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docs(manifest): rename FC to createos-sandbox
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‎.github/workflows/examples.yml‎

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# --- S3-compatible bucket for example 38 (s3-disk-ffmpeg-transcode) ---
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# Wire these secrets, uncomment, and drop 38 from the discover
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# exclude list above to run that example end-to-end in CI. The bucket
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# must be reachable from the FC agent, not just the runner.
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# must be reachable from the createos-sandbox agent, not just the runner.
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# S3_BUCKET: ${{ secrets.S3_BUCKET }}
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# S3_ENDPOINT: ${{ secrets.S3_ENDPOINT }}
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# S3_REGION: ${{ secrets.S3_REGION }}

‎examples/README.md‎

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| 39 | [39-bandwidth-recharge](39-bandwidth-recharge/) | Read a sandbox's bandwidth quota and grow it after create with rechargeBandwidth (create no longer accepts bandwidth_quota_bytes). | createSandbox, getBandwidth, rechargeBandwidth, destroy | — |
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| 40 | [40-idle-auto-pause](40-idle-auto-pause/) | Set an idle auto-pause timeout at create with auto_pause_after_seconds and change it live with setAutoPause(seconds | null) so an idle sandbox stops billing. | createSandbox, setAutoPause, destroy | — |
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| 41 | [41-python-pdf-extractor](41-python-pdf-extractor/) | Upload a fillable PDF into a sandbox, pip-install PyMuPDF, extract every form-field name and value to JSON, and download the result — no external API required. | createSandbox, files.upload, runCommand, destroy | — |
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| 42 | [42-doc-to-markdown](42-doc-to-markdown/) | Upload a local document (HTML, DOCX, PDF, …) into an FC sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result. | createSandbox, files.upload, runCommand, files.download, destroy | — |
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| 42 | [42-doc-to-markdown](42-doc-to-markdown/) | Upload a local document (HTML, DOCX, PDF, …) into a createos-sandbox sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result. | createSandbox, files.upload, runCommand, files.download, destroy | — |
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| 43 | [43-crawl4ai-crawler](43-crawl4ai-crawler/) | Install Crawl4AI and Playwright/Chromium inside a microVM, crawl a public URL to Markdown, download the output to the host. | createSandbox, files.upload, runCommand, files.download, destroy | — |
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| 44 | [44-claude-changelog-generator](44-claude-changelog-generator/) | Clone a public git repo inside a sandbox, run the commit log through the Claude Messages API, and download the generated CHANGELOG.md. | createSandbox, sh, runCommand, files.upload, files.download, destroy | extra |
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| 45 | [45-claude-github-wiki](45-claude-github-wiki/) | Clone a public GitHub repo into a sandbox and run a Claude tool-use agent that reads the file tree to answer questions about the codebase. | createSandbox, runCommand, destroy | — |
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| 46 | [46-mastra-agent](46-mastra-agent/) | Install the Mastra TypeScript agent framework inside an FC microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response. | createSandbox, sh, files.upload, destroy | — |
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| 47 | [47-effective-agents-patterns](47-effective-agents-patterns/) | Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside an FC sandbox, with an OpenAI-compatible model proxy. | createSandbox, files.upload, runCommand, sh, destroy | — |
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| 46 | [46-mastra-agent](46-mastra-agent/) | Install the Mastra TypeScript agent framework inside a createos-sandbox microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response. | createSandbox, sh, files.upload, destroy | — |
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| 47 | [47-effective-agents-patterns](47-effective-agents-patterns/) | Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside a createos-sandbox sandbox, with an OpenAI-compatible model proxy. | createSandbox, files.upload, runCommand, sh, destroy | — |
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Setup `extra` = needs an external service or extra secrets; excluded from CI.
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- **14 jupyter-singleton** — Fork can occasionally stick in 'pausing' on the control plane.
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- **36 self-hosted-agent-worker** — **needs extra setup** — Needs Anthropic managed-agents access.
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- **37 self-hosted-sandbox-per-session** — **needs extra setup** — Needs Anthropic managed-agents access.
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- **38 s3-disk-ffmpeg-transcode** — **needs extra setup** — Needs an S3-compatible bucket reachable from the FC agent.
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- **38 s3-disk-ffmpeg-transcode** — **needs extra setup** — Needs an S3-compatible bucket reachable from the createos-sandbox agent.
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- **43 crawl4ai-crawler** — Heavy install step (~600 s); needs s-4vcpu-4gb for Chromium headroom.
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- **44 claude-changelog-generator** — **needs extra setup** — Needs ANTHROPIC_AUTH_TOKEN + ANTHROPIC_BASE_URL (or ANTHROPIC_API_KEY) for the Claude Messages API inside the sandbox.
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- **46 mastra-agent** — Requires an OpenAI-compatible provider (OPENAI_API_URL + OPENAI_API_KEY + OPENAI_MODEL). OTEL_SDK_DISABLED=true is injected into the sandbox to prevent Mastra's OpenTelemetry flush from blocking exit.

