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Zcode Delegate

CommunityPopular
amElnagdy
zcode-delegate

Delegate a coding task to the Z.AI ZCode CLI as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to ZCode — phrasings like "have ZCode do X", "delegate this to ZCode", "run it through ZCode", or "use ZCode to implement/fix/refactor" — or to run a queue of coding tasks through ZCode while staying the reviewer. DO NOT USE for tasks small enough to do inline, or when the user wants the code written directly without delegating.

Overview

PublisheramElnagdy
Repositorydelegate-skills
Skill namezcode-delegate
Stars
2.1K
Forks
167
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by amElnagdy on GitHub. Read the source before you install it.

Installation

Install the Zcode Delegate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/amElnagdy/delegate-skills.git /tmp/delegate-skills
mkdir -p .claude/skills
cp -r /tmp/delegate-skills/skills/zcode-delegate .claude/skills/zcode-delegate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Zcode Delegate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Zcode Delegate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Zcode Delegate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ZCode Delegate

You are the orchestrator. This skill lets you hand a bounded coding task to a separate implementer — the Z.AI ZCode CLI — then review what it produced and land it yourself. You write the brief and own the judgment; ZCode does the typing; you verify and commit.

Nothing here is specific to one orchestrating agent. The loop needs only the ability to run a shell command and read a file. (It is designed for and run on Claude Code; treat other orchestrators as designed-for, not yet proven.)

When NOT to use this

  • The task is small enough to just do inline — delegation overhead is not worth it.
  • ZCode is not installed, or its CLI has no model provider configured.
  • You want to write the code yourself, or you only need a review.

Prerequisites (check once)

  1. ZCode is installed. The CLI ships inside the desktop app — it is not on PATH and not on npm. The relay resolves it in this order: --zcode-path <file> or ZCODE_CLI first, then PATH, then the installed app bundle. On Linux the app is an AppImage with no fixed install path, so the flag or the environment variable is required there — the relay guesses nothing.
  2. A model provider is configured for the CLI, with a key it can actually reach. Being signed into the desktop app is not enough — see below.
  3. You are in (or will point --cd at) the target git repository.

The relay records the CLI version and how it was resolved into result.json, so a surprising install is visible after the fact.

Authenticating the headless CLI

Signing into the ZCode desktop app does not authenticate the CLI this relay drives. The CLI keeps its own config at ~/.zcode/cli/config.json, separate from the desktop app's, and nothing bridges the two. zcode login is the intended path, but where it fails with OAuth response is not valid JSON the way in is a Z.AI API key.

Two pieces are needed, and they are separate:

  1. The provider block must exist in ~/.zcode/cli/config.json. It defines the provider, its endpoint and its models — the environment cannot supply this:

    jsonc
    {
      "provider": {
        "zai": {
          "kind": "anthropic",
          "options": { "apiKeyRequired": true, "baseURL": "https://api.z.ai/api/anthropic" },
          "models": { "glm-5.1": { "name": "GLM-5.1" } }
        }
      },
      "model": { "main": "zai/glm-5.1" }
    }
  2. The key can live either in provider.zai.options.apiKey in that file, or in the environment as any one of ZAI_API_KEY, ZCODE_API_KEY, or ANTHROPIC_API_KEY. Prefer the environment — it keeps the secret off disk.

If a run fails with Model provider is missing an API key: <provider>, the provider block resolved but no key was found: set one of those variables and re-run.

Autonomy — read this before dispatching

ZCode's own term is mode. It has four values; only two are usable headlessly.

modeBehaviour
yoloWrites. ZCode's own default for --prompt, and this relay's write-capable default.
planRefuses edits. What --read-only selects.
buildRejected by this relay. No permission client exists headlessly, so tools are blocked and the run exits 0 having done nothing.
editRejected for the same reason.

Two limits stated plainly, because ZCode cannot enforce them:

  • plan mode refused edits in testing, but the relay does not treat that as a guarantee. It takes a Git fingerprint before the run and reports a tri-state readOnlyViolation afterwards. Confirm touchedFiles came back empty rather than assuming no edits.
  • ZCode has no --allowed-tools. Only the --disallowed-tools denylist exists, and it is genuinely enforced. An explicit allowlisted tool surface is therefore impossible here — do not assume one.

