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Codex-side supervisor tooling for safely delegating bounded coding tasks to ZCode.

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ZCode-supervisor

Version License Node Python

Codex-side tooling for using ZCode as a bounded coding worker while Codex stays the orchestrator and final auditor.

日本語版はこちら: README.ja.md を開く

This repository is not affiliated with Z.AI or ZCode.

Quick Start

The current public setup path is uvx from this GitHub repo:

uvx --from git+https://github.com/AkiGarage/ZCode-supervisor.git \
  zcode-install-repo /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO

After the first PyPI release, the shorter package command will be:

uvx --from zcode-supervisor zcode-install-repo /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO

Then check the routing decision before the first delegated task:

zcode-auto-route \
  --workspace /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO \
  --objective "setup smoke check"

For development from source, clone this repo and run the underlying Python command directly:

git clone https://github.com/AkiGarage/ZCode-supervisor.git
cd ZCode-supervisor
python3 tools/zcode_supervisor/zcode_supervisor.py install-repo \
  --repo /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO \
  --write-agents

The Homebrew tap is archived for now; clone AkiGarage/ZCode-supervisor for source work.

Release details and verification commands are in docs/distribution.md.

Ask Codex To Set It Up

If you want Codex to do the setup for you, copy this whole prompt into Codex. GitHub shows a copy button on the code block. Replace /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO with the absolute path to the repo you want ZCode to help edit.

You are Codex. Please set up ZCode-supervisor for this target repo:

TARGET_REPO=/ABSOLUTE/PATH/TO/YOUR/TARGET_REPO

Goal:
Make this target repo ready for the ZCode-supervisor workflow where Codex keeps
planning, orchestration, validation, audit, recovery, and final acceptance, and
ZCode only performs bounded implementation through zcodectl run-packet.

Rules:
- Be careful and non-destructive.
- Do not read or print secrets, .env files, credentials, API keys, private keys,
  or token files.
- Do not edit application source code in the target repo during setup.
- If TARGET_REPO is still a placeholder, stop and ask me for the real absolute
  path.
- If a required app or tool is missing, stop with the exact missing prerequisite
  and the next command or official link I should use.
- Do not push, commit, delete branches, or change production behavior.

Steps:
1. Confirm TARGET_REPO exists and is a git repository.
2. Prefer the public GitHub-backed `uvx` path. If `uvx --version` works, set
   INSTALLER_MODE=uvx and do not clone anything. If `uvx` is missing, show this
   official install link and continue with the source fallback:
   https://docs.astral.sh/uv/getting-started/installation/
3. For source fallback only, find this ZCode-supervisor repo locally. Prefer
   ~/dev/ZCode-supervisor if it exists. Set SUPERVISOR_REPO to the real absolute
   path. If it is not present, clone it with:
   mkdir -p ~/dev
   git clone https://github.com/AkiGarage/ZCode-supervisor.git ~/dev/ZCode-supervisor
   If clone fails, stop and report the exact error.
4. Verify local basics:
   - node --version must be >= 22
   - python3 --version must be >= 3.11
   - git --version must work
5. Verify ZCode is installed or give me this official install link:
   https://zcode.z.ai/en/docs/install
6. Run the target repo installer from Terminal or shell. If INSTALLER_MODE=uvx:
   uvx --from git+https://github.com/AkiGarage/ZCode-supervisor.git \
     zcode-install-repo "$TARGET_REPO"
   Otherwise run the source fallback:
   python3 "$SUPERVISOR_REPO/tools/zcode_supervisor/zcode_supervisor.py" install-repo \
     --repo "$TARGET_REPO" \
     --write-agents
7. Verify these files now exist inside TARGET_REPO:
   - .codex/zcode-routing.json
   - .codex/ZCODE_DELEGATION.md
   - .agents/mcp.json
   - AGENTS.md
8. Run a dry route check. If INSTALLER_MODE=uvx:
   uvx --from git+https://github.com/AkiGarage/ZCode-supervisor.git \
     zcode-auto-route \
     --workspace "$TARGET_REPO" \
     --objective "setup smoke check"
   Otherwise run:
   python3 "$SUPERVISOR_REPO/tools/zcode_supervisor/zcode_supervisor.py" auto-route \
     --workspace "$TARGET_REPO" \
     --objective "setup smoke check"
9. If possible, run preflight. If INSTALLER_MODE=uvx:
   uvx --from git+https://github.com/AkiGarage/ZCode-supervisor.git \
     zcodectl cli-preflight
   uvx --from git+https://github.com/AkiGarage/ZCode-supervisor.git \
     zcodectl vision-preflight --workspace "$TARGET_REPO"
   Otherwise run:
   node "$SUPERVISOR_REPO/tools/zcode_control/zcodectl.mjs" cli-preflight
   node "$SUPERVISOR_REPO/tools/zcode_control/zcodectl.mjs" vision-preflight --workspace "$TARGET_REPO"
10. Report:
   - what was written
   - commands run
   - pass/fail result for each check
   - anything I still need to do manually
   - the exact command I should use for the first real delegated task

