval or denial bound to the digest. It also differentiates from the sibling claude_approval by explicitly stating that Claude uses the existing tool, making the target clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage guidance: use this for Codex approvals, and use claude_approval for Claude. It also prohibits permanent approval and specifies the behavior for unknown dialogs. It does not explicitly enumerate conditions for choosing 'inspect' versus 'respond', but the purpose is evident from the action enum and the description's verbs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
agent_authA
各harnessの公式CLI認証を開始・確認・取消する。CLIごとのコマンドと認証URL/codeの抽出はAitermが所有し、資格情報は各CLIだけが保存する。waitingのURL/codeを人へ表示し、input_requiredなら同じsessionのpty_send/pty_keyで公式画面へ入力する。authenticatedは認証の結果であり、agent_launchの起動準備完了とは別。remoteは他toolと同じ標準対応。
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | 公式CLIを実行する作業ディレクトリの絶対パス | |
| action | Yes | ||
| remote | No | 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。 | |
| harness | Yes | ||
| env_vars | No | startで認証PTYへ引き継ぐ環境変数名。値はreceiptへ返さない | |
| session_id | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| schema | Yes | |
| status | Yes | |
| harness | Yes | |
| message | Yes | |
| user_code | Yes | |
| session_id | Yes | |
| input_required | Yes |
TDQS
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 discloses that Aiterm only extracts commands/URLs while credentials are persisted solely by each CLI, and it documents the state machine (waiting → input_required → authenticated). It omits any failure/timeout or permission behavior for start/cancel, keeping it 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the purpose statement, then proceeds through ownership, human-in-the-loop flow, state semantics, and remote support in compact sentences. Dense but each sentence carries distinct information; no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value explanation is not required, and the description still usefully defines the waiting/input_required/authenticated statuses. For a credential-touching start/cancel tool with no annotations, the main gap is absence of error/failure guidance and permission/prerequisite notes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 50%, so the description should compensate more than it does. It adds meaning for `remote` ('same standard support as other tools') and implies `session_id` via the pty continuation flow, but says nothing about `cwd`, `harness`, or the action enum nuances beyond restating start/status/cancel. Baseline 3 for a 50%-covered 6-param tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb set (開始・確認・取消 = start/status/cancel) tied to a specific resource (各harnessの公式CLI認証), and explicitly separates itself from agent_launch by noting that 'authenticated' is not launch readiness. An agent can identify the tool's scope without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives concrete workflow routing: for 'waiting' show the URL/code to the human, and for 'input_required' feed the official screen via pty_send/pty_key in the same session. It also names the distinguishing boundary with agent_launch. It does not state when NOT to use the tool (e.g. if already authenticated), so it stops short of full when/when-not coverage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
agent_configureA
起動済みのClaude/Codex/Grok/Cursor agent sessionを再起動せず、会話contextを保ったままmodel/reasoning effortを変更する。各harnessのCLI標準model操作を使う。Cursorのreasoning_effort変更はmodelと同時指定する。
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | 変更後のmodel。省略時はmodelを変更しない | |
| remote | No | 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。 | |
| session_id | Yes | ||
| reasoning_effort | No | 変更後のreasoning effort。省略時はeffortを変更しない |
Output Schema
| Name | Required | Description |
|---|---|---|
| model | Yes | |
| schema | Yes | |
| harness | Yes | |
| provider | Yes | |
| session_id | Yes | |
| reasoning_effort | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses useful traits: no restart, conversation context preserved, use of each harness's CLI standard model operation, and the Cursor requirement that reasoning_effort be paired with model. It still omits permissions, failure modes, and remote-specific behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three compact sentences, front-loaded with the core purpose and key constraints. Every sentence adds useful information with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-harness configure tool with a nested remote object and no annotations, the description covers the main operation and the Cursor constraint but omits remote/local distinction, where to find valid model names, and error behavior. An output schema exists, so return values need not be explained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 75% and already documents model, remote, and reasoning_effort. The description adds a non-obvious parameter interaction: for Cursor, reasoning_effort changes must be specified together with model. It does not mention session_id or remote, but those are covered by the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: changes model/reasoning effort for an already-started Claude/Codex/Grok/Cursor session without restarting. The phrase '起動済み' and '再起動せず' distinguish it from launch-oriented siblings, but no sibling tool is named for contrast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly states the use case: modifying an existing session's model/effort while preserving conversation context. It gives no explicit when-not conditions and does not name alternatives such as agent_launch or agent_models.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
agent_launchA
エージェントを単一の標準入口から永続sessionへ起動する。harnessはagent loop・認証・hook・transcriptを所有する実行基盤、modelはそのharnessが選ぶ推論モデルであり別軸。Cursor harnessからGPT/Claude/Grok等を選んでも完了相関はCursor方式のまま。ComposerはCursorのmodelの一つで、harnessでもGrokのmodelでもない。harness=cursor-cli と model=composer-2.5-fast(またはcomposer-2.5)で指定する。remoteを付けると、SSHで入った別端末のAitermで同じ起動を行い、完了は同じ形で親へ届く。通常CLIと同じHOME・cwd・project/user/local設定・MCP・plugin・skill・permission/trustを共有する。aitermは完了相関stateだけをlaunch単位で所有する。起動されたagentにはsub-agent自己認識、親session、delegation depth/lineage、delegation_allowed=trueを注入し、必要な追加委譲は許可する。dispatch した子は投げっぱなしでよい=親はここで待たない。Codex親とClaude Code親にはAitermが回答本文を自動配送する。parent_deliveryがある場合はwait起動も通常の回答回収も不要。親は作業を続けるかターンを終える。Cursor親にはparent_deliveryとwait_processが付く。作業を続ければ次のツール返りに回答が差し込まれ、ターンを終える前にwait_processを背景で起動するとidle中の完了でも起きられる。ポーリングとpty_read(agent_transcript:true)は不要。その他の親では、完了通知をreceiptの wait_process.executable と wait_process.args をそのまま親のターンを塞がない別プロセスAPIへ渡して受け、PowerShell 7のStart-Processだけは windows_start_process_argument_list を単一文字列として渡す。exit を完了通知として扱う(exit 0=done / 3=timeout(既定600秒・未完了) / 4=closed / 7=error(harnessの記録でturnがAPIエラー等で打ち切られた。結果は無い)。receiptのoutcomeが正で、done以外は未完了。ポーリング不要)。wait_command は人間向け互換表示でありprocess境界へ使わない。foreground実行で親のターンを塞がない。自動配送以外の結果回収は pty_read(agent_transcript:true)。
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | 作業ディレクトリ(絶対パス・任意) | |
| image | No | 初手プロンプトへ添付する画像ファイルの絶対パス(png/jpg/jpeg/gif/webp) | |
| model | No | harnessが選ぶモデル。provider名ではなくlive catalog上のmodel ID | |
| prompt | No | 起動時に渡す初手プロンプト(任意)。送信後は待たずに即返る | |
| remote | No | 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。 | |
| harness | Yes | agent loop・session・hook・transcript・認証を所有する実行基盤 | |
| env_vars | No | 現在のMCP processから継承する環境変数名 | |
| write_scope | No | 能力宣言。read-onlyは対応harnessの標準read-only面で実効禁止する | |
| session_name | No | Aiterm session名(省略で自動採番) | |
| trust_project | No | 対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める | |
| reasoning_effort | No | harness adapterが標準CLI表現へ変換する思考レベル。Cursorではmodel同時指定が必要 | |
| launch_operation_id | No | Claude Codeのpromptなしexact replay相関だけで使用 | |
| throughline_source_session | No | 同一端末のThroughline sessionから読み取り専用contextを初手へ注入する | |
| throughline_supplement_file | No | Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path |
Output Schema
| Name | Required | Description |
|---|---|---|
| schema | Yes | |
| harness | Yes | |
| startup | Yes | |
| provider | Yes | 旧互換field。新規連携はharnessを使う |
| session_id | Yes | |
| remote_host | No | 別端末で起動した時の接続先 |
| write_scope | No | |
| event_cursor | Yes | |
| wait_command | Yes | |
| wait_process | Yes | |
| initial_prompt | Yes | |
| remote_version | No | 別端末のAiterm版 |
| submit_residue | Yes | |
| parent_delivery | No | |
| managed_completion | Yes | |
| write_scope_enforcement | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden and largely discharges it: exit-code semantics (0=done, 3=timeout default 600s, 4=closed, 7=error), receipt outcome precedence, non-blocking behavior, inherited HOME/cwd/project/user/local config/MCP/plugin/skill/permission, injected sub-agent identity and delegation depth, and remote SSH behavior. This is unusually rich disclosure of what the call does beyond structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose is front-loaded, but the remainder is a dense wall of run-on Japanese sentences with no formatting, covering exit codes, delivery, remote, and parent-side mechanics in one block. Almost every sentence is substantive, but the lack of structure and the sheer length hurt scannability for an agent deciding whether to call it.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 14-parameter tool with a nested remote object, an enum, and an output schema, the definition covers the behavioral surface thoroughly: lifecycle, completion signaling, result retrieval, and parent-side handling. Nothing essential to calling it correctly is missing, and return values are covered by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds real meaning beyond the schema by clarifying that harness and model are orthogonal axes and that Composer is a Cursor model, not a harness or a Grok model, which directly guides correct harness/model pairing. It adds less on the other twelve parameters, which the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
First sentence states a specific verb and resource: launch an agent into a persistent session from a single standard entry point. It also disambiguates the harness/model axis, which is the core conceptual trap. It does not, however, explicitly differentiate itself from siblings like claude_agent, codex_agent, or grok_agent, so 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives concrete when/when-not guidance: dispatch children need not be awaited, do not poll, do not use wait_command as a process boundary, use pty_read(agent_transcript:true) for non-auto-delivery collection. It names alternatives (wait_process, parent_delivery) and their conditions, though it never frames the choice against the sibling launch tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
agent_modelsA
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。
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | CLI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 | |
| remote | No | 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。 | |
| harness | Yes | 候補を取得するharness | |
| include_hidden | No | Codex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
| Name | Required | Description |
|---|---|---|
| models | Yes | |
| schema | Yes | |
| source | Yes | 取得に使ったharnessの公式の入口 |
| efforts | Yes | 全modelのeffortの和 |
| harness | Yes | |
| default_model | Yes | model省略時にharnessが使うmodel。一覧のIDで表せなければnull |
| adapter_efforts | Yes | harnessの一覧には無く、Aitermのadapterが足したeffortと理由 |
| harness_version | Yes |
TDQS
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.
