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 live-agent-lifecyclegit 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/live-agent-lifecycle)<a href="https://agentmods.dev/skills/baphuongna/pi-crew/live-agent-lifecycle"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/live-agent-lifecycle/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/live-agent-lifecycle"><img src="https://agentmods.dev/badge/skills/baphuongna/pi-crew/live-agent-lifecycle.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 204 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 | $0.01937 |
| Opus 5 | $0.00009 | $0.00968 |
| Sonnet 5 | $0.00004 | $0.00387 |
| Haiku 4.5 | $0.00002 | $0.00194 |
Grade A, and why
live-agent-lifecycle 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 — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.
live-agent-lifecycle
Live agents are real-time, in-memory worker sessions managed by LiveAgentManager (src/runtime/live-agent-manager.ts). They are distinct from CrewAgentRecord files on disk — live agents provide real-time activity (tool names, response text, turn count) while agent records are durable snapshots.
Architecture
LiveAgentHandle is the core data structure:
interface LiveAgentHandle {
agentId: string; // unique per run
taskId: string; // maps to task
runId: string; // run this agent belongs to
workspaceId: string; // manifest.cwd — workspace boundary
role?: string;
agent?: string;
modelName?: string;
session: LiveSessionHandle; // steer/prompt/abort/dispose
status: CrewAgentRecord["status"];
pendingSteers: string[];
pendingFollowUps: string[];
pendingMessages: IrcMessage[];
activity: LiveAgentActivity; // real-time tracking
createdAt: string;
updatedAt: string;
}
The in-memory liveAgents Map stores all active handles. It is never persisted — on Pi restart, the Map is empty and agents are re-created from agent records.
Registration
registerLiveAgent(input, eventLogFn?, eventsPath?) is called when a live session worker starts. It:
- Creates or reuses the handle in
liveAgentsMap - Preserves pending steers/followups from previous sessions
- Emits
live_agent.registeredevent to events.jsonl - Flushes any pending steers/followups immediately if the session already has the methods
Key caller sites:
live-session-runtime.ts— when a live session agent startslive-executor.ts— when spawning a live task- (workspaceId is passed through the entire call chain)
Workspace Isolation
workspaceId: string field is the workspace boundary. Set to manifest.cwd at registration time.
Why it matters: When Pi has multiple workspace folders open, agents from workspace A must not be visible or controllable from workspace B. Every handle carries its origin workspace.
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 · 207 lines · 18 tokens per session scan A a5a2ec63581d
live-agent-lifecycle is a skill published in the GitHub repository baphuongna/pi-crew (52 stars, last pushed 4d ago), licensed MIT. It adds 18 tokens to every session and 1,937 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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