Success means the target repo has routing files installed, a dry route check
works, and I understand any remaining manual prerequisite.

Setup Guide: Set Up One Target Repo

Use this section when you are starting from zero. The goal is to mark one existing repository as a place where Codex can plan and audit while ZCode does bounded implementation work.

0. Know The Two Repositories

  • This repo: ZCode-supervisor. It contains the supervisor tools.
  • Target repo: the repo you want ZCode to help edit. This is the path you pass to zcode-install-repo.

/path/to/target-repo is a placeholder. Replace it with the absolute path to your own target repo, such as:

~/work/my-app

You can get the absolute path by opening Terminal, moving into the target repo, and running:

pwd

1. Put This Supervisor Repo On Disk

If you are reading this on GitHub and do not have the repo locally yet, clone it first:

git clone https://github.com/AkiGarage/ZCode-supervisor.git
cd ZCode-supervisor
pwd

The pwd output is the absolute path to this supervisor repo. If your clone is not at ~/dev/ZCode-supervisor, replace that path in examples with your own supervisor repo path.

2. Install The Required Apps And Tools

Install and sign in to ZCode first:

Minimum local tools:

  • ZCode desktop app installed and connected to a model provider.
  • Node.js >=22.
  • Python >=3.11.
  • Git.
  • A POSIX-like shell such as the default macOS Terminal shell.
  • Network access to the configured model provider.

Check the local basics:

node --version
python3 --version
git --version

3. Run The Installer From Terminal

Run this in Terminal. You may run it from any current folder, because the target repo is provided as an absolute path:

zcode-install-repo /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO

Example:

zcode-install-repo ~/work/my-app

This command is setup only. Run it once per target repo; it is not a per-task command.

If zcode-install-repo is not found, run the supervisor command directly from this repo:

python3 /absolute/path/to/ZCode-supervisor/tools/zcode_supervisor/zcode_supervisor.py install-repo \
  --repo /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO \
  --write-agents

If your supervisor repo lives somewhere else, replace /absolute/path/to/ZCode-supervisor with the absolute path from pwd in step 1.

Primary Install Path

The current public setup path is uvx from this GitHub repo:

uvx --from git+https://github.com/AkiGarage/ZCode-supervisor.git \
  zcode-install-repo /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO

After the first PyPI release, the shorter package command will be:

uvx --from zcode-supervisor zcode-install-repo /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO

The PyPI package is published through Trusted Publishing, without long-lived PyPI tokens. High-assurance users can also download the GitHub Release archive, verify SHA256SUMS, and run gh attestation verify before using it. Homebrew is archived for now; see docs/distribution.md.

