act101 vs Groundrule

act101 empowers engineers to refactor and port code across 163 languages with precision. It’s designed for individual developers and teams who want to ensure their AI coding agents produce reliable, tested changes without guesswork. By analyzing code, executing refactors, and providing deterministic merge verdicts, act101 transforms the coding process into a structured and verifiable workflow.

The platform operates in three stages: Analyze, Act, and Attest. First, it analyzes the codebase with 41 analyzers to identify potential issues. Then, it applies one of 183 refactor operations, ensuring changes are made efficiently. Finally, it attests to the changes with a clear verdict and rollback options, allowing developers to maintain control over their code quality. With act101, you can trust that every modification is backed by thorough analysis and testing.

Best for: Individual engineers and codebase owners seeking reliable AI refactoring.

• Code refactoring
• Code analysis
• Porting code
• Automated testing
• Quality assurance

See the full listing - act101 on ScrollLaunch.

AI agents now write a large share of your code. Your engineering standards didn't come along: they live in wikis, review comments and the heads of a few senior people, and every agent file (AGENTS.md, CLAUDE.md, Cursor rules, Copilot instructions) drifts into its own copy.

Groundrule turns those standards into one rulebook, teaches it to every coding agent, and checks every change against it.

**One rulebook.** Write a standard once: the requirement, why it exists, how to fix a violation, a severity and a stage. Start from curated packs (security baseline, TypeScript/Node, Python, Go, Java/Spring, React, architecture, Docker, Kubernetes, Terraform, GitHub Actions, testing, agent hygiene) and add your own.

**Every agent reads it.** One `groundrule sync` writes AGENTS.md, CLAUDE.md, Cursor rules and Copilot instructions from the same source, and a stop hook plus an MCP server let agents check their own work before they finish.

**Start from what your code already does.** `groundrule scan` reads the rules a repository already keeps (layer boundaries, placement conventions, package gates, imported from your existing docs too) and sends proposals to a review inbox, each with its evidence. Accept, and it's a standard.

**Checked on every pull request.** Deterministic checks run in CI and on commits. Each finding names what failed, which standard, the evidence (file and line) and the fix. Blockers stop the merge; everything else teaches.

**Roll out on evidence.** Every rule moves through observe → teach → advise → enforce, with the data to justify each step. A compliance report shows pass rate, rules in effect, exceptions used and what commits declare about coding agents, exportable as CSV.

The core (CLI, checks, packs, hooks, MCP server) is open source under Apache-2.0 and works with no account. The hosted workspace adds the rulebook, inbox, rollout stages, team and repository settings, and compliance reports. Free for small teams; open-source projects stay free.

Best for: Engineering teams that ship with AI coding agents: platform and staff engineers, tech leads and engineering managers who own code quality, architecture and security standards.

• Standards for coding agents
• AGENTS md generation
• Architecture rule enforcement
• PR compliance checks
• Security baseline enforcement
• Agent file drift detection

See the full listing - Groundrule on ScrollLaunch.