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 skills add baphuongna/pi-crew --skill child-pi-spawninggit clone --depth 1 https://github.com/baphuongna/pi-crewWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/baphuongna/pi-crew/child-pi-spawning)<a href="https://agentmods.dev/skills/baphuongna/pi-crew/child-pi-spawning"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/child-pi-spawning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/baphuongna/pi-crew/child-pi-spawning"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/child-pi-spawning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 224 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What 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 5.1 | $0.00018 | $0.02342 |
| Opus 5 | $0.00009 | $0.01171 |
| Sonnet 5 | $0.00004 | $0.00468 |
| Haiku 4.5 | $0.00002 | $0.00234 |
Grade A, and why
child-pi-spawning scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
child-pi-spawning
Child Pi workers are subprocesses spawned by task-runner.ts via runChildPi() in child-pi.ts. Understanding the spawn flow, lifecycle events, and failure modes is essential for debugging worker crashes and "worker blinks" issues.
Spawn Flow
task-runner.ts (runTeamTask)
→ runChildPi({ cwd, task, agent, model, skillPaths, signal, onLifecycleEvent })
→ child-pi.ts (runChildPi main function)
→ buildPiWorkerArgs() → getPiSpawnCommand() → spawn(command, args, options)
→ ChildProcess spawned
→ activeChildProcesses.set(pid, child)
→ input.onLifecycleEvent({ type: "spawned", pid, ts })
→ stdout.on("data") → ChildPiLineObserver
→ stderr.on("data")
→ child.on("error") → onLifecycleEvent("spawn_error")
→ child.on("exit") → onLifecycleEvent("exit")
→ child.on("close") → onLifecycleEvent("close"), settle(result)
Key components
- ChildPiLineObserver: Parses JSON events and stdout lines from child Pi's output stream
- Response timeout: 5-minute timer resets on every stdout/stderr chunk; on timeout → SIGTERM
- Final drain: After last assistant event, waits
finalDrainMs(default 2s) then SIGTERM - Hard kill: After
hardKillMs(default 2s) from SIGTERM, SIGKILL - Active process tracking:
activeChildProcessesMap for global cleanup
Lifecycle Events
ChildPiLifecycleEvent interface — emitted via onLifecycleEvent callback:
interface ChildPiLifecycleEvent {
type: "spawned" | "spawn_error" | "response_timeout" | "final_drain" | "hard_kill" | "exit" | "close";
pid?: number;
exitCode?: number | null;
error?: string;
ts: string;
}
Event sequence for normal completion:
1. spawned pid=12345 ← child.pid assigned
2. [stdout events: message, tool_execution_start, tool_execution_end, message_end...]
3. final_drain pid=12345 ← last assistant event received, SIGTERM sent
4. exit exitCode=0 ← process exited
5. close exitCode=0 ← stdio fully closed
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.
- 9d ago First seen · 227 lines · 18 tokens per session scan A 5ee823202d21
child-pi-spawning is a skill published in the GitHub repository baphuongna/pi-crew (52 stars, last pushed 5d ago), licensed MIT. It adds 18 tokens to every session and 2,342 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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