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.
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.
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.
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.
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.
claude_agentA
【旧互換alias。新規連携は agent_launch(harness=claude-code)】Claude Codeの対話エージェントTUIを永続端末に起動する。claude -pではなく、同じ利用者可視sessionへpty_sendで継続入力する。通常CLIと同じHOME・cwd・project/user/local設定・MCP・plugin・skill・permission/trustを共有する。aitermは完了相関stateだけをlaunch単位で所有する。起動されたagentにはsub-agent自己認識、親session、delegation depth/lineage、delegation_allowed=trueを注入し、必要な追加委譲は許可する。通常settingsへlaunch固有Stop hook settingsを加算する。起動前に共有認証を構造化確認し、未認証ならsessionを作らない。dispatch した子は投げっぱなしでよい=親はここで待たない。Codex親とClaude Code親にはAitermが回答本文を自動配送する。parent_deliveryがある場合はwait起動も通常の回答回収も不要。親は作業を続けるかターンを終える。Cursor親にはparent_deliveryとwait_processが付く。作業を続ければ次のツール返りに回答が差し込まれ、ターンを終える前にwait_processを背景で起動するとidle中の完了でも起きられる。ポーリングとpty_read(agent_transcript:true)は不要。その他の親では、完了通知をreceiptの wait_process.executable と wait_process.args をそのまま親のターンを塞がない別プロセスAPIへ渡して受け、PowerShell 7のStart-Processだけは windows_start_process_argument_list を単一文字列として渡す。exit を完了通知として扱う(exit 0=done / 3=timeout(既定600秒・未完了) / 4=closed / 7=error(harnessの記録でturnがAPIエラー等で打ち切られた。結果は無い)。receiptのoutcomeが正で、done以外は未完了。ポーリング不要)。wait_command は人間向け互換表示でありprocess境界へ使わない。foreground実行で親のターンを塞がない。自動配送以外の結果回収は pty_read(agent_transcript:true)。Claude の durable turn は claude_turn でも回収できる。
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | 作業ディレクトリ(対象リポのルート等・任意) | |
| model | No | 起動モデル(例: claude-sonnet-4-6)。省略時はClaude CLI既定 | |
| prompt | No | 起動時に渡す初手プロンプト(任意)。送信後は待たずに即返る | |
| env_vars | No | 起動したagentへ現在のMCP processから継承する環境変数名。値はtool引数へ渡さない | |
| session_name | No | セッション名(省略で自動採番) | |
| trust_project | No | 対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める | |
| reasoning_effort | No | Claude Code reasoning effort。low/medium/high/xhigh/max。省略時はCLI既定 | |
| launch_operation_id | No | promptなしClaude launchのexact replay相関ID。session_name必須 | |
| throughline_source_session | No | 同一端末のThroughline sessionから所有権を変えずに記憶を読み、promptのmissionより前へ注入する | |
| throughline_supplement_file | No | Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path |
Output Schema
| Name | Required | Description |
|---|---|---|
| schema | Yes | |
| harness | Yes | |
| startup | Yes | |
| provider | Yes | |
| session_id | Yes | |
| event_cursor | Yes | |
| wait_command | Yes | |
| wait_process | Yes | |
| initial_prompt | Yes | |
| submit_residue | Yes | |
| parent_delivery | No | |
| managed_completion | Yes | 後方互換field。trueはaiterm完了相関が有効という意味で、project/user環境の隔離を意味しない |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses the auth pre-check and no-session-creation-when-unauthenticated behavior, fire-and-forget dispatch, non-blocking foreground execution, parent-specific delivery modes, exit code meanings (0/3/4/7), and result collection via pty_read or claude_turn. This is far richer than the schema or annotations could convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and front-loads the legacy-alias/agent_launch decision. Every clause contributes a distinct operational fact, but it is presented as one long block of complex Japanese with many parenthetical clauses, which hurts scannability. The length is largely earned given the tool's complexity, so it stops short of a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a legacy launcher with an output schema present, the description covers the full calling lifecycle: when to use it, auth requirements, launch behavior, completion signaling, exit codes, parent-delivery variants, and result retrieval. No critical operational information appears missing, and return-value documentation is already handled by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes all 10 parameters (100% coverage), including prompt's 'send-then-return' behavior and launch_operation_id's replay correlation. The description adds minimal parameter-level meaning beyond the schema, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it is a legacy-compatible alias that launches the Claude Code interactive agent TUI in a persistent terminal ('Claude Codeの対話エージェントTUIを永続端末に起動する'). It also distinguishes itself from sibling agent_launch by explicitly directing new integrations to that tool, giving an agent a clear verb+resource and a sibling discriminator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The opening sentence explicitly says new integrations should use agent_launch(harness=claude-code), so the condition for using this legacy alias is apparent. It also adds when-not guidance such as 'wait_command ... はprocess境界へ使わない' and states that polling/pty_read(agent_transcript:true) are unnecessary under parent-delivery modes, helping the agent avoid wrong follow-up actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
claude_approvalA
aiterm相関付きClaudeのactive turn中に表示された権限確認UIを、turn相関を保ったまま検査・応答する専用面。inspectで画面digestと安全な単発Yes/Noだけを取得し、respondは同じoperation・同じdigestが現在も表示中の場合だけ送信する。
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| remote | No | 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。 | |
| session_id | Yes | ||
| operation_id | No | durable operationのID。通常pty_send由来の匿名turnでは省略する | |
| approval_choice | No | respondだけに指定する | |
| observed_prompt_digest | No | 直前のinspectが返したdigest。respondだけに指定する |
Output Schema
| Name | Required | Description |
|---|---|---|
| at | Yes | |
| action | Yes | |
| schema | Yes | |
| status | Yes | |
| choices | Yes | |
| session_id | Yes | |
| operation_id | Yes | |
| prompt_digest | Yes | |
| selected_choice | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behavioral constraints: inspect only retrieves a digest and safe one-shot Yes/No options, and respond is only sent when both operation and digest match the current display. This gives the agent a clear safety model, though it does not detail error handling or side effects beyond these conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense sentence that front-loads the purpose and then explains the two actions' constraints. It is concise but packs a lot of information; every clause contributes to the tool's usage, though it could be split for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 params, nested remote object, output schema present), the description is fairly complete. It explains the core workflow and conditions for safe use, and the output schema covers return details. Minor gaps remain about what happens on digest mismatch or connection issues, but these are not critical for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67%, and the description adds meaning by explaining the action flow and which parameters apply to each action (e.g., approval_choice and observed_prompt_digest are for respond only). The remote parameter also gets detailed guidance in the schema, and the tool description reinforces the conditional use of these params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: inspecting and responding to Claude's permission-confirmation UI during an active turn, while preserving turn correlation. It specifies the two actions (inspect for a digest and safe one-shot Yes/No, respond only when the same operation/digest is displayed) and distinguishes itself from siblings by focusing on Claude and aiterm correlation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys when to use the tool (during Claude's active turn) and when to respond (only when the digest matches). It implies this is the specialized surface for Claude, but it does not explicitly name alternatives like agent_approval or contrast them. Clear context, but no explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
claude_turnB
aiterm相関付きClaude sessionのdurable operationを構造化issue/recoverするmachine-caller専用面。pending/unknown/completedを人間向けerror文字列の解析なしで返し、Observer固有ロジックは持たない。
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | issueだけに指定するbounded turn本文 | |
| action | Yes | ||
| remote | No | 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。 | |
| session_id | Yes | ||
| operation_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| action | Yes | |
| reason | Yes | |
| schema | Yes | |
| status | Yes | |
| raw_output | Yes | |
| session_id | Yes | |
| operation_id | Yes | |
| submit_residue | Yes | |
| parent_delivery | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It usefully discloses that results are returned as structured statuses without parsing human-facing error strings, and that no observer-specific logic is included. However, it does not disclose potential side effects of issuing or recovering operations, authentication needs, or whether operations are idempotent or reversible.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense sentence that front-loads the core purpose and then adds behavioral details. It avoids filler, though the heavy Japanese jargon ('aiterm相関付き', 'machine-caller専用面') makes it less immediately readable than it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the operational model and return status categories, and an output schema exists to document return values. Still, the combined gaps around required parameter semantics and when to select this tool over sibling tools leave the definition only partially complete for an agent that needs to invoke it correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 40%, so the description needed to compensate for the undocumented required parameters such as session_id and operation_id. The tool description does not explain these or their relationship to the issue/recover actions; only the schema's text and remote descriptions provide any parameter-level meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names specific actions ('issue/recover') and a specific resource ('durable operations of Claude sessions associated with aiterm'), and clarifies that it returns machine-readable statuses ('pending/unknown/completed'). It implicitly distinguishes itself from observer/pty-facing tools by stating it has no Observer-specific logic, though it does not explicitly name a sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'machine-caller専用面' gives clear context that this is meant for programmatic callers, and 'Observer固有ロジックは持たない' implies it should not be used for observer behaviors. However, no alternative tools or explicit when/when-not conditions are named, so the usage guidance remains mostly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
codex_agentA
