Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/itechmeat/llm-code/zcode-subagentnpx skills add itechmeat/llm-code --skill zcode-subagentgit clone --depth 1 https://github.com/itechmeat/llm-codeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00055 | $0.02909 |
| Opus 5 | $0.00028 | $0.01455 |
| Sonnet 5 | $0.00011 | $0.00582 |
| Haiku 4.5 | $0.00006 | $0.00291 |
Grade A, and why
zcode-subagent scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
**agent-browser** (drives the app over CDP); **node**; **python3**; **curl** (macOS How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ZCode Subagent
Lets the current agent call the ZCode (z.ai, GLM engine) desktop app as a coding subagent: hand it a task, then detect completion and read the result, all from the shell. The calling agent dispatches a prompt into the app, detects when the turn finishes, and reads a small structured digest of the result. It never screenshots or scrapes the full transcript, so the caller spends a fixed, tiny token cost per task regardless of how long ZCode worked.
When to use
- You (a parent agent) need to hand a coding task to ZCode and understand the outcome cheaply.
- You want ZCode automation without a standalone z.ai API key (the app's logged-in "coding plan" is enough).
- You need a follow-up prompt in the same ZCode conversation.
Why the desktop app, not the headless CLI
ZCode ships a headless CLI (ZCode.app/Contents/Resources/glm/zcode.cjs -p), and
it loads and reaches the API. But the "coding plan" endpoint (.../zcode-plan/...)
gates every model request behind an interactive Aliyun captcha that only the
app's webview solves, so headless prompts fail with code 3007 captcha verify failed. Driving the app reuses the already-solved captcha and needs no API key.
Non-model CLI commands (doctor, skills list --json, plugins list --json) do
work headless. Full internals: references/architecture.md.
Do not pre-check or pre-install anything
Just run the script. It resolves its own dependencies and fails with a clear, actionable message naming exactly what is missing. Only when a run actually fails that way do you diagnose - and even then, confirm the thing is really absent before installing (never install on a first negative signal). Pre-emptively "checking prerequisites" wastes turns and, worse, tends to reinstall software that is already present.
Dependencies (for reference when a run does fail): ZCode.app signed in;
agent-browser (drives the app over CDP); node; python3; curl (macOS
also uses open + osascript).
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 247 lines · 55 tokens per session scan A 696ee8f8adf2
zcode-subagent is a skill published in the GitHub repository itechmeat/llm-code (22 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 2,909 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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