4. Confirm What Was Written

The installer writes these files inside the target repo:

  • .codex/zcode-routing.json
  • .codex/ZCODE_DELEGATION.md
  • .agents/mcp.json
  • AGENTS.md pointer text, when --write-agents is used

The important rule is simple: Codex keeps planning, orchestration, validation, audit, recovery, and final acceptance. ZCode only handles bounded implementation through zcodectl run-packet.

5. Check The Route Before Editing

Use a dry run before implementation work:

zcode-auto-route \
  --workspace /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO \
  --objective "Fix the failing ledger summary test."

Typical results:

  • needs_codex_planning: Codex should choose allowed files and validation.
  • delegate_zcode: the task is ready to run through ZCode.
  • codex_direct: Codex can handle it directly.
  • ask_user: pause because the task is high risk.

6. Run A Real Delegated Task

After Codex has chosen a tight edit scope and validation command:

zcode-auto-route \
  --workspace /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO \
  --objective "Fix the failing ledger summary test." \
  --allowed src/ledger.js \
  --validation "npm test" \
  --execute

Use --allowed for files ZCode may edit. Use --validation for the command Codex will trust as the first safety check. Keep both narrow.

Troubleshooting The First Run

  • command not found: zcode-install-repo: use the direct python3 ... install-repo command shown above, or add this repo's scripts/ directory to your PATH.
  • repo does not exist: replace the placeholder with the exact absolute path from pwd.
  • ZCode cannot run prompts: open ZCode once, sign in, configure the provider, then run node tools/zcode_control/zcodectl.mjs cli-preflight from this repo.
  • Vision or screenshot tasks fail preflight: run node tools/zcode_control/zcodectl.mjs vision-preflight --workspace /ABSOLUTE/PATH/TO/YOUR/TARGET_REPO.

Repository Snapshot

  • Current version: v0.0.1
  • Primary use case: delegate bounded coding tasks to ZCode/GLM while Codex keeps planning, guardrails, validation, and final review.
  • Main command path: node tools/zcode_control/zcodectl.mjs run-packet
  • Responsibility split: isolate workspaces, snapshot before execution, audit changes after execution, and reject unsafe or out-of-scope diffs.
  • Best for: low-babysitting AI coding workflows, reproducible tool comparisons, token/quota-aware delegation, and supervised benchmark runs.

Start Here

What This Provides

  • zcode_supervisor: creates task packets, snapshots workspaces, and audits ZCode changes after execution.
  • zcodectl: CLI-first controller for the bundled ZCode headless CLI, with optional Electron CDP helpers for desktop inspection.
  • Workspace-local ZCode templates for AGENTS.md, quality gates, parallel work, and Skill-friendly operating playbooks.
  • Small benchmark fixtures and tests for the supervisor/audit workflow.
  • A GLM-5.2/ZCode operating playbook for long-horizon coding, root-cause analysis, production-grade standards checks, and token-efficient delegation.
  • Optional repo-local Codex usage hook shim that records session starts/stops through codex-usage-ledger when configured, with local pending JSONL fallback when the central ledger is unavailable.

Version

Current release: v0.0.1

Distribution and release preparation: docs/distribution.md

How Codex And ZCode Share Responsibility

This project is built around a simple responsibility split:

  • Codex decides the plan, allowed files, validation command, audit result, and final acceptance.
  • ZCode does only the bounded implementation work Codex explicitly delegates.

The intended workflow is:

  1. Codex creates a compact task packet.
  2. Codex snapshots the workspace.
  3. ZCode works inside an isolated workspace or worktree.
  4. Codex runs the supervisor audit.
  5. Codex independently reviews and accepts or rejects the result.

Full access should only be used in disposable workspaces or isolated worktrees. Packet creation blocks regular-workspace Full access by default and rejects obviously destructive validation commands. The supervisor audit rejects forbidden edits, changes outside the allowed file set, optional changed file count overages, validation failures, workspace mismatches, and secret-like content in changed files.

