Most AI coding tools handle one step at a time. You ask, they answer, you move on. Cursor Agent with no limit on tool calls works differently — it keeps going. It reads files, searches the web, runs your tests, checks the output, finds related code it noticed along the way, fixes that too, and only stops when the whole job is done. Not one step. The whole thing.
What 'no limit' actually changes
A tool call is any action Agent takes on your behalf — reading a file, running a terminal command, searching the codebase, checking a browser. When platforms cap these (say, at 25 or 50 per session), complex tasks hit a wall mid-way and you have to restart or continue manually. Remove the cap and a different kind of work becomes possible: workflows that actually mirror how a developer thinks, not just how a chatbot responds.
The difference is iterative depth. Real development rarely goes in a straight line. You write a feature, run the tests, find a type error — a mismatch between what a value is and what the code expects — check where that type is defined, fix it, discover a dependency that also needs updating, and so on. Each step surfaces the next. Agent can follow that chain without stopping.
A full-stack feature, start to finish
Take adding a search feature to a web app. With no tool call limit, Agent might do something like this: semantic search across the codebase to find anything related to search or filtering, read those files to understand the existing API design, search the web for documentation on the search library you're using, check your package dependencies to confirm the right version is installed, write the backend endpoint, write the frontend component that calls it, start the dev server, open the browser to test it visually, run the test suite, and generate a quick design mockup for review. That's ten or more tool calls, but from your perspective it's one instruction and one result.
Now, you might be thinking: but I still have to review all of that. True — and you should. Agent surfaces what it did at each step, so you can follow along or jump straight to the output. The point isn't that you hand over control. It's that you stop being the one manually stitching steps together.
What a large refactor looks like
Refactoring — restructuring existing code without changing what it does — is one of the most tedious tasks in development because it touches so many files. Agent handles it differently at scale. It finds every instance of the pattern you want to change, reads enough of each file to understand the variation, checks your project's naming conventions, applies the changes across the whole codebase, runs the linter and formatter, checks types, runs tests, and confirms the build passes. No file left half-touched. No test left unrun.
The same depth applies to performance work, security audits, and database migrations. A security audit, for instance, might involve searching for vulnerable patterns (like unsanitised user input reaching a database query), looking up the latest CVEs — publicly disclosed security vulnerabilities — for the libraries you're using, applying fixes, and then scanning for other places in the codebase where the same class of problem exists. Agent does not stop after fixing the one file you pointed it at. It keeps looking.
The other workflows, briefly
Performance debugging follows a similar shape: profile the app, read the slow code, research optimisation techniques, apply them, measure again in the browser, find similar bottlenecks elsewhere, fix those too. Documentation generation works the same way: find all public APIs — the functions and endpoints other code is meant to call — extract their signatures and existing comments, pull real usage examples from the codebase, write the docs, preview them, ask you about anything unclear. Each of these workflows involves ten or more tool calls that flow into each other naturally, not as a list of tasks you hand over one by one.
What this feels like in practice
The honest way to describe it: Agent handles the connective tissue. The reading-to-understand, the searching-to-confirm, the running-to-verify — all the steps between the idea and the finished thing that are not themselves the idea. What you provide is intent and judgment. What Agent provides is execution, more like a junior developer working through a ticket than a tool completing a single command.
That's not a small change. Most of the time in development is connective tissue.