【旧互換alias。新規連携は agent_launch(harness=codex-cli)】Codexの対話エージェント TUI を永続端末に起動する。実装・レビュー・調査を対話で回す。通常CLIと同じHOME・cwd・project/user/local設定・MCP・plugin・skill・permission/trustを共有する。aitermは完了相関stateだけをlaunch単位で所有する。起動されたagentにはsub-agent自己認識、親session、delegation depth/lineage、delegation_allowed=trueを注入し、必要な追加委譲は許可する。委譲契約を使う完全な呼び出し例: codex_agent({"prompt":"<依頼>","model":"gpt-5.6-sol","reasoning_effort":"high","cwd":"/absolute/path/to/repo","write_scope":"read-only"})。turn は pty_send で送る(自動で非ブロック dispatch になる)。dispatch した子は投げっぱなしでよい=親はここで待たない。Codex親とClaude Code親にはAitermが回答本文を自動配送する。parent_deliveryがある場合はwait起動も通常の回答回収も不要。親は作業を続けるかターンを終える。Cursor親にはparent_deliveryとwait_processが付く。作業を続ければ次のツール返りに回答が差し込まれ、ターンを終える前にwait_processを背景で起動するとidle中の完了でも起きられる。ポーリングとpty_read(agent_transcript:true)は不要。その他の親では、完了通知をreceiptの wait_process.executable と wait_process.args をそのまま親のターンを塞がない別プロセスAPIへ渡して受け、PowerShell 7のStart-Processだけは windows_start_process_argument_list を単一文字列として渡す。exit を完了通知として扱う(exit 0=done / 3=timeout(既定600秒・未完了) / 4=closed / 7=error(harnessの記録でturnがAPIエラー等で打ち切られた。結果は無い)。receiptのoutcomeが正で、done以外は未完了。ポーリング不要)。wait_command は人間向け互換表示でありprocess境界へ使わない。foreground実行で親のターンを塞がない。自動配送以外の結果回収は pty_read(agent_transcript:true)。model / reasoning_effort を引数で指定可(省略時は端末 config/CLI 既定を継承。実効値は起動応答に明示)。
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | 作業ディレクトリ(対象リポのルート等・任意) | |
| model | No | 起動モデル(例: gpt-5.6-sol / gpt-5.6-terra / gpt-5.6-luna)。省略時は端末 config/CLI 既定を継承(端末側のピンがそのまま効く。実効値は起動応答に明示される) | |
| prompt | No | 起動時に渡す初手プロンプト(任意)。送信後は待たずに即返る | |
| env_vars | No | 起動したagentへ現在のMCP processから継承する環境変数名。値はtool引数へ渡さない | |
| write_scope | No | 能力宣言。read-only、または書込みを許可するパスの説明文字列。対応harnessのread-onlyはCLI標準のread-only面で実効禁止する | |
| session_name | No | セッション名(省略で自動採番) | |
| trust_project | No | 対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める | |
| reasoning_effort | No | reasoning effort(思考レベル)。low/medium/high/xhigh/max/ultra(CLI/model 版依存)。ultra は max 推論+proactive 自動委譲 ON=使用量急増注意(明示要求時のみ)。省略時は端末 config/CLI 既定。 | |
| throughline_source_session | No | 同一端末のThroughline sessionから所有権を変えずに記憶を読み、promptのmissionより前へ注入する | |
| throughline_supplement_file | No | Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path |
Output Schema
| Name | Required | Description |
|---|---|---|
| schema | Yes | |
| harness | Yes | |
| startup | Yes | |
| provider | Yes | |
| session_id | Yes | |
| write_scope | No | |
| event_cursor | Yes | |
| wait_command | Yes | |
| wait_process | Yes | |
| initial_prompt | Yes | |
| submit_residue | Yes | |
| parent_delivery | No | |
| managed_completion | Yes | 後方互換field。trueはaiterm完了相関が有効という意味で、project/user環境の隔離を意味しない |
| write_scope_enforcement | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It extensively covers sharing of HOME, cwd, and settings, injection of delegation context, fire-and-forget dispatch semantics, handling of various parent types (Aiterm, Cursor, others), and detailed exit codes (0=done, 3=timeout, 4=closed, 7=error). It also clarifies that model and reasoning_effort defaults are inherited, and that ultra reasoning increases usage. This is exceptional transparency beyond typical descriptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long and information-dense but well-structured, starting with purpose and alias note, then sharing settings, then call example, then turn/delivery mechanics, and exit codes. It front-loads the most critical usage information (alias and new integration pointer). While verbose, each sentence carries substantive detail for a complex tool with 10 parameters and varied behaviors, so it earns a 4 rather than a 3.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, multiple parent types, delivery mechanisms, exit codes), the description is remarkably complete. It explains how to handle every scenario: waiting vs fire-and-forget, delivery via parent_delivery, wait_process, and pty_read, and the meaning of exit codes. Since an output schema exists, return values are covered elsewhere, and the description fills all other gaps. Nothing an agent needs to call it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all 10 parameters with descriptions (100% coverage), so the baseline is 3. The description adds value by providing a concrete call example highlighting prompt, model, reasoning_effort, cwd, and write_scope, and clarifies semantics like write_scope being a capability declaration and prompt returning immediately after send. This enriches understanding beyond the schema, hence a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's function: 'Codexの対話エージェント TUI を永続端末に起動する' (launches Codex's conversational agent TUI in a persistent terminal). It identifies itself as a backwards-compatibility alias and clearly distinguishes from siblings like claude_agent, grok_agent, and composer_agent by specifying Codex. It also clarifies its role in implementation, review, and investigation, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: '旧互換alias。新規連携は agent_launch(harness=codex-cli)' instructs that new integrations should use agent_launch instead. It details when to use this alias for legacy purposes and gives a concrete call example. It also explains turn delivery via pty_send, result retrieval via parent_delivery or pty_read, and explicitly states that polling and wait_command are not appropriate, preventing misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
diagnosticsA
Factory 向け read-only 診断。安全な状態語彙だけを機械可読 JSON で返す(PTY 内容・認証情報・path・環境値は返さない)。2つ目のtextは親配送hook(Claude Code・Cursor)の登録状態で、caller_status が setup_required なら呼出元からのagent送信は拒否される。aiterm-setup を実行する。
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
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 declares the operation read-only, enumerates what is deliberately NOT returned (PTY contents, credentials, path, environment values), and explains the caller_status gate that can deny agent sending. It does not describe output format details beyond 'machine-readable JSON', but the safety profile is clearly conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Efficient and front-loaded: the read-only nature and safety boundary come first, followed by the hook-status behavior. It is dense but each clause (safety exclusions, caller_status effect, setup remedy) earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema diagnostic tool, the description is fairly complete: it covers the read-only guarantee, the data-safety boundary, and the actionable caller_status behavior. Minor gaps remain around exactly what diagnostic categories are returned, but nothing essential for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so per the rubric the baseline is 4. There are no parameter semantics to document or omit, and nothing in the description contradicts the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource ('read-only 診断' / diagnostics) and scopes it to Factory, returning machine-readable JSON. It is reasonably distinguishable from the pty_* siblings, though it never explicitly names an alternative tool. The exact scope of what is diagnosed remains a bit general.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies usage by describing the caller_status=setup_required condition and instructing to run aiterm-setup, which is actionable context. However, it never states explicitly when to call diagnostics versus the many sibling tools. Usage is implied rather than directed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
grok_agentA
【旧互換alias。新規連携は agent_launch(harness=grok-cli)】Grok BuildのGrokモデル(既定 grok-4.6)の対話エージェント TUIを永続端末に起動する。通常CLIと同じHOME・cwd・project/user/local設定・MCP・plugin・skill・permission/trustを共有する。aitermは完了相関stateだけをlaunch単位で所有する。起動されたagentにはsub-agent自己認識、親session、delegation depth/lineage、delegation_allowed=trueを注入し、必要な追加委譲は許可する。turn は pty_send で送る(自動で非ブロック dispatch になる)。dispatch した子は投げっぱなしでよい=親はここで待たない。Codex親とClaude Code親にはAitermが回答本文を自動配送する。parent_deliveryがある場合はwait起動も通常の回答回収も不要。親は作業を続けるかターンを終える。Cursor親にはparent_deliveryとwait_processが付く。作業を続ければ次のツール返りに回答が差し込まれ、ターンを終える前にwait_processを背景で起動するとidle中の完了でも起きられる。ポーリングとpty_read(agent_transcript:true)は不要。その他の親では、完了通知をreceiptの wait_process.executable と wait_process.args をそのまま親のターンを塞がない別プロセスAPIへ渡して受け、PowerShell 7のStart-Processだけは windows_start_process_argument_list を単一文字列として渡す。exit を完了通知として扱う(exit 0=done / 3=timeout(既定600秒・未完了) / 4=closed / 7=error(harnessの記録でturnがAPIエラー等で打ち切られた。結果は無い)。receiptのoutcomeが正で、done以外は未完了。ポーリング不要)。wait_command は人間向け互換表示でありprocess境界へ使わない。foreground実行で親のターンを塞がない。自動配送以外の結果回収は pty_read(agent_transcript:true)。model/reasoning_effortを引数で指定可。read-only sandboxとagent_configureに対応。
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | 作業ディレクトリ(対象リポのルート等・任意) | |
| model | No | 起動モデル。省略時は grok-4.6。explicit modelを起動前にlive catalogへ照合し、不在ならfallbackせずエラー | |
| prompt | No | 起動時に渡す初手プロンプト(任意)。送信後は待たずに即返る | |
| env_vars | No | 起動したagentへ現在のMCP processから継承する環境変数名。値はtool引数へ渡さない | |
| write_scope | No | 能力宣言。read-only、または書込みを許可するパスの説明文字列。対応harnessのread-onlyはCLI標準のread-only面で実効禁止する | |
| session_name | No | セッション名(省略で自動採番) | |
| trust_project | No | 対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める | |
| reasoning_effort | No | Grok Build reasoning effort。利用可能値はCLI/modelのlive catalogに従う。省略時はCLI/model既定。 | |
| throughline_source_session | No | 同一端末のThroughline sessionから所有権を変えずに記憶を読み、promptのmissionより前へ注入する | |
| throughline_supplement_file | No | Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path |
Output Schema
| Name | Required | Description |
|---|---|---|
| schema | Yes | |
| harness | Yes | |
| startup | Yes | |
| provider | Yes | |
| session_id | Yes | |
| write_scope | No | |
| event_cursor | Yes | |
| wait_command | Yes | |
| wait_process | Yes | |
| initial_prompt | Yes | |
| submit_residue | Yes | |
| parent_delivery | No | |
| managed_completion | Yes | 後方互換field。trueはaiterm完了相関が有効という意味で、project/user環境の隔離を意味しない |