Command Reference After Setup

The examples in this section use shorter placeholder paths. Replace every /path/to/target-repo or /path/to/repo with the absolute path to your real target repo, just like in the Setup Guide above.

Install repo-local routing hints in a target repository:

zcode-install-repo /path/to/target-repo

Run this once per target repo. It is setup, not a per-task command.

This writes .codex/zcode-routing.json, .codex/ZCODE_DELEGATION.md, and .agents/mcp.json in the target repo. It also adds a small AGENTS.md pointer so Codex knows the default split: Codex plans, orchestrates, audits, validates, and final-accepts; ZCode handles only bounded implementation through zcodectl run-packet. The MCP file enables the recommended zai-mcp-server stdio entry for vision packets without writing API keys into the repository. Re-run with --force only when you intentionally want to refresh generated files or replace an existing zai-mcp-server entry.

If the PATH wrapper is unavailable, use the underlying command:

python3 /path/to/ZCode-supervisor/tools/zcode_supervisor/zcode_supervisor.py install-repo \
  --repo /path/to/target-repo \
  --write-agents

Auto Routing

Installed repos default to routing_mode: auto. Future Codex sessions should run the route check before implementation edits:

zcode-auto-route \
  --workspace /path/to/target-repo \
  --objective "Fix the failing ledger summary test."

This check is optional when you already know the task should run through ZCode; it is mainly a dry-run for inspecting the route decision. You do not need to run all three setup/check/execute commands for every task:

  • First-time setup: run zcode-install-repo /path/to/target-repo once.
  • Route inspection: run zcode-auto-route --workspace ... --objective ... when you want to see the JSON decision.
  • Real delegated implementation: run zcode-auto-route ... --allowed ... --validation ... --execute after Codex has selected the file scope and validation command.

If the user explicitly says "use ZCode", "have ZCode do it", or similar, Codex should treat that as an instruction to use this ZCode-supervisor flow for bounded implementation work. Codex still owns planning, orchestration, validation, audit, recovery, and final acceptance.

The router returns JSON so Codex can proceed without asking for routine decisions:

  • delegate_zcode: create a packet and run ZCode.
  • needs_codex_planning: Codex must choose a tight allowed-file set and validation command, then rerun with --execute.
  • codex_direct: Codex may handle the task directly because it is read-only, trivial, missing routing config, or explicitly marked no-zcode.
  • ask_user: pause for a short plan because the task matches a high-risk category such as destructive changes, migrations, credentials, production, or money-sensitive work.

For normal implementation after Codex has selected allowed files and validation:

zcode-auto-route \
  --workspace /path/to/target-repo \
  --objective "Fix the failing ledger summary test." \
  --allowed src/ledger.js \
  --validation "npm test" \
  --execute

--execute creates the packet, calls zcodectl run-packet, writes run results under .codex/zcode/runs/, and keeps Codex responsible for final acceptance. This is intentionally a smart default rather than a hard lock: high-risk, read-only, trivial, and no-zcode tasks do not get forced through ZCode.

Create a task packet:

python3 tools/zcode_supervisor/zcode_supervisor.py packet \
  --workspace benchmarks/zcode-goal-mode \
  --objective "Fix summarizeLedger so npm test passes." \
  --allowed src/ledger.js \
  --forbidden test/ledger.test.js \
  --validation "npm test" \
  --effort max \
  --task-class root-cause \
  --risk-budget low \
  --max-changed-files 1 \
  --goal \
  --out .local/packets/ledger.json \
  --prompt-out .local/packets/ledger.prompt.txt

Snapshot the workspace:

python3 tools/zcode_supervisor/zcode_supervisor.py snapshot \
  --workspace benchmarks/zcode-goal-mode \
  --out .local/snapshots/ledger.before.json

After ZCode runs, audit the result:

python3 tools/zcode_supervisor/zcode_supervisor.py audit \
  --workspace benchmarks/zcode-goal-mode \
  --snapshot .local/snapshots/ledger.before.json \
  --packet .local/packets/ledger.json