‎examples/manifest.json‎

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"entry": "index.ts",
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"ci": false,
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"status": "requires-extra-setup",
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"notes": "Needs an S3-compatible bucket reachable from the FC agent."
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"notes": "Needs an S3-compatible bucket reachable from the createos-sandbox agent."
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},
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{
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"id": "39",
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"slug": "doc-to-markdown",
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"dir": "42-doc-to-markdown",
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"title": "Python doc to Markdown converter",
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"summary": "Upload a local document (HTML, DOCX, PDF, …) into an FC sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result.",
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"summary": "Upload a local document (HTML, DOCX, PDF, …) into a createos-sandbox sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result.",
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"primitives": ["createSandbox", "files.upload", "runCommand", "files.download", "destroy"],
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"deps": [],
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"env": ["CREATEOS_SANDBOX_API_KEY", "CREATEOS_SANDBOX_BASE_URL"],
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"slug": "mastra-agent",
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"dir": "46-mastra-agent",
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"title": "Mastra agent in a sandbox",
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"summary": "Install the Mastra TypeScript agent framework inside an FC microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response.",
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"summary": "Install the Mastra TypeScript agent framework inside a createos-sandbox microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response.",
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"primitives": ["createSandbox", "sh", "files.upload", "destroy"],
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"deps": [],
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"env": [
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"slug": "effective-agents-patterns",
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"dir": "47-effective-agents-patterns",
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"title": "Effective agent patterns",
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"summary": "Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside an FC sandbox, with an OpenAI-compatible model proxy.",
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"summary": "Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside a createos-sandbox sandbox, with an OpenAI-compatible model proxy.",
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"primitives": ["createSandbox", "files.upload", "runCommand", "sh", "destroy"],
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"deps": ["ai", "@ai-sdk/openai"],
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"env": [

‎examples/package.json‎

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{
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"name": "fc-sdk-examples",
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"name": "createos-sandbox-sdk-examples",
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"private": true,
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"type": "module",
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"dependencies": {