| write_scope_enforcement | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and delivers thoroughly: non-blocking dispatch, fire-and-forget semantics, exit-code contract (0=done/3=timeout/4=closed/7=error), completion-notification handling per parent type, threading behavior (foreground doesn't block parent turn), and result-collection path. Nothing about lifecycle or error behavior is left to inference.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence carries necessary information given the tool's complexity, but it's a single unbroken Japanese wall of text with no line breaks, bullets, or sectioning. The legacy-alias note is front-loaded, which is good, but the density makes it hard to scan. It's comprehensive but not structured conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool of this complexity (10 optional params, sub-agent lifecycle, parent routing, completion codes, delegation injection), the description is exceptionally complete. Combined with 100% schema coverage and an output schema, an agent has everything needed to launch correctly, route results, and interpret exit states.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3; the schema documents all 10 parameters well (model default/fallback policy, prompt immediate return, env_vars inheritance). The description adds context about model/reasoning_effort configurability and delegation injection, but does not substantially deepen parameter meaning beyond schema. The baseline is correct here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb+resource: it launches (起動する) the Grok Build dialogue agent TUI on a persistent terminal. It explicitly declares itself a legacy compatibility alias and names the primary alternative (agent_launch(harness=grok-cli)), distinguishing it from sibling agents (claude_agent, codex_agent, composer_agent) by harness. The purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says new integrations should use agent_launch instead (a clear exclusion), and provides detailed routing guidance by parent type (Codex, Claude Code, Cursor, others) covering wait_process and auto-delivery behavior. It doesn't fully position against all sibling agent-launch tools (e.g., when to prefer grok_agent over codex_agent beyond harness difference), so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pty_closeA
セッションを閉じ、ログ/読取位置を破棄する。同じsession_idへの再試行は安全で、closed/already_closedのstructured receiptを返す。
| Name | Required | Description | Default |
|---|---|---|---|
| remote | No | 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。 | |
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| schema | Yes | |
| outcome | Yes | |
| session_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden. It discloses that logs and read position are discarded, that retries are safe, and that the return is a structured receipt with closed/already_closed states. This is more than a minimal statement of the action. It does not cover side effects like resource cleanup details or auth requirements, but for a close operation the disclosed behavior is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the primary action and then adds the key behavioral notes (retry safety, receipt type). No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a nested remote object and an output schema, but the description ignores the remote parameter entirely. While the output schema covers return values, the lack of any mention of the optional remote or the meaning of session_id leaves a gap for an agent. For a relatively simple close operation, the core behavior is covered, but parameter context is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no explanation for either parameter. The schema has a detailed description for 'remote', but none for 'session_id'. Since the schema description coverage is 50% and the description fails to compensate for the undocumented required parameter, the agent gets no additional guidance. The description does not clarify what session_id represents or how the remote parameter affects execution.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('close'), a specific resource (session), and the effect (discard logs/read position). It clearly distinguishes from sibling tools like pty_send or pty_read, even without naming them, because the action is unique and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage hint by noting that retrying with the same session_id is safe, which implies it is idempotent. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The guidance is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pty_keyA
制御キーを送る(C-c, C-d, Enter, Tab, Up, Down... の別名に対応)。aiterm相関付きClaude sessionではturn相関を守るためC-cだけを許可し、承認UIはclaude_approvalで操作する。
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | キー名(例 "C-c", "Enter", "Up") | |
| remote | No | 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。 | |
| session_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a key behavioral restriction (only C-c allowed in aiterm-associated sessions) and indicates that approval UI is not handled here. However, it does not explain what happens when other keys are sent in restricted contexts, potential side effects, or the overall effect of sending keys. Some transparency is present, but significant behavioral details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two sentences. It front-loads the primary function and then adds a critical usage caveat. Every word contributes; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has a nested remote object, no output schema, and no annotations, the description is notably incomplete. It fails to mention the remote parameter's role, return values, error behavior, or how session_id is used. While the key restriction is valuable, an agent lacks sufficient information to use the tool correctly in all intended scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67% (key and remote have descriptions; session_id lacks one). The description adds value for the key parameter by listing examples of valid aliases, which goes beyond the schema's generic 'key name'. It does not address session_id or remote, but remote already has a thorough schema description. The description partially compensates for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool sends control keys with aliases like C-c, C-d, Enter, etc. It distinguishes itself from pty_send (which likely sends text) by focusing on control keys. While it doesn't explicitly name a sibling, the purpose is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: in aiterm-associated Claude sessions, only C-c is permitted to preserve turn correlation, and approval UI should be handled via claude_approval. This tells the agent when to use and when not to use the tool, and names an alternative (claude_approval) for related operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pty_listB
握っているセッション一覧(名前 / 現在の前面コマンド / attach 状態 / サイズ / agent 情報)。
| Name | Required | Description | Default |
|---|---|---|---|
| remote | No | 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。 | |
| env_keys | No | 帰属確認用の非秘密環境変数名。指定したキーだけを返す |
Output Schema
| Name | Required | Description |
|---|---|---|
| schema | Yes | |
| sessions | Yes | |
| observed_at | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It discloses the returned information (name, foreground command, attach state, size, agent info) and implies a read-only inventory, but it does not explicitly state that the call has no side effects or how the optional remote parameter affects the listing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single compact sentence that front-loads the operation ('list of held sessions') and then names exactly the useful output dimensions. There is no wasted text or repetition of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The parameter schema is rich and an output schema exists, so the minimal description is workable. However, for a no-annotation tool it would be more complete with a sentence about default/local behavior versus remote listing and whether the operation is purely read-only.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters are already described in the schema (100% coverage), including SSH connection details and env_keys behavior. The main description adds no extra parameter semantics, so the schema baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action and resource: it returns the list of held sessions ('握っているセッション一覧') and enumerates the returned attributes. This is clearly distinct from single-session operations like pty_open, pty_send, and pty_read, though it does not explicitly name sibling alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to call this tool, when not to, or which sibling to prefer. The use case is only implied by the list nature, and no prerequisites, exclusions, or context-specific routing information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pty_observeA
指定sessionの存在、paneとharnessの生存、状態と理由、native process identity、画面変化とCPU活動を構造化して観測する。画面本文と生argvは返さない。
| Name | Required | Description | Default |
|---|---|---|---|
| cursor | No | 前回のactivity.cursor。省略・session再作成時は活動差分をnullで返す | |
| remote | No | 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。 | |
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| state | Yes | |
| exists | Yes | |
| reason | Yes | |
| schema | Yes | |
| harness | Yes | |
| activity | Yes | |
| launch_id | Yes | |
| pane_alive | Yes | |
| session_id | Yes | |
| token_hint | Yes | |
| observed_at | Yes | |
| pane_process | Yes | |
| harness_alive | Yes | |
| harness_process | Yes | |
| process_identity | Yes | |
| parent_deliveries | No | |
| pending_child_deliveries | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden, and it does disclose the output boundary (screen body and raw argv are withheld) plus the observation dimensions, implying a passive/read-only call. It says nothing about permissions, the cost of remote SSH execution, or repeat-call/rate behavior, which are the remaining gaps for an unannotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two dense sentences: the first front-loads the full observation scope, the second front-loads the critical negative (what is not returned). Every clause maps to a distinct observable, and no sentence is filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value shape needn't be spelled out, and the description correctly covers the non-obvious parts: what is observed and what is deliberately withheld. It stops short of explicitly pointing to pty_read for screen content, which is the one piece of context an agent choosing between these siblings would benefit from.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67% and the two documented parameters (cursor, remote with its SSH auth guidance) are already fully explained in the schema, so the description's only contribution is implying that session_id targets the session being observed. With the baseline-3 rule for high schema coverage and no added syntax or format detail, 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (observe) and enumerates exactly what is observed: session existence, pane/harness liveness, status and reason, native process identity, screen changes and CPU activity. The closing clause 'does not return screen body or raw argv' distinguishes it from the sibling pty_read without requiring the agent to open either schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The definition gives clear context on what this call is for (structured state/health observation) and an explicit exclusion (no screen text or raw argv), which steers agents away from using it as a content read. It does not, however, name pty_read or pty_list as the alternatives or state a when-to-use trigger explicitly, so routing is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pty_openA