Requirements And Control Surfaces

This toolkit does not require Codex Computer Use. The preferred automation path is the ZCode headless CLI bundled inside the ZCode desktop app:

Codex or a normal terminal
  -> node tools/zcode_control/zcodectl.mjs
  -> ZCode bundled CLI
  -> ZCode / GLM task execution

Control surface priority:

  1. ZCode bundled headless CLI, recommended and required for headless delegation. cli-prompt and run-packet use this path. It is the path validated by this project on macOS with ZCode 3.1.2.
  2. cua-driver plus Electron CDP, optional. cua-driver is an MIT-licensed background computer-use driver from the Cua project: https://cua.ai/docs/cua-driver/guide/getting-started/introduction When available, GUI helpers can use this kind of desktop-control surface to inspect visible text, take screenshots, click buttons, and read visible Usage Stats without making it the primary delegation path. Thanks to the Cua authors for the computer-use driver work; this project uses that capability only as an optional diagnostic/control surface.
  3. Codex Computer Use, optional fallback only. It can operate the GUI when available, but this repository does not depend on it and does not require it for the primary workflow.

Minimum local tooling:

  • ZCode desktop app installed and connected to a model provider.
  • Node.js >=22.
  • Python >=3.11.
  • Git and a POSIX-like shell for scripts/check.sh.
  • Network access to the configured model provider.

The latest official ZCode install docs list these supported platforms:

  • macOS on Apple Silicon and Intel.
  • Windows.
  • Linux through the Linux beta group.

See the official ZCode install docs: https://zcode.z.ai/en/docs/install

Project support status:

Platform Status Notes
macOS Tested ZCode 3.1.2, bundled CLI path /Applications/ZCode.app/Contents/Resources/glm/zcode.cjs, bundled CLI version 0.14.8, GUI config path ~/.zcode/v2/config.json, CLI config path ~/.zcode/cli/config.json.
Windows Expected, not verified ZCode is officially supported and 3.1.2 adds Windows shell selection, but this project still needs Windows-specific CLI path discovery and shell validation. Set ZCODE_CLI_PATH if auto-detection does not find the bundled CLI.
Linux Expected/beta, not verified ZCode Linux packages are distributed through the official beta group, but this project has not validated Linux CLI paths, desktop launch, or config discovery yet. Set ZCODE_CLI_PATH, --source-config, and --cli-config as needed.

bootstrap-cli-config can copy a local ZCode GUI Coding Plan API key into the ZCode CLI config with 0600 permissions and redacted output. On non-macOS systems, pass explicit config paths if the defaults do not match the installed ZCode layout:

node tools/zcode_control/zcodectl.mjs bootstrap-cli-config \
  --provider zai \
  --model glm-5.2 \
  --source-config /path/to/gui/config.json \
  --cli-config /path/to/cli/config.json

ZCode Desktop Control

zcodectl is intentionally small and experimental. Its primary path is the bundled ZCode headless CLI. Its GUI helpers expect ZCode to be available as a desktop app and use Electron CDP after launch.

For ZCode 3.1.2 and later, prefer the bundled headless CLI when it is available:

node tools/zcode_control/zcodectl.mjs cli-path
node tools/zcode_control/zcodectl.mjs cli-preflight
node tools/zcode_control/zcodectl.mjs bootstrap-cli-config \
  --provider zai \
  --model glm-5.2
node tools/zcode_control/zcodectl.mjs cli-doctor
node tools/zcode_control/zcodectl.mjs run-packet \
  --packet .local/packets/ledger.json \
  --mode plan \
  --max-attempts 2 \
  --retry-delay-ms 60000 \
  --usage-snapshot-source auto \
  --out .local/runs/ledger.zcode.json

run-packet sends the supervisor-generated packet prompt to the bundled ZCode CLI with the packet workspace as --cwd. It avoids GUI/CDP fragility and is the preferred Codex control path for headless delegation. If the CLI config is not ready, cli-prompt and run-packet try to bootstrap it from the local ZCode desktop GUI config before sending the prompt. Pass --no-bootstrap to disable that behavior. Use cli-prompt for ad-hoc prompts:

run-packet treats ZCode provider overload as structured supervisor state. It classifies ProviderBusinessError, provider code 1305, temporary overload messages, and CLI exit code 143. Every attempt is audited by the Codex-side supervisor after the ZCode turn, so validation does not depend on ZCode's internal Bash/tool permission client. The result returns supervisor_state:

  • success: CLI completed normally and supervisor audit plus validation passed.
  • audit_failed: CLI completed normally, but supervisor audit or validation failed.
  • partial_success: provider error happened after scoped changes, and audit plus validation passed.
  • retryable_provider_error: provider error happened with no file changes.
  • unsafe_partial: provider error happened with changed files that failed scope, validation, or safety checks.

Safe no-change provider errors retry up to --max-attempts with --retry-delay-ms cooldown. Changed files are never blindly retried; they are audited first. The JSON result includes cli_ok, provider_error, provider_code, provider_message, provider_id, provider_kind, usage_available, attempts, retry_count, retry_delays_ms, safe_to_retry_later, partial_artifacts_possible, audit, validation, validation_ok, and compact attempt_results.

run-packet also captures before/after usage snapshots. The default --usage-snapshot-source auto first calls the Z.AI quota API directly using ZAI_API_KEY, launchctl getenv ZAI_API_KEY, or the local redacted ZCode CLI config as the credential source. The API key is never written to result JSON or logs. If the direct API snapshot is unavailable, auto falls back to the CodexBar CLI:

codexbar usage --provider zai --format json

CodexBar.app does not need to be running for either path. The snapshot is non-fatal: if both direct API and CodexBar CLI capture are missing or unavailable, task execution continues and the JSON records the snapshot error. When capture succeeds, the JSON includes:

  • usage_snapshots.before and usage_snapshots.after: raw provider snapshots plus normalized quota windows. Direct Z.AI API snapshots use source: "zai-api"; CodexBar snapshots use source: "codexbar".
  • usage_accounting.tokens_*: consumed token fields normalized from the ZCode CLI JSON usage payload for this run.
  • usage_accounting.quota_percent_*: before, after, and delta for the primary used-percent quota window. quota_percent_direction is used.
  • Direct Z.AI TOKENS_LIMIT.percentage is treated as the measured used-percent value even when the same window omits finite usage and remaining token counts. The normalized window records token_counts_available separately, so percent deltas remain available without inventing token-count deltas.
  • usage_accounting.quota_windows: per-window deltas, including reset-change detection so a quota-window reset is not misreported as negative usage.

Use --usage-snapshot-source zai-api to require direct Z.AI API capture, --usage-snapshot-source codexbar to require CodexBar CLI capture, or --usage-snapshot-source none to disable snapshot capture. Use --usage-provider zai to make the provider explicit. --zai-quota-url can point at a custom Z.AI-compatible quota endpoint for tests. --codexbar-path or the CODEXBAR_PATH environment variable can point at a custom CodexBar CLI path.

node tools/zcode_control/zcodectl.mjs cli-prompt \
  --workspace benchmarks/zcode-goal-mode \
  --mode plan \
  --text "Review this fixture and report the failing test cause." \
  --out .local/runs/review.json

bootstrap-cli-config reads the local ZCode GUI config, finds an existing Coding Plan API key, and writes the CLI-native config at ~/.zcode/cli/config.json with 0600 permissions. Secret values are copied locally and are not printed in command output. The default provider is zai and the default model is glm-5.2.

cli-preflight checks the CLI binary, model selection, and whether a Coding Plan API key is configured. It redacts secret values and reports prompt_ready=true when headless prompts can run.

