ClaudeWorkInbox & emailAI score · 63/100AI-assisted edit · no obvious prompt-injection riskX

Multi-Agent Team Auto Morning Report Email

Script aggregates multi-agent and machine status → model generates email → scheduled delivery

ExperiencedStepsWorkflowTip
Who
Operators and team leads managing multiple AI agents and machines
You get
Receive a structured email at 7am daily, replacing manual agent status checks
You need
Claude · Codex · Gemini

Constraints

Requires: scripted access to agent status and code repositories, email delivery capability, at least one LLM API (Claude/Codex/Gemini). Author uses 4 agents (Claude, Codex, Z.ai, Gemini) and 3 machines. Specific scripting language, scheduler, and email service are not specified.

What they did

Chris Pirillo used to open a chat every morning and type 'what happened overnight?' Now he runs a multi-agent auto morning report system: a script collects status data from four agents (Claude, Codex, Z.ai, Gemini) and three machines, a model generates a structured email, and it delivers at 7am daily. The email has five sections: three-line summary, real-time status, completed items with quality, blocked items with fix progress, and what's next. Operational rules enforce script/model separation, precise failure tracking, automatic idle agent restart, and single-fact bullets.

How it went

Day one's email reported 46 commits landed, 91 issues closed, and status from four agents and three machines. Author reports scanning it over coffee without manual queries. (Source: author report)

Worth knowing

Author did not disclose scripting language, scheduler, email service, API configuration, or costs. Z.ai uses GLM-5.3-Flash. Source is an experience report, not a setup tutorial; implementers must choose their own stack for data pulling and email delivery. Not tested by this site; reproduction requires additional technical decisions.

Steps

  1. Script gathers facts

    Automatically pull status data from all agents and machines: commit counts, issues closed, current running tasks per agent, failures/blocks and their resolution status. No email is generated without facts.

  2. Model writes the email

    Feed collected facts to a model to generate email body in fixed structure: 1) Three-line summary; 2) Real-time status per agent and machine; 3) Items completed since last check and quality (merged/parked/reverted); 4) Blocked items with fix progress and owner; 5) What's starting next. Rules: model writes only, never fabricates; failures count only if still unresolved; idle agents must be restarted before reporting (unless out of budget); one fact per bullet.

  3. Schedule delivery

    Configure automatic email delivery at 7am daily. Author's day-one email included: 46 commits, 91 issues closed, status from 4 agents and 3 machines.

  4. Operational rules

    Enforce four anti-hallucination rules continuously: ① Script gathers facts, model writes only, no facts means no email; ② Failure counts only as latest unresolved result, fixed items explain the fix; ③ 'Nothing' for agent current work is wrong unless out of budget—report restarts idle agents before writing; ④ Bullets, one fact each, scannable over coffee.

Prompt you can copy

Reference prompt · Editorial suggestion。Confirm the destination, input variables and output format before use.

This block is the prompt. Ads are never placed here.

No prompt needed — just follow the steps.

Configure script collection, model invocation, and email delivery per steps; no fixed prompt template needed.

Source

不再每天早上问「昨晚发生了什么」:多 Agent 团队 7 点发晨报邮件——脚本收集事实、模型只负责写,附 4 条防胡写规则 · ChrisPirillo · X · 2026-10-16T21:11:25.000Z

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