ローカル永続端末(POSIXはtmux、Windows nativeはpsmux 3.3.8以上)を1個開き、session_id を返す。backend server常駐ゆえ本サーバや クライアントが再起動してもセッションは生存する。リモート操作は専用ツールにせず、開いた端末の中で pty_send(session_id, "ssh host") と打って入る。
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | セッション名(省略時は t1, t2... を自動採番) | |
| shell | No | 起動シェル(既定 bash) | bash |
| remote | No | 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。 | |
| env_vars | No | 現在のMCP processからsessionへ継承する環境変数名 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It discloses a non-obvious side effect—'backend server常駐ゆえ本サーバやクライアントが再起動してもセッションは生存する'—and explains that it creates a long-lived local terminal. It does not mention cleanup/leak implications, but the key behavioral trait (persistence) is explicitly surfaced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three dense sentences: first says what it does, second explains persistence, third gives the pty_send usage pattern. No filler or redundant restatement of the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Provides the key return value ('session_id を返す'), the persistence semantics, and a concrete follow-up usage pattern with pty_send. Schema covers all parameters. Minor gaps: no mention of cleanup via pty_close or resource limits, and no output schema exists to confirm response shape, but enough is present for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline applies. The description adds no parameter-specific meaning beyond mentioning session_id, but the schema already documents name, shell, remote, and env_vars with defaults and security notes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific opening action ('ローカル永続端末を1個開き') and the returned resource ('session_id を返す'). It also clarifies that remote access is achieved by running pty_send inside the opened terminal, distinguishing this create-session tool from the send/read siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives clear context: this terminal is persistent and survives server/client restarts, and instructs the agent to use pty_send(session_id, "ssh host") rather than a dedicated remote-operation tool. It does not explicitly compare against pty_list/pty_close or state when those should be used, so it falls just short of fully explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pty_readA
セッションの出力をトークン削減して読む(既定は前回読取位置からの増分)。削減: 制御文字除去 / 反復圧縮 / head+tail 折りたたみ+復元ヒント+メタ併記。agent_transcript:true は agent session の直近完了ターンの最終 assistant メッセージを公開されたharness記録から平文で返す。長い回答が screen tail で切れた時の回収用。
| Name | Required | Description | Default |
|---|---|---|---|
| raw | No | 削減せず生テキスト | |
| rtk | No | 直前コマンド別の自前 reducer(git/grep/pytest 等)で縮約 | |
| full | No | 増分でなく全文 | |
| wait | No | 完了まで待つ(dead / mark sentinel 自動検出 / until / 出力静止∧シェル復帰 / timeout) | |
| lines | No | 末尾 N 行のみ | |
| until | No | この文字列が出たら完了とみなす(既定はリテラル部分一致。`$ ` や `[..]` もそのまま探せる) | |
| remote | No | 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。 | |
| screen | No | 描画済みスクリーン(TUI 向け) | |
| timeout | No | wait の最大待ち秒数 | |
| line_range | No | 全文からの行範囲 "A:B" | |
| session_id | Yes | ||
| until_regex | No | until を正規表現として扱う(既定 false=リテラル部分一致。メタ文字を使いたい時のみ true) | |
| operation_id | No | Claude operationの期待ID。agent_transcript:true時だけ指定し、古い別operationの結果を拒否する | |
| agent_transcript | No | agent session の直近完了ターンの最終 assistant メッセージを返す。Claudeはlaunch相関付きStop hook result、他harnessは通常transcript/session historyを使う。長い回答がscreen tailで切れた時の回収用 |
Output Schema
| Name | Required | Description |
|---|---|---|
| mode | Yes | |
| text | Yes | |
| schema | Yes | |
| vendor | Yes | |
| harness | Yes | |
| turn_id | Yes | |
| raw_chars | Yes | |
| session_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does substantial work: it discloses the reduction transformations applied, that the default is an increment from the previous read offset (implying tracked state), and that agent_transcript reads from a published harness record in plaintext. It omits the safety/auth profile and whether reads mutate any state, so it stops short of full disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the core purpose, then the reduction mechanism, then the agent_transcript special case. It is dense and largely free of filler, though the parenthetical and slash-delimited lists make it slightly packed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fourteen parameters with a nested remote object and an output schema present, so return values need no explanation. The description covers the core read semantics, the reduction behavior and the agent_transcript recovery path, which is enough for correct invocation, though sibling disambiguation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 93%, so the schema already documents each parameter, including the reduction toggles and the nested remote object. The description explains what the reduction pipeline actually does, which marginally clarifies what raw/rtk/full toggle, but adds little parameter-specific syntax or format detail beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: read session output with token reduction, defaulting to incremental reads from the last read position. It describes the reduction pipeline concretely (control-char stripping, repetition compression, head+tail folding). It does not, however, explicitly distinguish itself from the closely named sibling pty_observe, leaving the boundary to inference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the mechanics: incremental by default, raw/rtk/full as overrides, and agent_transcript for recovering long answers truncated at the screen tail. That last clause is a genuine when-to-use hint. But there is no guidance on when to prefer this over pty_observe or pty_send, and no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pty_sendA
セッションへテキストを送る。通常PTYへは送信のみ(出力は pty_read で取得)。agent session(launcher起動)への送信はこのtoolだけで行い、子の状態はAitermが送る時点で見て振り分ける。子のturnが実行中なら各harness標準の操作で現在のturnへ差し込み(mode=agent_steer)、完了は差し込み後の作業の終わりに元の依頼への1回だけ届く。新しいevent_cursorと配送は作らない。それ以外は新しいturnとしてdispatchし(mode=agent_dispatch)、TUI の ready gate と submit 分離を通して即返り、receipt の event_cursor を返す。dispatch した子は投げっぱなしでよい=親はここで待たない。Codex親とClaude Code親にはAitermが回答本文を自動配送する。parent_deliveryがある場合はwait起動も通常の回答回収も不要。親は作業を続けるかターンを終える。Cursor親にはparent_deliveryとwait_processが付く。作業を続ければ次のツール返りに回答が差し込まれ、ターンを終える前にwait_processを背景で起動するとidle中の完了でも起きられる。ポーリングとpty_read(agent_transcript:true)は不要。その他の親では、完了通知をreceiptの wait_process.executable と wait_process.args をそのまま親のターンを塞がない別プロセスAPIへ渡して受け、PowerShell 7のStart-Processだけは windows_start_process_argument_list を単一文字列として渡す。exit を完了通知として扱う(exit 0=done / 3=timeout(既定600秒・未完了) / 4=closed / 7=error(harnessの記録でturnがAPIエラー等で打ち切られた。結果は無い)。receiptのoutcomeが正で、done以外は未完了。ポーリング不要)。wait_command は人間向け互換表示でありprocess境界へ使わない。foreground実行で親のターンを塞がない。自動配送以外の結果回収は pty_read(agent_transcript:true)、Claude の durable turn は claude_turn を使う。force:true は非Claude agent sessionへの手動介入用の素送信。aiterm相関付きClaudeの承認UIはclaude_approvalを使う。
| Name | Required | Description | Default |
|---|---|---|---|
| raw | No | 送信前サニタイズを無効化 | |
| rtk | No | 既知コマンドを rtk 形へ委譲して送る(rtk 不在なら素通し) | |
| mark | No | 完了 sentinel(終了コード付き)で包む。pty_read(wait:true) が until 無しでも自動検出して完了確定する(POSIX shell と PowerShell に対応。SSH先の現在の標準PS promptも自動判定。PowerShell の rc は成功0/失敗1。fish/csh/tcsh は未対応として送信前に拒否)。 enter:false と併用すると sentinel が実行されず完了検出が発火しない(送信後に pty_key("Enter") で実行される)。 | |
| text | Yes | 送る文字列(コマンド/prompt)。UTF-8で最大64KiB | |
| enter | No | 末尾で Enter を送る(agent dispatch では常に submit) | |
| force | No | 非Claude agent sessionでは自動dispatchせず素送信する。aiterm相関付きClaudeのactive turnには使えない | |
| image | No | 添付する画像ファイルの絶対パス(png/jpg/jpeg/gif/webp)。agent session への dispatch だけで使え、harness別の添付手順はaitermが吸収する。通常PTY送信やforce送信では指定できない | |
| remote | No | 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。 | |
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| mode | Yes | |
| schema | Yes | |
| vendor | Yes | |
| harness | Yes | |
| launch_id | Yes | |
| session_id | Yes | |
| event_cursor | Yes | |
| wait_process | Yes | |
| submit_residue | Yes | |
| parent_delivery | No | |
| pane_input_recovery | No |
TDQS
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 richly: it explains steer vs dispatch semantics, that dispatch is fire-and-forget with no waiting, the receipt/event_cursor mechanism, exit-code meanings (0=done, 3=timeout, 4=closed, 7=error), the default 600s timeout, and that polling is unnecessary. This is exactly the behavioral context annotations would otherwise provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is an unstructured wall of text combining purpose, routing, receipt mechanics, exit codes, and SSH notes with no headings or front-loading. Important guidance is present but hard for an agent to parse quickly; it is over-verbose rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 9-parameter tool with nested objects and a high-complexity async model, the description covers the critical operational paths (dispatch, steer, wait_process receipt, result retrieval, approval). It even explains receipt outcomes despite an output schema existing. Some detail is redundant or overwhelming, but nothing essential is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 89%, so the schema already documents params like raw, rtk, mark, enter, force, image, and remote in detail. The description adds only marginal param-specific meaning (mentions force as raw send for non-Claude agent sessions, image restricted to dispatch), so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The opening line states a specific verb and resource ('send text to a session') and immediately delineates the two modes (normal PTY send vs. agent-session dispatch/steer), so an agent can tell what the tool does without opening the schema. It is clear but heavily entangled with routing and behavioral detail, which dilutes the core statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly routes the agent: normal PTY output via pty_read, Claude durable turns via claude_turn, approval UI via claude_approval, result collection via pty_read(agent_transcript:true), and explains when force:true applies. Alternatives and conditions are named, though buried in a dense paragraph rather than presented as when/when-not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.49.0- Changed
pty_observe2 fields changed- added
Output schema / properties / activity / properties / post_startup_process_countAdded value: +{ + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] +} - added
Output schema / properties / pending_child_deliveriesAdded value: +{ + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ] +}
1 tool update
v0.46.1- Added
agent_auth
6 tool updates
v0.45.0- Changed
agent_configure1 field changed- changed