Image And Vision Tasks

GLM-5.2 is treated as text-only in this supervisor. For image understanding, use ZCode's built-in image service through the recommended zai-mcp-server MCP service, then attach workspace-local images through the packet:

python3 tools/zcode_supervisor/zcode_supervisor.py packet \
  --workspace benchmarks/zcode-goal-mode \
  --objective "Implement the UI state shown in the screenshot." \
  --allowed src/ledger.js \
  --validation "npm test" \
  --vision-image screenshots/state.png \
  --vision-color-sample primary=screenshots/state.png@240,420 \
  --out .local/packets/vision.json

--vision-image marks image understanding as required and stores the image paths in the packet. run-packet automatically forwards those paths to the ZCode CLI as repeated --attach arguments. Before running a required vision packet, run-packet checks redacted ZCode MCP configuration for the preferred image service and stops with vision_service_unavailable if it is missing, instead of letting the worker guess from filenames or text.

Use --vision-color-sample name=image.png@x,y when a task needs pixel-exact hex colors. The supervisor reads that PNG pixel locally and injects the exact uppercase #RRGGBB value into the worker prompt, while ZCode still handles the broader image understanding. The sampler is intentionally narrow: workspace local, non-secret, non-interlaced 8-bit RGB/RGBA PNG files.

You can check the image-service setup directly:

node tools/zcode_control/zcodectl.mjs vision-preflight \
  --workspace benchmarks/zcode-goal-mode

zcode-install-repo /path/to/repo writes .agents/mcp.json with the recommended stdio server:

{
  "mcpServers": {
    "zai-mcp-server": {
      "args": ["-y", "@z_ai/mcp-server"],
      "command": "npx",
      "enable": true,
      "type": "stdio"
    }
  }
}

The relevant ZCode docs describe zai-mcp-server as the recommended MCP server for visual understanding of images, screenshots, and interface context: https://zcode.z.ai/en/docs/mcp-services

The npm package that provides the zai-mcp-server binary is @z_ai/mcp-server. It expects Z_AI_API_KEY; for required vision packets, run-packet passes an available key to the ZCode child process from the current environment, ZAI_API_KEY, or the local ZCode CLI config without printing the secret value. Pixel-exact color sampling should still be verified with a deterministic image tool when exact hex values matter; generic vision can be close but not always exact.

The GUI/CDP helpers remain available for inspecting the desktop app and reading visible Settings usage when CDP is exposed:

Example:

node tools/zcode_control/zcodectl.mjs launch --port 9223
node tools/zcode_control/zcodectl.mjs targets --port 9223
node tools/zcode_control/zcodectl.mjs goal --port 9223 --text-file .local/packets/ledger.prompt.txt

If ZCode is already running without a debug port, use node tools/zcode_control/zcodectl.mjs launch --port 9223 --new-instance and check that the launch output includes "cdp": {"ok": true, ...} before running targets, usage, or goal.

Do not send secrets through zcodectl eval or prompt files.

Usage, Token, And Quota Logging

For every delegated ZCode task, capture Usage Stats before and after the run, then append the result to the evaluation ledger.

The current ZCode Usage Stats docs split usage into App Usage for local session records and Coding Plan for remote Z.ai / BigModel quota, GLM-5.2 and GLM-5-Turbo model usage, and MCP tool-call usage. Treat quota snapshots as time-sensitive evidence and keep the raw snapshot beside the normalized eval record.

node tools/zcode_control/zcodectl.mjs open-usage --port 9223
node tools/zcode_control/zcodectl.mjs usage --port 9223 --out .local/usage/ledger.before.json

# Run the ZCode task.

node tools/zcode_control/zcodectl.mjs open-usage --port 9223
node tools/zcode_control/zcodectl.mjs usage --port 9223 --out .local/usage/ledger.after.json

python3 tools/zcode_eval/zcode_eval.py append-result \
  --run-id zcode-ledger-001 \
  --tool zcode \
  --task-id ledger \
  --task-name "Ledger fixture" \
  --status pass \
  --validation "npm test: pass" \
  --usage-before .local/usage/ledger.before.json \
  --usage-after .local/usage/ledger.after.json

append-result records tokens_before, tokens_after, tokens_used, quota_percent_before, quota_percent_after, and quota_percent_used. By default, quota percent is treated as remaining quota, so consumed quota is derived as before minus after. If the visible UI is a used-percent counter, pass --quota-percent-direction used.

