feat: initial companion repo for OpenClaw vs Claude Code article
40 files demonstrating every major OpenClaw capability using Claude Code: - 3 agents (researcher, writer, reviewer) - 3 skills (daily-briefing, slack-message, web-research) - 2 security hooks (pre-tool-use blocker, post-tool-use logger) - 10 self-contained examples with copy-paste prompts - Complete feature map (20 capabilities, 11 full match, 7 different, 2 gap) - Security docs including NemoClaw comparison - Automation, messaging, browser, memory documentation Zero dependencies. Clone and run. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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49
examples/01-agent-runtime/prompt.md
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49
examples/01-agent-runtime/prompt.md
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# Example 01: Agent Runtime
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**Capability:** Claude Code executes tools autonomously, streams output as it works,
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and loops until the task is complete. No user input needed between steps.
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**OpenClaw equivalent:** Long-running daemon with tool execution and streaming output.
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---
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## The Prompt
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```
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Research the top 3 AI frameworks released this month, compare their GitHub stars,
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and write a summary to research-output.md
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For each framework include:
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- Name and release date
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- GitHub URL and current star count
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- One sentence on what problem it solves
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- Your verdict on whether it's worth watching
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End the file with a "Verdict" section that ranks all three.
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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. Use WebSearch to find AI framework releases from the current month
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2. Use WebFetch to retrieve GitHub pages and extract star counts
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3. Loop through each framework, gathering data tool call by tool call
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4. Use Write to create `research-output.md` with the structured summary
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5. Report completion with a summary of what was written
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You will see each tool call streamed as it happens. Claude does not ask for
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confirmation between steps unless it hits something ambiguous.
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---
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## Why This Matters
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This is the agent loop in action: plan, execute, observe, repeat. The same
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loop that runs a 300-step pipeline also runs this 5-step research task.
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The difference is only scale.
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Claude Code v2.1.84 added adaptive thinking, which adjusts reasoning depth
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automatically. Complex sub-tasks get more thought; simple ones proceed fast.
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50
examples/02-shell-and-files/prompt.md
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examples/02-shell-and-files/prompt.md
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# Example 02: Shell Execution and File I/O
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**Capability:** Claude Code runs shell commands and reads/writes files as part of the
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same task. Shell output becomes input to the next step automatically.
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**OpenClaw equivalent:** `exec` tool with PTY support + read/write/edit file tools.
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---
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## The Prompt
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```
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Create a directory called 'project-scaffold', add these files inside it:
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1. package.json with name "my-project", version "0.1.0", and description
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"A scaffolded project created by Claude Code"
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2. README.md with a project overview section and a "Getting Started" section
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with placeholder install instructions
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3. .gitignore for Node.js (node_modules, .env, dist, .DS_Store)
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Then run 'find project-scaffold -type f' to verify all three files exist
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and show me the contents of package.json.
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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. Use Bash to run `mkdir project-scaffold`
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2. Use Write to create each of the three files
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3. Use Bash to run `find project-scaffold -type f` and capture the output
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4. Use Read to show the contents of `package.json`
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5. Report back with the directory tree and file verification
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---
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## Why This Matters
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Shell execution and file I/O are the foundation of every automation. Claude Code
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handles both in the same task context, so shell output can feed directly into
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file content decisions.
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The permission system controls what shell commands are allowed. In the
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`settings.json` in this repo, `rm -rf` and a handful of other destructive
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patterns are blocked by the `pre-tool-use.sh` hook before execution reaches
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the shell. See `examples/09-security-hooks/` for details.
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54
examples/03-web-search/prompt.md
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examples/03-web-search/prompt.md
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# Example 03: Web Search and Fetch
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**Capability:** Claude Code can search the web and fetch full page content as part of
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any task. Both tools are built-in; no MCP server required.
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**OpenClaw equivalent:** Brave Search API + web_fetch with Firecrawl fallback.
