OxCode Blog
Free AI Coding Agent for VS Code: Run Your First Task
A developer installs a fresh extension, opens an active project, prompts the chat box to fix an auth handler, and watches thirty lines of unvetted code overwrite their working files. Ten minutes later, Git status shows modifications across five untracked files, the dev server fails to compile, and the developer closes the editor in frustration.
Most developers test AI tools backwards. They throw a big, open-ended feature request at a fresh install, skip setting boundaries, and then wonder why the output creates more work than it saves.
Testing an autonomous coding agent takes the opposite approach. You need a contained environment, a deterministic problem, and a strict verification routine. The goal of your first session is not to ship an entire feature. It's to find out whether the agent respects your instructions, plans accurately, and leaves your codebase cleaner than it found it.
What a good first task for a free AI coding agent looks like
Your first task must not be open-ended feature creation. Ask an agent to build a complete authentication workflow or integrate an unfamiliar API on run one, and you can't tell where hallucination ends and real logic begins.
A good first task meets three criteria. The scope stays isolated to one or two files. The expected behavior is binary: the code either outputs the correct value or it doesn't. And you can prove the failure before the agent touches anything.
Think of a timestamp bug where a token expiration helper divides milliseconds by 1,000 twice. Another classic candidate is an off-by-one error in a pagination utility that returns nine items instead of ten. Both problems have obvious inputs, deterministic outputs, and zero external network dependencies.
Deterministic tasks remove the guesswork. Pick an issue where you already know what the fix looks like. Then you can judge the agent on its reasoning, its respect for your directory structure, and whether it stops when the job is done.
Step 1: Create a disposable Git branch before you install anything
Never run an AI coding agent on your main branch or inside a dirty working directory. Autonomous agents inspect files, edit code, and stage terminal commands. Run one on an uncommitted working tree and you can't track what it changed.
Open your terminal in VS Code. Run git status. Stash or commit whatever work you currently have in flight. Then cut a clean, dedicated throwaway branch with this command: git checkout -b test/agent-sandbox-run.
A branch gives you an escape hatch. If the agent makes erratic edits or touches files outside the prompt scope, a single git checkout command or branch deletion wipes the slate clean in 200 milliseconds.
Treat this branch as scrap paper. You aren't pushing this code to GitHub or merging it into staging. You're building a sandbox where an external tool can fail safely without costing you billable hours or corrupting your local state.
Step 2: Pick a small existing bug with a reproducible failing test
Code that compiles is not code that works. Most AI assistants generate syntactically valid code that quietly fails boundary checks. To test a free AI coding agent for VS Code fairly, give it an objective standard.
Find a bug you already understand. If you maintain a Node.js API, write a minimal unit test in Jest or Vitest that asserts the correct behavior and fails right now. For example, write a test for an endpoint filter where passing status=archived returns an empty array instead of active records. Run the test locally. Confirm that the terminal prints red.
This failing test is your baseline truth. You're giving the agent an explicit boundary: make this specific test turn green without altering the test assertions.
Code review needs an objective anchor. Without a reproducible test, you end up clicking through your application to guess whether the logic holds up. With a failing test, verification takes three seconds in your local terminal.
Step 3: Install the OxCode extension and ask for a plan first (Free plan: 15 runs/day)
Open the VS Code Extensions view, search for OxCode, and install the extension. OxCode runs directly inside VS Code, Cursor, Antigravity, and other VS Code-based IDEs. For individual developers in India exploring agentic workflows, the OxCode pricing structure includes a Free plan with 15 runs per day. Paid tiers include Starter at ₹899 per month for 40 runs per day and Pro at ₹3,999 per month for 150 runs per day, with the first two months discounted to ₹99 and ₹999.
When you open the OxCode interface, switch to Plan mode before you trigger an Agent run. OxCode is built context aware: it understands your codebase before it touches it, and it routes each prompt to the most efficient model for the job, so you never have to think about which model to pick.
State your prompt clearly: 'Read test/pagination.test.ts and src/utils/pagination.ts. Formulate a plan to fix the off-by-one error so the test passes. Do not modify files outside src/utils/.'
Good agents plan before they execute. OxCode has distinct Plan and Debug modes alongside its standard Agent mode, so you can inspect its logic before any file modification begins.
Step 4: Review the proposed changes before approving anything
Once the plan looks sound, switch to Agent mode to execute the fix. OxCode uses approval-first commands. When the agent wants to inspect directory structures, modify a file, or run a diagnostic command in your terminal, it asks for your permission first.
Don't reflexively hit accept. Read the proposed edit line by line. Look for three warning signs:
Scope creep: Did the agent rewrite package.json, import unnecessary external libraries, or alter configuration files?
Test dilution: Did the agent try to edit your failing test file to force a green result?
Logic shortcuts: Did the agent write a hardcoded return statement that satisfies only the test fixture instead of fixing the underlying utility?
OxCode runs what it writes in a sandbox and catches and fixes its own bugs before calling a task done. It solved 73 of 89 Terminal-Bench 2.1 tasks and resolved 410 of 500 SWE-bench Verified instances (82%) on one attempt each. Even with high benchmark scores, you're the supervising engineer. Inspect every command and file write before granting terminal access.
Step 5: Run the tests yourself and review the full diff
When the agent reports that the task is finished, don't take its word for it. Coding agents can declare success while leaving side effects in files you aren't watching.
Switch to your integrated terminal. Run your test runner manually: npm test or pytest. Check with your own eyes that the failing test you created in Step 2 now passes.
Next, run your entire test suite, not just the isolated unit test. Make sure fixing this bug didn't break an adjacent module or invalidate existing contracts.
Finally, run git diff. Review the entire patch in VS Code's diff viewer. Check every modified line against your project's coding standards. If you want to study systematic verification patterns, read our practical guide on how to debug AI-generated code in VS Code.
Trust comes from verification, not agent status messages. A clean diff and a passing test suite are the evidence you need to keep the code.
What to do if it fails, and when to keep or delete the branch
Sometimes an agent misreads your codebase or generates code that fails your local tests. If that happens, don't fight the tool across ten chaotic prompt iterations.
If the agent is close, switch to Debug mode in OxCode. Give it the specific terminal error trace and ask it to diagnose why its first attempt failed. OxCode's project memory helps retain the context of your codebase structure across steps.
If the agent touched unexpected files, introduced cyclical dependencies, or burned through three attempts without progress, delete the branch immediately. Run git checkout main and git branch -D test/agent-sandbox-run.
Deleting the branch takes five seconds and restores your workspace to a clean state. You lost nothing, and you spent zero rupees on wasted tokens.
When you're ready to compare tool costs across your workflow, check out our breakdown of AI coding assistant pricing in rupees. Indian developers don't need to pay 20 dollars every month on overseas subscriptions just to get autonomous coding assistance inside their editor.
Conclusion
Adopting an AI coding agent doesn't mean handing over your codebase on day one. You build trust through small, verifiable steps, strict approval gates, and disciplined Git hygiene.
OxCode gives you that control with Plan mode, approval-first commands, sandboxed execution, and 15 free runs every day. Install OxCode from the Visual Studio Marketplace, create your disposable branch, and run your first bug fix safely.