0d0b83f98c
Add three new sections to all 14 examples: - "Carry Forward": what output feeds into later examples (01-10) - "The Cumulative Path": alternative prompt building on previous output (02-10) - "Now Try It Yourself": personalized template with transferable pattern (all) - "Building On" callout connecting back to previous examples (02-10) Add Example 14: Build Your Personal Agent - capstone that guides reader through writing their own CLAUDE.md, creating a personal skill, connecting a messaging channel, setting up automation, and testing end-to-end. Update README with cumulative path diagram, two usage modes, and example 14. Update GETTING-STARTED.md with cross-references to relevant examples. 17 files changed, 703+ lines added. The examples now form a coherent learning path from "see what it can do" to "build your own agent." Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
118 lines
4.3 KiB
Markdown
118 lines
4.3 KiB
Markdown
# Example 06: Multi-Agent Orchestration
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**Capability:** Claude Code can spawn sub-agents with distinct roles, run them in
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parallel or in sequence, and combine their outputs into a final result.
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**OpenClaw equivalent:** Sub-agents, agent-to-agent messaging, mesh workflows.
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> **Building on Examples 01-05.** You have raw research (01), organized structure (02), verified data (03), and persistent state (05). Now three specialized agents turn that raw material into a polished, reviewed document. This is where the pipeline produces something you can actually share.
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---
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## Prerequisites
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This example uses the agents defined in `.claude/agents/`:
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- `researcher.md` - web research and source gathering
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- `writer.md` - structured content drafting
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- `reviewer.md` - accuracy and quality review
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These agents load automatically when Claude Code opens this project.
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---
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## The Prompt
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```
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Use the researcher agent to find information about how Claude Code handles
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agent isolation and worktree sandboxing (introduced in v2.1.49 and v2.1.50).
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Then use the writer agent to draft a 300-word technical summary of the findings,
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written for a developer audience. No jargon without explanation.
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Finally, use the reviewer agent to check the draft for technical accuracy.
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If the reviewer finds any issues, have the writer fix them before showing
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me the final version.
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```
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---
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## What Happens
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Claude Code will:
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1. Invoke the researcher agent via the Agent tool with the research task
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2. Receive the research output and pass it to the writer agent
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3. Invoke the writer agent to produce the 300-word draft
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4. Invoke the reviewer agent with both the draft and source material
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5. If the reviewer flags issues, loop back to the writer for a revision
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6. Present the final reviewed draft
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---
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## Why This Matters
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Agent Teams (v2.1.32) gives Claude Code a mesh model that matches OpenClaw's
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sub-agent architecture. Worktree isolation (v2.1.50) means each agent gets
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its own working directory, preventing file conflicts in parallel runs.
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The researcher-writer-reviewer pattern is the same loop that produces articles
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for `fromaitochitta.com`. The agents here are minimal versions of that pipeline.
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---
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## Carry Forward
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You now have a multi-agent review loop. This is the quality engine:
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- **Example 07** delivers the reviewed output to your phone
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- **Example 10** runs this exact agent sequence as steps 2-4 of the full pipeline
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- **Example 14** shows you how to customize these agents for your own work
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The researcher-writer-reviewer pattern is the single most reusable workflow in this repo. Any task that involves gathering information, drafting content, and checking quality follows this shape.
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---
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## The Cumulative Path
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> If you ran Examples 01-05, you have a research report with verified data
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> and persistent state. This prompt runs the full agent review cycle on it.
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```
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Read all files in pipeline-output/research-report/.
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Use the researcher agent to verify any claims that have not been
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web-verified yet and fill any gaps in the data.
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Then use the writer agent to produce a polished 400-word summary
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suitable for sharing with a colleague. Clear language, no jargon,
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structured with headings.
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Finally, use the reviewer agent to check for accuracy, clarity,
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and completeness. If the reviewer finds issues, have the writer
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fix them before showing me the final version.
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Save the final version to pipeline-output/research-report/final-summary.md
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```
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After running this, your research has been through a professional review cycle. The `final-summary.md` is something you could email to your team.
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---
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## Now Try It Yourself
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Replace the demo topic with something you need researched and reviewed:
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```
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Use the researcher agent to find information about [your topic].
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Then use the writer agent to draft a [length]-word [format] for
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[your audience]. Use the reviewer agent to check [what matters
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most: accuracy, tone, completeness]. Loop until the reviewer
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approves.
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```
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**The pattern you just learned:** specialized agents + sequential handoff + revision loop. Break any complex task into roles (research, draft, review) and let agents handle each part.
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Ideas worth trying:
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- Research a vendor and produce a one-page recommendation memo
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- Gather competitive intelligence and write an executive briefing
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- Compile technical documentation and review it for accuracy
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