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Taskless turns corrections into rules so the same mistake never slows you down twice. You can start using it right now with no sign-up required.

Run the Taskless CLI in any repository that has a coding agent configured (e.g., a .claude/, .cursor/, .opencode/, or .agents/ directory):

Terminal window
npx @taskless/cli

This installs the consolidated Taskless skill into each detected tool directory. The skill is a thin router. When your agent needs to act, it fetches the current recipe from the CLI via npx @taskless/cli help <topic>.

Ask your coding agent how to get started with Taskless. Say something like “help me get started with Taskless”, or run /tskl onboard. The agent reads through your codebase and its history, finds the conventions and patterns worth capturing as deterministic rules, and helps you turn the strongest candidates into your first rules.

Ask your coding agent to create a rule using natural language:

“Create a taskless rule that catches direct fetch() calls without error handling”

Taskless is local-first. The agent authors the rule on your machine whenever it reasonably can, writing a static rule to .taskless/rules/ and validating it locally, with no account or API calls. When a rule genuinely needs the Taskless service, the agent tells you before using it. See Authoring Rules for how the destination gets chosen.

Run your rules against your codebase:

Terminal window
npx @taskless/cli check

Any matches are reported with file, line, severity, and message. The command exits with code 1 on error-severity matches, so it’s suitable for CI pipelines.

You’re using Taskless.

  • Create rules: your coding agent generates static analysis rules locally from natural language descriptions
  • Improve rules: iterate on existing rules to fix false positives, broaden coverage, or adjust severity
  • Check rules: run all rules against your codebase from the CLI or CI
  • Delete rules: remove rules you no longer need

With a free Taskless account, you unlock:

  • AI-powered rule generation: Taskless generates higher-quality rules using its API, with validation and test cases
  • GitHub integration: create rules from PR comments, issues, and the dashboard, delivered as pull requests
  • Advanced features: organization controls, rule-based memory management, auditing, and rule tracing

Ready to connect? See Full Setup with GitHub.

  • Be specific about the pattern. “Detect direct fetch() calls without error handling” beats “improve error handling.”
  • Include code examples. A “bad” example (what should be caught) and a “good” example (what it should look like instead) improve generation quality.
  • Specify the language. Taskless can infer it, but stating it explicitly avoids ambiguity.
  • Explain the “why”. Context about why the pattern is a problem helps generate better messages and fixes.