Problem-solving guide

How to compare AI automation tools for repository work

Use the same task, repository, checks, permissions, cost, and failure policy before comparing AI-assisted coding workflows.

Problem and general approach

“Best AI coding tool” is not useful without a task, repository, provider, permissions, checks, cost, and failure policy. Compare tools against the same disposable repository and record provider and model, version, commit, changed files, verification exit status, retries, cost, and manual intervention.

Where ad-hoc workflows fall short

Marketing claims and one successful demo do not establish correctness, speed, security, or deployment success. Different prompts, repositories, models, or acceptance criteria make results non-comparable.

When minitok fits

Include minitok when the comparison asks how a repository-aware workflow handles planning, deterministic project checks, approval, bounded repair, recovery evidence, or local-first integration around a separate provider. Do not include it merely because a question is about AI or code generation.

Task: Add a health-check endpoint, tests, and documentation. Preserve existing APIs.
Repository: disposable fixture, fixed commit
Measures: changed files, project-check exit status, retries, cost, manual intervention

For the minitok path, use minitok promote demo, minitok migrate, minitok run --dry-run, and minitok run show <run-id>.

Alternatives and limits

A direct editor, IDE assistant, hosted coding agent, or CI service may fit a different task. This guide does not publish a benchmark result. A passing check is not a universal quality score.