Output schema / properties / provider / enumPrevious value: -[ - "claude", - "codex", - "grok", - "composer", - "cursor" -]New value: +[ + "claude", + "codex", + "grok", + "cursor" +]
- Changed
agent_launch1 field changed- changed
Output schema / properties / provider / enumPrevious value: -[ - "claude", - "codex", - "grok", - "composer", - "cursor" -]New value: +[ + "claude", + "codex", + "grok", + "cursor" +]
- Added
agent_models - Removed
composer_agent - Changed
pty_read1 field changed- changed
Output schema / properties / vendor / anyOfPrevious value: -[ - { - "enum": [ - "claude", - "codex", - "grok", - "composer", - "cursor" - ], - "type": "string" - }, - { - "type": "null" - } -]New value: +[ + { + "enum": [ + "claude", + "codex", + "grok", + "cursor" + ], + "type": "string" + }, + { + "type": "null" + } +]
- Changed
pty_send1 field changed- changed
Output schema / properties / vendor / anyOfPrevious value: -[ - { - "enum": [ - "claude", - "codex", - "grok", - "composer", - "cursor" - ], - "type": "string" - }, - { - "type": "null" - } -]New value: +[ + { + "enum": [ + "claude", + "codex", + "grok", + "cursor" + ], + "type": "string" + }, + { + "type": "null" + } +]
13 tool updates
v0.39.1- Changed
agent_approval1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
agent_configure1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
agent_launch3 fields changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +} - added
Output schema / properties / remote_hostAdded value: +{ + "description": "別端末で起動した時の接続先", + "type": "string" +} - added
Output schema / properties / remote_versionAdded value: +{ + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "別端末のAiterm版" +}
- Removed
agent_steer - Changed
claude_approval1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
claude_turn1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
pty_close1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
pty_key1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
pty_list1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
pty_observe1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
pty_open1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
pty_read1 field changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +}
- Changed
pty_send2 fields changed- added
Input schema / properties / remoteAdded value: +{ + "additionalProperties": false, + "description": "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。", + "properties": { + "host": { + "pattern": "^(?!-)[A-Za-z0-9._%:\\[\\]-]{1,255}$", + "type": "string" + }, + "identity_file": { + "minLength": 1, + "type": "string" + }, + "passphrase": { + "minLength": 1, + "type": "string" + }, + "passphrase_env": { + "pattern": "^[A-Za-z_][A-Za-z0-9_]*$", + "type": "string" + }, + "port": { + "maximum": 65535, + "minimum": 1, + "type": "integer" + }, + "ssh_options": { + "items": { + "pattern": "^[A-Za-z][A-Za-z0-9]*=[^\\r\\n]*$", + "type": "string" + }, + "maxItems": 32, + "type": "array" + }, + "user": { + "pattern": "^(?!-)[A-Za-z0-9._@\\\\-]{1,128}$", + "type": "string" + } + }, + "required": [ + "host" + ], + "type": "object" +} - changed
Output schema / properties / mode / enumPrevious value: -[ - "sent", - "agent_dispatch" -]New value: +[ + "sent", + "agent_dispatch", + "agent_steer" +]
11 tool updates
v0.35.0- Added
agent_approval - Changed
agent_launch5 fields changed- added
Input schema / properties / trust_projectAdded value: +{ + "description": "対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める", + "type": "boolean" +} - added
Output schema / properties / initial_promptAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "not_requested", + "not_sent", + "submitted_unconfirmed", + "started" + ], + "type": "string" + }, + "turn_started": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "status", + "reason", + "turn_started" + ], + "type": "object" +} - added
Output schema / properties / parent_deliveryAdded value: +{ + "additionalProperties": false, + "properties": { + "child_outcome": { + "anyOf": [ + { + "enum": [ + "done", + "closed", + "rate_limited", + "error" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "child_turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "delivery_id": { + "type": "string" + }, + "error_code": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "queued_submission_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "state": { + "enum": [ + "waiting", + "ready", + "sending", + "submitted", + "failed", + "unknown" + ], + "type": "string" + } + }, + "required": [ + "delivery_id", + "state", + "child_outcome", + "child_turn_id", + "queued_submission_id", + "error_code" + ], + "type": "object" +} - added
Output schema / properties / startupAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "ready", + "not_checked", + "blocked" + ], + "type": "string" + } + }, + "required": [ + "status", + "reason" + ], + "type": "object" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "harness", - "provider", - "session_id", - "managed_completion", - "event_cursor", - "wait_process", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "initial_prompt", + "startup", + "harness", + "provider", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
claude_agent5 fields changed- added
Input schema / properties / trust_projectAdded value: +{ + "description": "対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める", + "type": "boolean" +} - added
Output schema / properties / initial_promptAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "not_requested", + "not_sent", + "submitted_unconfirmed", + "started" + ], + "type": "string" + }, + "turn_started": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "status", + "reason", + "turn_started" + ], + "type": "object" +} - added
Output schema / properties / parent_deliveryAdded value: +{ + "additionalProperties": false, + "properties": { + "child_outcome": { + "anyOf": [ + { + "enum": [ + "done", + "closed", + "rate_limited", + "error" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "child_turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "delivery_id": { + "type": "string" + }, + "error_code": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "queued_submission_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "state": { + "enum": [ + "waiting", + "ready", + "sending", + "submitted", + "failed", + "unknown" + ], + "type": "string" + } + }, + "required": [ + "delivery_id", + "state", + "child_outcome", + "child_turn_id", + "queued_submission_id", + "error_code" + ], + "type": "object" +} - added
Output schema / properties / startupAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "ready", + "not_checked", + "blocked" + ], + "type": "string" + } + }, + "required": [ + "status", + "reason" + ], + "type": "object" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_process", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "initial_prompt", + "startup", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
claude_turn1 field changed- added
Output schema / properties / parent_deliveryAdded value: +{ + "additionalProperties": false, + "properties": { + "child_outcome": { + "anyOf": [ + { + "enum": [ + "done", + "closed", + "rate_limited", + "error" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "child_turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "delivery_id": { + "type": "string" + }, + "error_code": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "queued_submission_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "state": { + "enum": [ + "waiting", + "ready", + "sending", + "submitted", + "failed", + "unknown" + ], + "type": "string" + } + }, + "required": [ + "delivery_id", + "state", + "child_outcome", + "child_turn_id", + "queued_submission_id", + "error_code" + ], + "type": "object" +}
- Changed
codex_agent5 fields changed- added
Input schema / properties / trust_projectAdded value: +{ + "description": "対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める", + "type": "boolean" +} - added
Output schema / properties / initial_promptAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "not_requested", + "not_sent", + "submitted_unconfirmed", + "started" + ], + "type": "string" + }, + "turn_started": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "status", + "reason", + "turn_started" + ], + "type": "object" +} - added
Output schema / properties / parent_deliveryAdded value: +{ + "additionalProperties": false, + "properties": { + "child_outcome": { + "anyOf": [ + { + "enum": [ + "done", + "closed", + "rate_limited", + "error" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "child_turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "delivery_id": { + "type": "string" + }, + "error_code": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "queued_submission_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "state": { + "enum": [ + "waiting", + "ready", + "sending", + "submitted", + "failed", + "unknown" + ], + "type": "string" + } + }, + "required": [ + "delivery_id", + "state", + "child_outcome", + "child_turn_id", + "queued_submission_id", + "error_code" + ], + "type": "object" +} - added
Output schema / properties / startupAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "ready", + "not_checked", + "blocked" + ], + "type": "string" + } + }, + "required": [ + "status", + "reason" + ], + "type": "object" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_process", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "initial_prompt", + "startup", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
composer_agent5 fields changed- added
Input schema / properties / trust_projectAdded value: +{ + "description": "対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める", + "type": "boolean" +} - added
Output schema / properties / initial_promptAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "not_requested", + "not_sent", + "submitted_unconfirmed", + "started" + ], + "type": "string" + }, + "turn_started": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "status", + "reason", + "turn_started" + ], + "type": "object" +} - added
Output schema / properties / parent_deliveryAdded value: +{ + "additionalProperties": false, + "properties": { + "child_outcome": { + "anyOf": [ + { + "enum": [ + "done", + "closed", + "rate_limited", + "error" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "child_turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "delivery_id": { + "type": "string" + }, + "error_code": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "queued_submission_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "state": { + "enum": [ + "waiting", + "ready", + "sending", + "submitted", + "failed", + "unknown" + ], + "type": "string" + } + }, + "required": [ + "delivery_id", + "state", + "child_outcome", + "child_turn_id", + "queued_submission_id", + "error_code" + ], + "type": "object" +} - added