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---
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## The Prompt
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```
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Search for the latest Claude Code release notes, summarize the 5 most impactful
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features added in recent versions, and write the summary to changelog-summary.md
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For each feature include:
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- Feature name and the version it shipped in
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- One sentence on what it does
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- One sentence on why it matters for agent workflows
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At the top of the file add a "Researched on" line with today's date and the
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source URLs you used.
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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. Use WebSearch to find Claude Code release notes and changelog pages
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2. Use WebFetch to retrieve the full changelog content from Anthropic's docs
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3. Parse and rank features by impact on agent workflows
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4. Use Write to create `changelog-summary.md` with source attribution
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5. Confirm the file was written
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---
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## Why This Matters
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Web search makes Claude Code's knowledge current. The training cutoff becomes
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less relevant when Claude can verify facts before writing them down.
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The combination of WebSearch (for discovery) and WebFetch (for depth) mirrors
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what a human researcher does: scan headlines, then read the full article.
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This is the same pattern used in the PREP phase of the article production
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pipeline that drives the `fromaitochitta.com` content workflow.
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---
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## Note on Sources
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Claude Code cites sources when writing research outputs. If you need full
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traceability, add "include the exact URL next to each claim" to the prompt.
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63
examples/04-browser-automation/prompt.md
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examples/04-browser-automation/prompt.md
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# Example 04: Browser Automation
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**Capability:** Claude Code can control a real browser via Playwright MCP, take
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screenshots, and extract structured data from live pages.
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**OpenClaw equivalent:** CDP/Playwright browser automation with screenshot and act commands.
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---
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## Prerequisites
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Playwright MCP must be enabled. Add this to `.mcp.json`:
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```json
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{
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"mcpServers": {
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"playwright": {
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"command": "npx",
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"args": ["@playwright/mcp@latest"]
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}
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}
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}
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```
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This repo's `.mcp.json` already includes it. If Claude Code does not show
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Playwright tools at startup, run `npm install` to ensure the package is
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available, then restart.
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---
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## The Prompt
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```
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Navigate to https://news.ycombinator.com, take a screenshot of the current
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front page, and list the top 5 stories with their point counts and submitter
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names.
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Save the list to hacker-news-top5.md with the format:
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1. [title] - [points] points by [submitter]
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Include a note at the bottom with the timestamp of when you fetched this.
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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. Use the Playwright MCP `browser_navigate` tool to load the page
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2. Use `browser_screenshot` to capture the current state
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3. Use `browser_snapshot` or `browser_get_text` to extract story data
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4. Use Write to save the structured list to `hacker-news-top5.md`
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---
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## Why This Matters
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Browser automation handles pages that cannot be reached with WebFetch alone:
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JavaScript-rendered content, login-protected pages, and interactive workflows.
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OpenClaw bundles Playwright natively. Claude Code uses the same underlying
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engine via MCP. The setup takes two minutes; the capability is identical.
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58
examples/05-memory-system/prompt.md
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examples/05-memory-system/prompt.md
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# Example 05: Memory System
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**Capability:** Claude Code maintains persistent memory across sessions through a
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hierarchy of markdown files. What is written in one session is available in the next.
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**OpenClaw equivalent:** Daily markdown logs + MEMORY.md + vector search (SQLite-vec).
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---
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## How the Hierarchy Works
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Claude Code loads context in this order, from broadest to narrowest:
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1. `~/.claude/CLAUDE.md` - global preferences, always loaded
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2. `CLAUDE.md` in the project root - project-specific config, always loaded
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3. `memory/MEMORY.md` - session state, loaded if referenced in CLAUDE.md
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4. `.claude/` managed memory - auto-updated by Claude when `--memory` is active
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The file loaded earlier provides the frame. Later files narrow it.
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---
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## The Prompt
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```
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Read this project's CLAUDE.md and summarize what you learn about the project
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in three bullet points.
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Then create a file at memory/project-notes.md with:
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- Today's date as a header
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- The three-bullet summary
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- A note that says "Memory system demonstrated successfully"
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Finally, explain in one paragraph how this file will be available in the
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next Claude Code session without re-reading CLAUDE.md.
