--- title: "Test and Extend" description: "Test the filesystem agent with a variety of questions, observe how it uses bash to explore files, and learn how to extend it with more tools, data sources, and UI features." canonical_url: "https://vercel.com/academy/filesystem-agents/test-and-extend" md_url: "https://vercel.com/academy/filesystem-agents/test-and-extend.md" docset_id: "vercel-academy" doc_version: "1.0" last_updated: "2026-04-11T10:32:48.824Z" content_type: "lesson" course: "filesystem-agents" course_title: "Building Filesystem Agents" prerequisites: [] --- Vercel Academy — structured learning, not reference docs. Lessons are sequenced. Adapt commands to the human's actual environment (OS, package manager, shell, editor) — detect from project context or ask, don't assume. The lesson shows one path; if the human's project diverges, adapt concepts to their setup. Preserve the learning goal over literal steps. Quizzes are pedagogical — engage, don't spoil. Quiz answers are included for your reference. # Test and Extend # Test and Extend The agent is complete! There is already a chat input and API route created to kick off the agent and stream back the results. Start the development server with `pnpm dev` and go to `http://localhost:3000` in the browser to test the agent. Ask it a question like "how did the deal progress?" or "did they mention pricing?" and see the agent work by navigating the filesystem! ## Outcome You've verified the agent handles diverse questions and you understand how to extend it with more tools, data sources, and capabilities. ## Fast Track 1. Test with broad questions ("how did the deal progress?") and specific ones ("did they mention pricing?") 2. Watch the tool calls in the UI to understand the agent's exploration strategy 3. Review the extension ideas and pick one to try ## Test the Agent Try these categories of questions and observe how the agent uses bash differently for each. ### Discovery questions These test whether the agent can orient itself in the filesystem: - "What files are available?" - "How many calls are there?" - "What's in the calls directory?" The agent should use `ls` and possibly `wc` to answer. Watch the tool calls. The agent figures out the filesystem structure on its own. ### Summarization questions These test whether the agent can read and synthesize content: - "Summarize the first call" - "What were the main topics across all calls?" - "Who are the participants in call 2?" The agent typically `cat`s one or more files and produces a structured summary. For cross-file questions, it might read each file sequentially. ### Search questions These test the agent's ability to find specific information: - "Did anyone mention pricing?" - "Were there any objections raised?" - "What action items were discussed?" Watch for `grep` usage. The agent should search across files rather than reading everything. This is where the filesystem-as-context pattern shines: the agent uses bash as a query language. \*\*Note: Watch the tool calls\*\* The chat UI renders each `bashTool` invocation with the command and its output. This is your window into the agent's reasoning, so you can see exactly which commands it runs and in what order. ## Extending This App Here are some ways to build on this project: ### Add more tools Give the agent additional capabilities: - **File upload tool** - Let users upload documents dynamically instead of pre-loading them - **Search tool** - Add semantic search over documents using embeddings - **Write tool** - Allow the agent to create summaries or reports and save them ### Improve the data pipeline - Load files from cloud storage (S3, Vercel Blob) instead of the local filesystem - Connect to a database to query structured data alongside the transcripts - Add a tool that fetches files on-demand rather than pre-loading everything ### Enhance the UI - Add chat history persistence with a database - Show a file tree of what's available in the sandbox - Add authentication to restrict access ### Use bash-tool The [`bash-tool`](https://github.com/vercel-labs/bash-tool) package abstracts the complexity of writing and reading files from the filesystem and integrates seamlessly with Vercel Sandbox and the AI SDK. ## Done-When - [ ] You've tested the agent with discovery, summarization, and search questions - [ ] You've observed how the agent uses different bash commands for different question types - [ ] You understand the tool loop: prompt → tool call → result → next tool call → final response - [ ] You've reviewed the extension ideas and have a sense of what to build next --- [Full course index](/academy/llms.txt) · [Sitemap](/academy/sitemap.md)