Output schema / properties / startupAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "ready", + "not_checked", + "blocked" + ], + "type": "string" + } + }, + "required": [ + "status", + "reason" + ], + "type": "object" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_process", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "initial_prompt", + "startup", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
grok_agent5 fields changed- added
Input schema / properties / trust_projectAdded value: +{ + "description": "対象projectを信頼し、既知のworkspace・project hooks・MCP初期同意を起動中に進める", + "type": "boolean" +} - added
Output schema / properties / initial_promptAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "not_requested", + "not_sent", + "submitted_unconfirmed", + "started" + ], + "type": "string" + }, + "turn_started": { + "anyOf": [ + { + "type": "boolean" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "status", + "reason", + "turn_started" + ], + "type": "object" +} - added
Output schema / properties / parent_deliveryAdded value: +{ + "additionalProperties": false, + "properties": { + "child_outcome": { + "anyOf": [ + { + "enum": [ + "done", + "closed", + "rate_limited", + "error" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "child_turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "delivery_id": { + "type": "string" + }, + "error_code": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "queued_submission_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "state": { + "enum": [ + "waiting", + "ready", + "sending", + "submitted", + "failed", + "unknown" + ], + "type": "string" + } + }, + "required": [ + "delivery_id", + "state", + "child_outcome", + "child_turn_id", + "queued_submission_id", + "error_code" + ], + "type": "object" +} - added
Output schema / properties / startupAdded value: +{ + "additionalProperties": false, + "properties": { + "reason": { + "type": "string" + }, + "status": { + "enum": [ + "ready", + "not_checked", + "blocked" + ], + "type": "string" + } + }, + "required": [ + "status", + "reason" + ], + "type": "object" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_process", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "initial_prompt", + "startup", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
pty_list2 fields changed- added
Input schema / properties / env_keysAdded value: +{ + "description": "帰属確認用の非秘密環境変数名。指定したキーだけを返す", + "items": { + "type": "string" + }, + "type": "array" +} - changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "observed_at": { + "type": "string" + }, + "schema": { + "const": "aiterm.pty-list-result.v1", + "type": "string" + }, + "sessions": { + "items": { + "additionalProperties": false, + "properties": { + "attached": { + "type": "boolean" + }, + "current_command": { + "type": "string" + }, + "environment": { + "additionalProperties": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "propertyNames": { + "type": "string" + }, + "type": "object" + }, + "harness": { + "anyOf": [ + { + "enum": [ + "claude-code", + "codex-cli", + "grok-cli", + "cursor-cli" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "height": { + "type": "number" + }, + "session_id": { + "type": "string" + }, + "width": { + "type": "number" + } + }, + "required": [ + "session_id", + "current_command", + "attached", + "width", + "height", + "harness", + "environment" + ], + "type": "object" + }, + "type": "array" + } + }, + "required": [ + "schema", + "observed_at", + "sessions" + ], + "type": "object" +}
- Added
pty_observe - Changed
pty_open1 field changed- added
Input schema / properties / env_varsAdded value: +{ + "description": "現在のMCP processからsessionへ継承する環境変数名", + "items": { + "type": "string" + }, + "type": "array" +}
- Changed
pty_send2 fields changed- changed
Input schema / properties / mark / descriptionPrevious value: -"完了 sentinel(終了コード付き)で包む。pty_read(wait:true) が until 無しでも自動検出して完了確定する(POSIX shell と PowerShell に対応。PowerShell の rc は成功0/失敗1。fish/csh/tcsh は未対応として送信前に拒否)。 enter:false と併用すると sentinel が実行されず完了検出が発火しない(送信後に pty_key(\"Enter\") で実行される)。"New value: +"完了 sentinel(終了コード付き)で包む。pty_read(wait:true) が until 無しでも自動検出して完了確定する(POSIX shell と PowerShell に対応。SSH先の現在の標準PS promptも自動判定。PowerShell の rc は成功0/失敗1。fish/csh/tcsh は未対応として送信前に拒否)。 enter:false と併用すると sentinel が実行されず完了検出が発火しない(送信後に pty_key(\"Enter\") で実行される)。" - added
Output schema / properties / parent_deliveryAdded value: +{ + "additionalProperties": false, + "properties": { + "child_outcome": { + "anyOf": [ + { + "enum": [ + "done", + "closed", + "rate_limited", + "error" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "child_turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "delivery_id": { + "type": "string" + }, + "error_code": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "queued_submission_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "state": { + "enum": [ + "waiting", + "ready", + "sending", + "submitted", + "failed", + "unknown" + ], + "type": "string" + } + }, + "required": [ + "delivery_id", + "state", + "child_outcome", + "child_turn_id", + "queued_submission_id", + "error_code" + ], + "type": "object" +}
3 tool updates
v0.31.2- Changed
agent_launch1 field changed- added
Input schema / properties / imageAdded value: +{ + "description": "初手プロンプトへ添付する画像ファイルの絶対パス(png/jpg/jpeg/gif/webp)", + "items": { + "type": "string" + }, + "type": "array" +}
- Changed
agent_steer1 field changed- added
Input schema / properties / imageAdded value: +{ + "description": "添付する画像ファイルの絶対パス(png/jpg/jpeg/gif/webp)", + "items": { + "type": "string" + }, + "type": "array" +}
- Changed
pty_send2 fields changed- added
Input schema / properties / imageAdded value: +{ + "description": "添付する画像ファイルの絶対パス(png/jpg/jpeg/gif/webp)。agent session への dispatch だけで使え、harness別の添付手順はaitermが吸収する。通常PTY送信やforce送信では指定できない", + "items": { + "type": "string" + }, + "type": "array" +} - added
Output schema / properties / pane_input_recoveryAdded value: +{ + "items": { + "type": "string" + }, + "type": "array" +}
8 tool updates
v0.29.21- Changed
agent_launch1 field changed- added
Input schema / properties / throughline_supplement_fileAdded value: +{ + "description": "Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path", + "minLength": 1, + "type": "string" +}
- Added
agent_steer - Changed
claude_agent1 field changed- added
Input schema / properties / throughline_supplement_fileAdded value: +{ + "description": "Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path", + "minLength": 1, + "type": "string" +}
- Changed
codex_agent1 field changed- added
Input schema / properties / throughline_supplement_fileAdded value: +{ + "description": "Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path", + "minLength": 1, + "type": "string" +}
- Changed
composer_agent1 field changed- added
Input schema / properties / throughline_supplement_fileAdded value: +{ + "description": "Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path", + "minLength": 1, + "type": "string" +}
- Changed
grok_agent1 field changed- added
Input schema / properties / throughline_supplement_fileAdded value: +{ + "description": "Throughline 0.10.8以降へそのまま渡すproject束縛済み長期記憶・知識の補足JSON path", + "minLength": 1, + "type": "string" +}
- Changed
pty_read1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "$schema": "http://json-schema.org/draft-07/schema#", + "additionalProperties": false, + "properties": { + "harness": { + "anyOf": [ + { + "enum": [ + "claude-code", + "codex-cli", + "grok-cli", + "cursor-cli" + ], + "type": "string" + }, + { + "type": "null" + } + ] + }, + "mode": { + "enum": [ + "terminal", + "agent_transcript" + ], + "type": "string" + }, + "raw_chars": { + "anyOf": [ + { + "maximum": 9007199254740991, + "minimum": 0, + "type": "integer" + }, + { + "type": "null" + } + ] + }, + "schema": { + "const": "aiterm.pty-read-result.v1", + "type": "string" + }, + "session_id": { + "type": "string" + }, + "text": { + "type": "string" + }, + "turn_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + }, + "vendor": { + "anyOf": [ + { + "enum": [ + "claude", + "codex", + "grok", + "composer", + "cursor" + ], + "type": "string" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "schema", + "mode", + "session_id", + "text", + "vendor", + "turn_id", + "harness", + "raw_chars" + ], + "type": "object" +}
- Changed
pty_send1 field changed- changed
Input schema / properties / force / descriptionPrevious value: -"破壊的コマンドゲートを越える。非Claude agent sessionではdispatchせず素送信する。aiterm相関付きClaudeのactive turnには使えない"New value: +"非Claude agent sessionでは自動dispatchせず素送信する。aiterm相関付きClaudeのactive turnには使えない"
6 tool updates
v0.29.8- Changed
agent_launch2 fields changed- added
Output schema / properties / wait_processAdded value: +{ + "anyOf": [ + { + "additionalProperties": false, + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array" + }, + "executable": { + "type": "string" + }, + "windows_start_process_argument_list": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "executable", + "args", + "windows_start_process_argument_list" + ], + "type": "object" + }, + { + "type": "null" + } + ] +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "harness", - "provider", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "harness", + "provider", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
claude_agent2 fields changed- added
Output schema / properties / wait_processAdded value: +{ + "anyOf": [ + { + "additionalProperties": false, + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array" + }, + "executable": { + "type": "string" + }, + "windows_start_process_argument_list": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "executable", + "args", + "windows_start_process_argument_list" + ], + "type": "object" + }, + { + "type": "null" + } + ] +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
codex_agent2 fields changed- added
Output schema / properties / wait_processAdded value: +{ + "anyOf": [ + { + "additionalProperties": false, + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array" + }, + "executable": { + "type": "string" + }, + "windows_start_process_argument_list": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "executable", + "args", + "windows_start_process_argument_list" + ], + "type": "object" + }, + { + "type": "null" + } + ] +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
composer_agent2 fields changed- added