‎llms-full.txt‎

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- [39-bandwidth-recharge](examples/39-bandwidth-recharge/) — Read a sandbox's bandwidth quota and grow it after create with rechargeBandwidth (create no longer accepts bandwidth_quota_bytes).
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- [40-idle-auto-pause](examples/40-idle-auto-pause/) — Set an idle auto-pause timeout at create with auto_pause_after_seconds and change it live with setAutoPause(seconds | null) so an idle sandbox stops billing.
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- [41-python-pdf-extractor](examples/41-python-pdf-extractor/) — Upload a fillable PDF into a sandbox, pip-install PyMuPDF, extract every form-field name and value to JSON, and download the result — no external API required.
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- [42-doc-to-markdown](examples/42-doc-to-markdown/) — Upload a local document (HTML, DOCX, PDF, …) into an FC sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result.
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- [42-doc-to-markdown](examples/42-doc-to-markdown/) — Upload a local document (HTML, DOCX, PDF, …) into a createos-sandbox sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result.
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- [43-crawl4ai-crawler](examples/43-crawl4ai-crawler/) — Install Crawl4AI and Playwright/Chromium inside a microVM, crawl a public URL to Markdown, download the output to the host.
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- [44-claude-changelog-generator](examples/44-claude-changelog-generator/) — Clone a public git repo inside a sandbox, run the commit log through the Claude Messages API, and download the generated CHANGELOG.md.
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- [45-claude-github-wiki](examples/45-claude-github-wiki/) — Clone a public GitHub repo into a sandbox and run a Claude tool-use agent that reads the file tree to answer questions about the codebase.
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- [46-mastra-agent](examples/46-mastra-agent/) — Install the Mastra TypeScript agent framework inside an FC microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response.
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- [47-effective-agents-patterns](examples/47-effective-agents-patterns/) — Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside an FC sandbox, with an OpenAI-compatible model proxy.
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- [46-mastra-agent](examples/46-mastra-agent/) — Install the Mastra TypeScript agent framework inside a createos-sandbox microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response.
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- [47-effective-agents-patterns](examples/47-effective-agents-patterns/) — Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside a createos-sandbox sandbox, with an OpenAI-compatible model proxy.
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<!-- END GENERATED: examples -->
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## Surface highlights

‎llms.txt‎

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- [39-bandwidth-recharge](examples/39-bandwidth-recharge/) — Read a sandbox's bandwidth quota and grow it after create with rechargeBandwidth (create no longer accepts bandwidth_quota_bytes).
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- [40-idle-auto-pause](examples/40-idle-auto-pause/) — Set an idle auto-pause timeout at create with auto_pause_after_seconds and change it live with setAutoPause(seconds | null) so an idle sandbox stops billing.
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- [41-python-pdf-extractor](examples/41-python-pdf-extractor/) — Upload a fillable PDF into a sandbox, pip-install PyMuPDF, extract every form-field name and value to JSON, and download the result — no external API required.
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- [42-doc-to-markdown](examples/42-doc-to-markdown/) — Upload a local document (HTML, DOCX, PDF, …) into an FC sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result.
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- [42-doc-to-markdown](examples/42-doc-to-markdown/) — Upload a local document (HTML, DOCX, PDF, …) into a createos-sandbox sandbox, convert it to Markdown with Microsoft MarkItDown (pip-installed inside the guest), and download the result.
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- [43-crawl4ai-crawler](examples/43-crawl4ai-crawler/) — Install Crawl4AI and Playwright/Chromium inside a microVM, crawl a public URL to Markdown, download the output to the host.
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- [44-claude-changelog-generator](examples/44-claude-changelog-generator/) — Clone a public git repo inside a sandbox, run the commit log through the Claude Messages API, and download the generated CHANGELOG.md.
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- [45-claude-github-wiki](examples/45-claude-github-wiki/) — Clone a public GitHub repo into a sandbox and run a Claude tool-use agent that reads the file tree to answer questions about the codebase.
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- [46-mastra-agent](examples/46-mastra-agent/) — Install the Mastra TypeScript agent framework inside an FC microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response.
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- [47-effective-agents-patterns](examples/47-effective-agents-patterns/) — Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside an FC sandbox, with an OpenAI-compatible model proxy.
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- [46-mastra-agent](examples/46-mastra-agent/) — Install the Mastra TypeScript agent framework inside a createos-sandbox microVM, upload an agent script, run it against an OpenAI-compatible provider, and capture the response.
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- [47-effective-agents-patterns](examples/47-effective-agents-patterns/) — Run three LLM agent patterns (prompt-chaining, routing, parallelization) using the Vercel AI SDK inside a createos-sandbox sandbox, with an OpenAI-compatible model proxy.
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<!-- END GENERATED: examples -->
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## Surface highlights

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