FOCUSED AI DISCOVERY HUB

AI Coding Assistants and Agents

Explore coding assistants, code agents and developer tools with a focus on reviewable changes, permissions and tests.

How to use this hub

Coding tools can save time while also increasing the amount of code a team must review. Compare repository access, execution permissions, change visibility and how well each tool fits your testing and security process.

Coding-tool checklist

Editorial profiles to compare

Coding AI

Cursor AI

Independent Cursor guide covering repository context, agent workflows, code review, permissions, plan limits and security checks.

Coding AI

OpenCode

Independent OpenCode guide covering terminal and editor workflows, model providers, repository permissions and code-review safety.

AI Platform

LM Studio

Independent LM Studio guide covering local-model setup, hardware fit, offline expectations, licenses and practical evaluation steps.

AI Platform

Onyx

Independent Onyx guide covering enterprise search, RAG, connectors, self-hosting, permissions and deployment checks.

Use one fair evaluation method

Run every coding option on the same small repository task with identical tests, permissions and review rules. Measure diff quality, test results, hidden dependency changes and the time needed for a human to understand the patch.

Coding agents can read files, propose edits and sometimes run commands, so the permission boundary matters as much as model quality. Use a disposable branch, remove credentials, limit accessible directories and begin with a task that already has a failing automated test. Do not let a demonstration repository become a route to production secrets.

Measure whether the change is scoped, understandable and compatible with project conventions. A solution that passes one visible test may still introduce a security issue, hidden dependency, migration risk or maintainability cost. Review the complete diff and terminal history, then run linting, unit tests, integration tests and a clean production build.

Record model-provider charges separately from the editor or agent subscription. Open-source agent code does not automatically make hosted inference private or free, and local execution does not remove the need to review model licenses and downloaded artifacts.

Minimum comparison checklist

  • Work on a clean branch with no secrets and limited permissions.
  • Review commands, diffs, dependencies and migrations before execution.
  • Run the repository's own lint, tests, security checks and production build.

Preserve the repository revision, tool mode, permissions and test output with the date; rerun the coding comparison after major agent, model or IDE changes.

Official reference points

Use these first-party pages to confirm current product documentation, availability and policies before relying on a comparison.