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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. Use Read to load `CLAUDE.md` from the project root
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2. Synthesize the project context into three bullets
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3. Use Write to create `memory/project-notes.md`
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4. Explain how CLAUDE.md references cause files to be auto-loaded
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---
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## Why This Matters
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OpenClaw uses SQLite-vec for semantic memory search across sessions. Claude Code
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uses structured markdown with explicit file references. Both achieve persistence.
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The markdown approach is more inspectable: you can read, edit, and version control
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every piece of memory Claude has about your project.
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The `memory/MEMORY.md` file in this repo shows the pattern at scale.
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57
examples/06-multi-agent/prompt.md
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examples/06-multi-agent/prompt.md
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# 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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---
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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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83
examples/07-messaging/prompt.md
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83
examples/07-messaging/prompt.md
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# Example 07: Messaging
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**Capability:** Claude Code can send and receive messages via external channels.
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Native Telegram support arrived in v2.1.80. Other channels use MCP servers.
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**OpenClaw equivalent:** 15+ native channels (WhatsApp, Telegram, Discord, Slack,
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Signal, iMessage, IRC, Matrix, Teams, and more).
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---
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## Architecture Difference
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OpenClaw ships with all 15+ channels built in. Claude Code takes an MCP approach:
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each channel is a separate server you opt into. This means more setup per channel,
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but also more control over what data leaves your machine.
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As of v2.1.80, Telegram is the first native channel in Claude Code. More are
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expected to follow the same pattern.
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---
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## Option A: Telegram (Native, v2.1.80+)
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Start Claude Code with the Channels flag:
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```bash
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claude --channels
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```
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Then in session:
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```
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Send a Telegram message to my personal chat that says:
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"Claude Code pipeline completed. Check research-output.md for results."
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```
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Requires the Telegram plugin configured in `.claude/settings.json`. The
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permission relay (v2.1.81) lets you approve tool calls from Telegram directly,
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without returning to the terminal.
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---
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## Option B: Slack (via MCP)
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Add to `.mcp.json`:
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```json
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{
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"mcpServers": {
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"slack": {
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"command": "npx",
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"args": ["-y", "@modelcontextprotocol/server-slack"],
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"env": {
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"SLACK_BOT_TOKEN": "xoxb-your-token",
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"SLACK_TEAM_ID": "T0123456"
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}
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}
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}
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}
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```
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Then use the `/skills/send-slack-message` skill in this repo:
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```
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/send-slack-message channel=#general message="Pipeline finished successfully."
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```
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---
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## What Happens
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For Telegram: Claude Code calls the native Channels API to deliver the message.
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For Slack: Claude Code calls the Slack MCP server, which relays via the Slack API.
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Both confirm delivery in the terminal output.
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---
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## Honest Comparison
|
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If you need 15 channels working out of the box, OpenClaw wins today. Claude Code
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has Telegram natively and the rest via MCP. The gap is narrowing with each
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release. For most personal automation needs, Telegram is sufficient.
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67
examples/08-cron-automation/prompt.md
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67
examples/08-cron-automation/prompt.md
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# Example 08: Cron and Scheduled Automation
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**Capability:** Claude Code supports scheduled and automated execution through
|
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three complementary mechanisms, covering in-session polling through to
|
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system-level cron jobs.
|
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|
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**OpenClaw equivalent:** HEARTBEAT.md, cron scheduler, webhooks, auto-reply.
|
||||
|
||||
---
|
||||
|
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## Three Approaches
|
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|
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### Approach 1: /loop (In-session polling, v2.1.71)
|
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|
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For tasks that should repeat while Claude Code is running:
|
||||
|
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```
|
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/loop interval=60
|
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|
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Every 60 seconds, check if a file called 'trigger.txt' exists in this
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directory. If it does, read its contents, execute the task described inside,
|
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delete the file, and write the result to 'loop-output.md'. Then wait for
|
||||
the next trigger.
|
||||
```
|
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|
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Use this for development and testing. The loop runs as long as the session
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is active.
|
||||
|
||||
---
|
||||
|
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### Approach 2: CronCreate (System-level scheduling, v2.1.71)
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|
||||
For tasks that should run on a schedule even when Claude Code is not open:
|
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|
||||
```
|
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Create a cron job that runs the 'daily-briefing' skill every morning at 07:00.
|
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Use the automation/daily-briefing.sh wrapper script. Show me the cron entry
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before creating it so I can verify it.