The loop

Run these five steps per task. Steps 1, 4, and 5 are your judgment; 2 and 3 are mechanical.

1. Write the brief

ZCode sees only what you send — no repo memory, no chat history. Everything the task needs goes in the brief: the goal, the current state, what to change, what to leave untouched, the project's actual gate commands (discover them from the repo's CLAUDE.md/AGENTS.md/Makefile — do not assume), and a report contract. Tell ZCode it will not commit. One task per brief. The relay delivers the brief as an attached file, so the command line no longer bounds its length — the model's context window still does. Full guidance and a template: references/writing-the-brief.md.

2. Dispatch

bash
node "<skill-dir>/scripts/relay.mjs" --brief brief.txt --cd /path/to/repo
# read-only (review/diagnosis, no edits):   add --read-only
# continue a specific session:              add --session <sess_...>  (from result.json; send only the delta brief)
# continue the latest session for --cd:     add --resume-last
# withhold tools (denylist):                add --disallowed-tools "Write,Edit,Bash"
# point at the CLI explicitly:              add --zcode-path /path/to/zcode.cjs
# hard time limit (watchdog):               add --timeout 2h  (default: off)
# see all options:                          node .../relay.mjs --help

(<skill-dir> is this skill's installed directory — the folder containing this SKILL.md.)

The relay writes its artifacts to a temp dir, so the repo under review stays clean. It never commits — see step 5. Mechanics, flags, and the result.json shape: references/dispatch-and-poll.md.

3. Wait for completion

The relay blocks until ZCode finishes, so back it with whatever your orchestrator offers:

  • Claude Code: run the Bash call with run_in_background: true; you are notified on completion.
  • Plain shell / other agents: foreground for short tasks, or background it and poll the result file. The run is done when result.json exists with a status. A pre-run usage error exits 2 and writes no result file, so check the exit code too; a CLI that cannot be found exits 127 but does write a result.json with status zcode_unavailable.

Do not trust progress trackers over reality: read the working tree, not a status line.

4. Review — do not trust the self-report

  • Re-run the project's gates yourself. Never take "gates passed" on faith.
  • Read the diff against the brief: did ZCode do what was asked, nothing more and nothing less? touchedFiles is your starting point.
  • On a --read-only run, check readOnlyViolation and confirm touchedFiles is empty.
  • Run the relevant guard skills on the diff if you have them installed.

Full checklist: references/review-and-land.md.

5. Land it

The orchestrator commits. Only after the gates pass and the diff holds:

  • Commit the verified work yourself, with a clear message.
  • If it needs changes, send a delta brief with --session <sessionId> from the prior result.json, and review again.

Read-only second opinions

The relay doubles as a way to get an adversarial second opinion with no write risk: dispatch --read-only with a brief listing the agreed points, then each contested point with both positions, and ask ZCode to defend or concede each. Because plan mode's guarantee is measured rather than enforced here, verify touchedFiles came back empty instead of assuming no edits.

Authorization model

Delegation is something the human opts into. Once they have, committing verified, gate-passing work is the agreed contract. Two limits: surface, don't absorb (report ZCode's design decisions and defensible-but-unasked turns rather than silently keeping them) and stop for scope changes (if correct completion needs going beyond the brief, ask). The full treatment is in references/review-and-land.md.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Zcode Delegate AI skill do?

Delegate a coding task to the Z.AI ZCode CLI as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to ZCode — phrasings like "have ZCode do X", "delegate this to ZCode", "run it through ZCode", or "use ZCode to implement/fix/refactor" — or to run a queue of coding tasks through ZCode while staying the reviewer. DO NOT USE for tasks small enough to do inline, or when the user wants the code written directly without delegating.

Why use Zcode Delegate on TypingMind?

Because you install it once and use it with any model. Zcode Delegate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Zcode Delegate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/amElnagdy/delegate-skills/tree/master/skills/zcode-delegate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Zcode Delegate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Zcode Delegate?

As many as you like. As long as a model supports skills, you can use Zcode Delegate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Zcode Delegate AI skill free?

Yes. It is published on GitHub by amElnagdy under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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