When recording a provider-error run, append-result also accepts optional metadata: --supervisor-state, --provider-error, --provider-code, --provider-message, --provider-id, --provider-kind, --attempts, --retry-count, --retryable-provider-error, --partial-artifacts-possible, --safe-to-retry-later, and --usage-available / --no-usage-available.

If ZCode does not expose CDP in the current session, you can still record the same fields explicitly:

python3 tools/zcode_eval/zcode_eval.py append-result \
  --run-id zcode-ledger-001 \
  --tool zcode \
  --task-id ledger \
  --task-name "Ledger fixture" \
  --status pass \
  --tokens-before 1000 \
  --tokens-after 1450 \
  --quota-percent-before 88.5 \
  --quota-percent-after 87.0

Review logs later with:

python3 tools/zcode_eval/zcode_eval.py show-log
python3 tools/zcode_eval/zcode_eval.py summarize

External duel runs can be imported into the same JSONL ledger. The importer reads results.json plus adjacent _control/zcode/*/zcode-result.json files when available, so provider overload rows keep provider_code, retryability, partial-artifact status, usage availability, and quota unavailable reasons:

python3 tools/zcode_eval/zcode_eval.py import-duel-results \
  --source /path/to/ClaudeCodeGLM-supervisor/work/supervisor_duel_eval/runs/20260617-153042/results.json \
  --path artifacts/evals/zcode-vs-claude.jsonl

ZCode Release Monitoring

ZCode compatibility is pinned against config/zcode-release-baseline.json. Check the official changelog manually with:

python3 tools/zcode_eval/zcode_release.py check \
  --baseline config/zcode-release-baseline.json \
  --include-installed

The GitHub Actions workflow .github/workflows/zcode-release-monitor.yml runs the same release check on a schedule. When the official ZCode version is newer than the baseline, it runs bash scripts/check.sh and opens or updates a GitHub Issue with the release notes and follow-up checklist.

Templates

Copy templates/zcode-codex-system/ into a disposable workspace or worktree to give ZCode:

  • a bounded worker contract via AGENTS.md
  • Skill-friendly playbooks and a quality gate
  • a parallel-work playbook
  • a GLM-5.2 operating profile for choosing task class, effort, and context strategy

Current ZCode docs say user-defined custom subagents are not supported yet. Use the built-in read-only Explore subagent for broad code research, and use Skills or Commands for reusable worker behavior. The legacy .zcode/cli/agents/ template files are retained only as draft role prompts, not as an advertised ZCode runtime feature.

GLM-5.2 Operating Defaults

  • Use effort=max for long-horizon implementation, cross-module debugging, architecture mapping, production-grade standards checks, and mobile/debugging loops.
  • Use effort=high for cheap probes, narrow reviews, and small repairs where speed matters more than deep search.
  • Treat 1M context as durable architectural memory, not a reason to dump every file into every task.
  • Use /goal only with objective acceptance criteria and an exact validation command.
  • Use --max-changed-files when the expected diff is small, so broad edits fail the audit automatically.
  • Use --workspace-kind fixture|worktree|disposable before Full Access; regular workspaces are blocked by default.
  • Keep Codex as final auditor even when ZCode completes the task.

See the GLM-5.2 ZCode Operator Guide: English / 日本語.

Development

Run the full local check:

bash scripts/check.sh

The project uses only the Python and Node standard libraries for its core checks.

Roadmap

See ROADMAP.md for planned benchmark work.

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