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```
|
||||
|
||||
Claude Code calls `CronCreate` to register the job with the system cron daemon.
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Use `CronList` to see all registered jobs and `CronDelete` to remove them.
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||||
The `automation/daily-briefing.sh` script in this repo is a ready-made wrapper.
|
||||
|
||||
---
|
||||
|
||||
### Approach 3: /schedule (Remote trigger, web only)
|
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|
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For triggering runs from anywhere, including from a phone:
|
||||
|
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```
|
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/schedule "Run the web-research skill on 'latest Anthropic news' and
|
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email me a summary" at 2025-04-01T08:00:00
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||||
```
|
||||
|
||||
`/schedule` is available in the Claude web interface. It queues a headless
|
||||
Claude Code run for the specified time. Combines with the Telegram permission
|
||||
relay (v2.1.81) for approval-gated automation.
|
||||
|
||||
---
|
||||
|
||||
## Why This Matters
|
||||
|
||||
OpenClaw uses HEARTBEAT.md as a persistent loop marker. Claude Code achieves
|
||||
the same outcome with more granularity: /loop for in-process polling, CronCreate
|
||||
for system scheduling, /schedule for remote triggering. The `automation/` directory
|
||||
in this repo provides macOS launchd examples as an alternative to cron.
|
||||
62
examples/09-security-hooks/prompt.md
Normal file
62
examples/09-security-hooks/prompt.md
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|
|
@ -0,0 +1,62 @@
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|||
# Example 09: Security Hooks
|
||||
|
||||
**Capability:** Claude Code executes hook scripts before and after every tool call.
|
||||
PreToolUse hooks can block dangerous operations. PostToolUse hooks create audit trails.
|
||||
|
||||
**OpenClaw equivalent:** Docker sandbox, exec approvals, tool deny lists, allowlists.
|
||||
|
||||
---
|
||||
|
||||
## How the Hooks Work
|
||||
|
||||
The `hooks/` directory in this repo contains two scripts:
|
||||
|
||||
- `pre-tool-use.sh` - runs before every Bash tool call. Blocks destructive patterns.
|
||||
- `post-tool-use.sh` - runs after every tool call. Appends to `hooks/audit.log`.
|
||||
|
||||
Both are registered in `.claude/settings.json` under the `hooks` key.
|
||||
|
||||
---
|
||||
|
||||
## The Prompt
|
||||
|
||||
```
|
||||
Try running this shell command: rm -rf /tmp/test-deletion-target
|
||||
|
||||
Before running it, explain what you expect the PreToolUse hook to do.
|
||||
After the attempt, check hooks/audit.log and show me the last 5 entries.
|
||||
Then explain what was blocked and why it was flagged by the hook.
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## What Happens
|
||||
|
||||
1. Claude Code calls the Bash tool with `rm -rf /tmp/test-deletion-target`
|
||||
2. Before execution, `pre-tool-use.sh` receives the command as input
|
||||
3. The hook matches the `rm -rf` pattern and exits with a non-zero code
|
||||
4. Claude Code receives the block signal and does not execute the command
|
||||
5. `post-tool-use.sh` logs the blocked attempt with timestamp and tool name
|
||||
6. Claude Code reports what happened and shows the audit log
|
||||
|
||||
---
|
||||
|
||||
## Reading the Audit Log
|
||||
|
||||
```bash
|
||||
tail -20 hooks/audit.log
|
||||
```
|
||||
|
||||
Each entry has the format: `[timestamp] TOOL: bash | STATUS: blocked | CMD: rm -rf ...`
|
||||
|
||||
---
|
||||
|
||||
## Architecture Difference from OpenClaw
|
||||
|
||||
OpenClaw sandboxes via Docker: the agent runs inside a container that limits
|
||||
what it can affect on the host. Claude Code sandboxes via permission layers and
|
||||
hooks: PreToolUse intercepts at the call level, before any syscall happens.
