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Tell AI Once.

Better code out of the coding agent you already use. You already write constraints: tests, types, a linter config. Taskless adds the one that covers what your codebase decided, enforced deterministically on every PR, in every IDE, on every run.

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No signup required to generate rules locally.

agent
Taskless Rules
Run 1✕ Disallowed any type
Run 2✕ Disallowed as unknown as cast
Run 3✕ Disallowed T extends any in generic
Run 4✕ Disallowed any in conditional infer
Markdown Rules
Run 1⚠ Use stricter types here
Run 2✓ Looks fine to me
Run 3⚠ Consider using generics
Run 4✓ No issues found
‹›
Markdown Rules vs. Taskless Rules across four runs
RunMarkdown RulesTaskless Rules
Run 1Use stricter types hereDisallowed any type
Run 2Looks fine to meDisallowed as unknown as cast
Run 3Consider using genericsDisallowed T extends any in generic
Run 4No issues foundDisallowed any in conditional infer

Markdown Rules
Don’t Work

AGENTS.md, skills/, .cursor/rules. They all inject markdown into the AI’s prompt and hope it listens. Different answer every time.

Taskless writes a rule and hands it to something that can actually decide it. Real analysis, not prompt engineering. Same result, every run.

Code review bots guess. Taskless knows.

A Constraint for
Every Convention

You describe, Taskless routes. It picks whatever can decide the rule: a syntax tree, the prose itself, your own linter, or a check that reads across files.

25+ languages and the prose you write, locally, with no account. A rule your linter can express goes into that tool’s own dialect, so your lint step runs it. When the answer is more complex, Taskless Cloud steps in and writes secure, testable code.

Deterministic By Design

Not AI opinions. Not prompt engineering. Rules that produce the same result every time.

Deterministic rule check passes consistently across runs

Same Result, Every Run

AI reviewers vary run to run. Taskless doesn’t. Your rules produce the same result whether it’s Monday or Friday, first PR or thousandth.

Code review rules sourced from team decisions

Your Decisions, Not AI Opinions

Rules come from your corrections, not generic training data. Every rule traces to something your team actually decided.

Single source of truth replacing scattered markdown rule files

No Files to Maintain

No AGENTS.md to keep current. No skills/ to curate. No .cursor/rules to sync. Correct a mistake and move on.

Each correction compounds into the next pull request

Compounds Over Time

Every correction becomes a rule. Every rule makes the next PR cleaner. Your codebase gets better without meetings about it.

Do More With
Taskless Cloud

The free CLI runs locally in your terminal and IDE with no account. Taskless Cloud is the upgrade: runtime rules, full provenance, and team-scale enforcement across your whole org.

Runtime RulesEnforce your rules at runtime across the whole org, not just at author time.
ProvenanceEvery rule traces back to the PR, issue, or decision it came from.
…and moreGitHub integration, team management, data retention, offloaded inference, and tamper-proof signatures.
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Install in One Command

Detects Claude Code, Cursor, and OpenCode. Works with Codex and anything else that supports Agent Skills. No account required to start.

Frequently Asked Questions

Is Taskless free?
Yes. The base skills are free and MIT licensed. The Taskless service is free for individual developers and small teams, with usage caps.
Is this another AI code reviewer?
No. AI code reviewers are LLMs. They give different feedback every run because that’s how language models work. Taskless creates deterministic rules from your corrections. Same input, same result, every time. It’s not reviewing your code with AI. It’s enforcing your team’s decisions with real analysis.
How is this different from AGENTS.md or Cursor Rules?
AGENTS.md, .cursor/rules, the skills/ directory, and similar standards all work the same way. Markdown gets injected into the AI’s prompt. The AI might follow it. Or it might not, especially in long conversations, complex tasks, or after model updates. Taskless creates rules that are analyzed rather than interpreted: a syntax tree for code, the words themselves for prose. They’re not suggestions to an LLM. They’re deterministic checks that pass or fail the same way every time. Think of it as the difference between asking someone to remember a rule and writing an automated test for it.
How does Taskless learn from my corrections?
Tag @taskless on a pull request or issue, use the dashboard, or create rules directly from your IDE with Agent Skills. Taskless routes your correction to whatever can decide it: a syntax tree, the prose itself, your own linter, or a check that reads across files, whichever fits the problem.
What if a rule is wrong or needs updating?
You own your rules. Ask Taskless to revise them, or update them yourself with your AI coding agent. Every rule comes with pass/fail examples so you can see exactly what it catches.
Do I need to change how my team works?
No. Once the first rule is in place, Taskless runs in the background like any other CI step. Nothing new to learn, nothing to context-switch into.
Does Taskless see my code?
Only when you ask it to. Tagging @taskless on a PR is an explicit request. Rules are generated using coding agents with guardrails built, recursively, with Taskless itself. Every rule includes fixtures so you can see exactly what’s being checked.

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