Output schema / properties / wait_processAdded value: +{ + "anyOf": [ + { + "additionalProperties": false, + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array" + }, + "executable": { + "type": "string" + }, + "windows_start_process_argument_list": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "executable", + "args", + "windows_start_process_argument_list" + ], + "type": "object" + }, + { + "type": "null" + } + ] +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
grok_agent2 fields changed- added
Output schema / properties / wait_processAdded value: +{ + "anyOf": [ + { + "additionalProperties": false, + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array" + }, + "executable": { + "type": "string" + }, + "windows_start_process_argument_list": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "executable", + "args", + "windows_start_process_argument_list" + ], + "type": "object" + }, + { + "type": "null" + } + ] +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "harness", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_process", + "wait_command", + "submit_residue" +]
- Changed
pty_send2 fields changed- added
Output schema / properties / wait_processAdded value: +{ + "anyOf": [ + { + "additionalProperties": false, + "properties": { + "args": { + "items": { + "type": "string" + }, + "type": "array" + }, + "executable": { + "type": "string" + }, + "windows_start_process_argument_list": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "executable", + "args", + "windows_start_process_argument_list" + ], + "type": "object" + }, + { + "type": "null" + } + ] +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "mode", - "session_id", - "event_cursor", - "launch_id", - "vendor", - "harness", - "submit_residue" -]New value: +[ + "schema", + "mode", + "session_id", + "event_cursor", + "wait_process", + "launch_id", + "vendor", + "harness", + "submit_residue" +]
8 tool updates
v0.28.0- Changed
agent_configure3 fields changed- added
Output schema / properties / harnessAdded value: +{ + "enum": [ + "claude-code", + "codex-cli", + "grok-cli", + "cursor-cli" + ], + "type": "string" +} - changed
Output schema / properties / provider / enumPrevious value: -[ - "claude", - "codex", - "grok", - "composer" -]New value: +[ + "claude", + "codex", + "grok", + "composer", + "cursor" +] - changed
Output schema / requiredPrevious value: -[ - "schema", - "session_id", - "provider", - "model", - "reasoning_effort" -]New value: +[ + "schema", + "session_id", + "provider", + "harness", + "model", + "reasoning_effort" +]
- Added
agent_launch - Changed
claude_agent2 fields changed- added
Output schema / properties / harnessAdded value: +{ + "const": "claude-code", + "type": "string" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_command", + "submit_residue" +]
- Changed
codex_agent3 fields changed- changed
Input schema / properties / write_scope / descriptionPrevious value: -"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codex/Grok/Composerのread-onlyはCLI sandboxで実効禁止する"New value: +"能力宣言。read-only、または書込みを許可するパスの説明文字列。対応harnessのread-onlyはCLI標準のread-only面で実効禁止する" - added
Output schema / properties / harnessAdded value: +{ + "const": "codex-cli", + "type": "string" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_command", + "submit_residue" +]
- Changed
composer_agent3 fields changed- changed
Input schema / properties / write_scope / descriptionPrevious value: -"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codex/Grok/Composerのread-onlyはCLI sandboxで実効禁止する"New value: +"能力宣言。read-only、または書込みを許可するパスの説明文字列。対応harnessのread-onlyはCLI標準のread-only面で実効禁止する" - added
Output schema / properties / harnessAdded value: +{ + "const": "grok-cli", + "type": "string" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_command", + "submit_residue" +]
- Changed
grok_agent3 fields changed- changed
Input schema / properties / write_scope / descriptionPrevious value: -"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codex/Grok/Composerのread-onlyはCLI sandboxで実効禁止する"New value: +"能力宣言。read-only、または書込みを許可するパスの説明文字列。対応harnessのread-onlyはCLI標準のread-only面で実効禁止する" - added
Output schema / properties / harnessAdded value: +{ + "const": "grok-cli", + "type": "string" +} - changed
Output schema / requiredPrevious value: -[ - "schema", - "provider", - "session_id", - "managed_completion", - "event_cursor", - "wait_command", - "submit_residue" -]New value: +[ + "schema", + "provider", + "harness", + "session_id", + "managed_completion", + "event_cursor", + "wait_command", + "submit_residue" +]
- Changed
pty_read1 field changed- changed
Input schema / properties / agent_transcript / descriptionPrevious value: -"agent session の直近完了ターンの最終 assistant メッセージを返す。Claudeはlaunch相関付きStop hook result、他vendorは通常transcriptを使う。長い回答がscreen tailで切れた時の回収用"New value: +"agent session の直近完了ターンの最終 assistant メッセージを返す。Claudeはlaunch相関付きStop hook result、他harnessは通常transcript/session historyを使う。長い回答がscreen tailで切れた時の回収用"
- Changed
pty_send3 fields changed- added
Output schema / properties / harnessAdded value: +{ + "anyOf": [ + { + "enum": [ + "claude-code", + "codex-cli", + "grok-cli", + "cursor-cli" + ], + "type": "string" + }, + { + "type": "null" + } + ] +} - changed
Output schema / properties / vendor / anyOfPrevious value: -[ - { - "enum": [ - "claude", - "codex", - "grok", - "composer" - ], - "type": "string" - }, - { - "type": "null" - } -]New value: +[ + { + "enum": [ + "claude", + "codex", + "grok", + "composer", + "cursor" + ], + "type": "string" + }, + { + "type": "null" + } +] - changed
Output schema / requiredPrevious value: -[ - "schema", - "mode", - "session_id", - "event_cursor", - "launch_id", - "vendor", - "submit_residue" -]New value: +[ + "schema", + "mode", + "session_id", + "event_cursor", + "launch_id", + "vendor", + "harness", + "submit_residue" +]
1 tool update
v0.27.9- Changed
pty_send1 field changed- changed
Input schema / properties / mark / descriptionPrevious value: -"完了 sentinel(終了コード付き)で包む。pty_read(wait:true) が until 無しでも自動検出して完了確定する(ネスト中や非シェル前面でも効く確実な完了検出。手で until を組む必要なし)。 enter:false と併用すると sentinel が実行されず完了検出が発火しない(送信後に pty_key(\"Enter\") で実行される)。"New value: +"完了 sentinel(終了コード付き)で包む。pty_read(wait:true) が until 無しでも自動検出して完了確定する(POSIX shell と PowerShell に対応。PowerShell の rc は成功0/失敗1。fish/csh/tcsh は未対応として送信前に拒否)。 enter:false と併用すると sentinel が実行されず完了検出が発火しない(送信後に pty_key(\"Enter\") で実行される)。"
5 tool updates
v0.27.0- Added
agent_configure - Changed
claude_agent1 field changed- added
Input schema / properties / env_varsAdded value: +{ + "description": "起動したagentへ現在のMCP processから継承する環境変数名。値はtool引数へ渡さない", + "items": { + "type": "string" + }, + "type": "array" +}
- Changed
codex_agent3 fields changed- added
Input schema / properties / env_varsAdded value: +{ + "description": "起動したagentへ現在のMCP processから継承する環境変数名。値はtool引数へ渡さない", + "items": { + "type": "string" + }, + "type": "array" +} - changed
Input schema / properties / reasoning_effort / descriptionPrevious value: -"reasoning effort(思考レベル)。low/medium/high/xhigh/max/ultra(CLI 版依存)。ultra は max 推論+proactive 自動委譲 ON=使用量急増注意(明示要求時のみ)。省略時は端末 config/CLI 既定。"New value: +"reasoning effort(思考レベル)。low/medium/high/xhigh/max/ultra(CLI/model 版依存)。ultra は max 推論+proactive 自動委譲 ON=使用量急増注意(明示要求時のみ)。省略時は端末 config/CLI 既定。" - changed
Input schema / properties / write_scope / descriptionPrevious value: -"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codexのread-onlyだけはCLI sandboxで実効禁止する"New value: +"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codex/Grok/Composerのread-onlyはCLI sandboxで実効禁止する"
- Changed
composer_agent4 fields changed- added
Input schema / properties / env_varsAdded value: +{ + "description": "起動したagentへ現在のMCP processから継承する環境変数名。値はtool引数へ渡さない", + "items": { + "type": "string" + }, + "type": "array" +} - changed
Input schema / properties / model / descriptionPrevious value: -"起動モデル。省略時は grok-composer-2.5-fast"New value: +"起動モデル。省略時は grok-composer-2.5-fast。既定/explicit modelを起動前にlive catalogへ照合し、不在ならfallbackせずエラー" - changed
Input schema / properties / reasoning_effort / descriptionPrevious value: -"指定不可(grok CLI の --effort は headless 専用で、対話 TUI では警告の上無視される。composer は effort 自体非対応)。指定すると起動前にエラーを返す"New value: +"Grok Build reasoning effort。利用可能値はCLI/modelのlive catalogに従う。省略時はCLI/model既定。" - changed
Input schema / properties / write_scope / descriptionPrevious value: -"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codexのread-onlyだけはCLI sandboxで実効禁止する"New value: +"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codex/Grok/Composerのread-onlyはCLI sandboxで実効禁止する"
- Changed
grok_agent4 fields changed- added
Input schema / properties / env_varsAdded value: +{ + "description": "起動したagentへ現在のMCP processから継承する環境変数名。値はtool引数へ渡さない", + "items": { + "type": "string" + }, + "type": "array" +} - changed
Input schema / properties / model / descriptionPrevious value: -"起動モデル。省略時は grok-4.5"New value: +"起動モデル。省略時は grok-4.6。explicit modelを起動前にlive catalogへ照合し、不在ならfallbackせずエラー" - changed
Input schema / properties / reasoning_effort / descriptionPrevious value: -"指定不可(grok CLI の --effort は headless 専用で、対話 TUI では警告の上無視される。composer は effort 自体非対応)。指定すると起動前にエラーを返す"New value: +"Grok Build reasoning effort。利用可能値はCLI/modelのlive catalogに従う。省略時はCLI/model既定。" - changed
Input schema / properties / write_scope / descriptionPrevious value: -"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codexのread-onlyだけはCLI sandboxで実効禁止する"New value: +"能力宣言。read-only、または書込みを許可するパスの説明文字列。Codex/Grok/Composerのread-onlyはCLI sandboxで実効禁止する"
TDQS
Scored across 18 tools
The pty_* session tools are clearly distinct, but the set contains three legacy launch aliases (claude_agent, codex_agent, grok_agent) that duplicate agent_launch(harness=...), and approval handling is split across agent_approval and claude_approval plus claude_turn. Descriptions explain the overlaps, but an agent must decide between parallel launch/approval paths that do nearly the same thing.
Predominantly consistent snake_case with meaningful prefixes (pty_*, agent_*, claude_*), which reads predictably. The deviation is the legacy per-harness names (claude_agent, codex_agent, grok_agent) that break the agent_launch pattern and the lone bare `diagnostics`.
18 tools is on the heavy side for the apparent scope, and three of them (claude_agent, codex_agent, grok_agent) are explicitly deprecated aliases of agent_launch, inflating the count without adding capability. The core PTY and agent lifecycle operations justify most of the surface, but it is heavier than necessary.
The domain (persistent terminal control plus agent orchestration) is well covered: open/send/read/key/close/list/observe for PTYs, and launch/configure/models/auth/approval/turn for agents. Minor gaps exist around session naming/attach or generic (non-Claude/Codex) approval handling, but agents can work around them.
Maintenance
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