|
||||
|
||||
For personal use, hooks are more flexible. You write exactly the rules you need.
|
||||
For untrusted third-party agents, Docker isolation is stronger. See
|
||||
`security/nemoclaw-comparison.md` for a full breakdown.
|
||||
72
examples/10-full-pipeline/prompt.md
Normal file
72
examples/10-full-pipeline/prompt.md
Normal file
|
|
@ -0,0 +1,72 @@
|
|||
# Example 10: Full Pipeline
|
||||
|
||||
**Capability:** A complete workflow combining web search, multi-agent orchestration,
|
||||
file I/O, memory, hooks, and logging in a single Claude Code run.
|
||||
|
||||
**OpenClaw equivalent:** End-to-end agent pipeline with messaging, skills, and hooks.
|
||||
|
||||
---
|
||||
|
||||
## What This Demonstrates
|
||||
|
||||
Every capability from examples 01-09 working together:
|
||||
|
||||
| Step | Capability | Example |
|
||||
|------|-----------|---------|
|
||||
| 1 | Web search | 03-web-search |
|
||||
| 2 | Researcher agent | 06-multi-agent |
|
||||
| 3 | Writer agent | 06-multi-agent |
|
||||
| 4 | Reviewer agent | 06-multi-agent |
|
||||
| 5 | File I/O | 02-shell-and-files |
|
||||
| 6 | Memory update | 05-memory-system |
|
||||
| 7 | Security logging | 09-security-hooks |
|
||||
| 8 | Agent runtime loop | 01-agent-runtime |
|
||||
|
||||
---
|
||||
|
||||
## The Prompt
|
||||
|
||||
```
|
||||
Run a full research-to-output pipeline on the topic: "How Claude Code handles
|
||||
permission modes: plan, autoEdit, and bypassPermissions"
|
||||
|
||||
Pipeline steps:
|
||||
1. Use the researcher agent to gather information from the web and official docs
|
||||
2. Pass the research to the writer agent to draft a 400-word explainer
|
||||
3. Send the draft to the reviewer agent for accuracy and clarity feedback
|
||||
4. Incorporate the reviewer's feedback into a final version
|
||||
5. Save the final version to pipeline-output/permission-modes.md
|
||||
6. Append a pipeline execution summary to memory/pipeline-log.md with:
|
||||
- Date and time
|
||||
- Topic researched
|
||||
- Word count of final output
|
||||
- Any issues encountered
|
||||
7. Show me the first 10 lines of the output file to confirm everything worked
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## What Happens
|
||||
|
||||
Claude Code will coordinate the full pipeline autonomously:
|
||||
|
||||
- The researcher agent uses WebSearch and WebFetch
|
||||
- The writer agent produces structured prose
|
||||
- The reviewer agent critiques and returns specific feedback
|
||||
- A revision loop runs if needed (bounded by maxTurns in settings.json)
|
||||
- File writes are intercepted by PostToolUse for audit logging
|
||||
- Memory is updated so the next session knows this pipeline ran
|
||||
|
||||
You will see each agent invocation streamed in sequence. The entire pipeline
|
||||
typically completes in 2-4 minutes depending on web fetch latency.
|
||||
|
||||
---
|
||||
|
||||
## Why This Matters
|
||||
|
||||
This is what Claude Code looks like as an actual agent platform, not a
|
||||
chat assistant. The same architecture, with different prompts and agents,
|
||||
runs the article production pipeline at `fromaitochitta.com`.
|
||||
|
||||
The companion repo you are reading is the minimal version of that setup.
|
||||
Clone it, open Claude Code, and run this prompt to see the full stack work.
|
||||
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