lisa-rails

Lisa

Lisa is a governance layer for AI-assisted software development. It ensures that AI agents — whether running on a developer's machine or in CI/CD — follow the same standards, workflows, and quality gates.

What Lisa Does

Intent Routing

When a request comes in (from a human, a JIRA ticket, or a scheduled job), Lisa classifies it and routes it to the appropriate flow. Flows are ordered sequences of specialized agents, each with a defined role.

A request to fix a bug routes to a different flow than a request to build a feature or reduce code complexity. The routing is automatic based on context, but can be overridden explicitly via slash commands.

Flows and Agents

A flow is a pipeline. Each step in the pipeline is an agent — a scoped AI with specific tools and skills. One agent investigates git history, another reproduces bugs, another writes code, another verifies the result.

Agents delegate domain-specific work to skills — reusable instruction sets that can be invoked by agents, by slash commands, or by CI workflows. The same skill that triages a JIRA ticket interactively is the same skill invoked by the nightly triage workflow.

Flows can nest. A build flow includes a verification sub-flow, which includes a ship sub-flow. This composition keeps each flow focused while enabling complex end-to-end workflows.

Quality Gates

Lisa enforces quality through layered gates:

• Rules are loaded into every AI session automatically. They define coding standards, architectural patterns, and behavioral expectations. The AI follows them because they're part of its context.
• Git hooks are hard stops. Pre-commit hooks run linting, formatting, and type checking. Pre-push hooks run tests, coverage checks, security audits, and dead code detection. Nothing ships without passing.
• Claude hooks bridge AI actions to project tooling — ensuring that when the AI commits, pushes, or creates a PR, the project's quality infrastructure runs.

Location Agnostic

The same rules, skills, and quality gates apply everywhere:

• On a developer's workstation running Claude Code interactively
• In a GitHub Action running a nightly improvement job
• In a CI workflow responding to a PR review comment

The analytical logic lives in skills. The enforcement lives in hooks and rules. The orchestration adapts to context — using MCP integrations locally and REST APIs in CI — but the standards don't change.

Template Governance

Lisa distributes its standards to downstream projects as templates. When a project installs Lisa, it receives:

• Linting, formatting, and type checking configurations
• Test and coverage infrastructure
• CI/CD workflows
• Git hooks
• AI agent definitions, skills, and rules

Templates follow governance rules: some files are overwritten on every update (enforced standards), some are created once and left alone (project customization), and some are merged (shared defaults with project additions).

Quick Start

curl -fsSL https://claude.ai/install.sh | bash

Ask Claude: "I just cloned this repo. Walk me through setup."

Working With Lisa

Ask Claude: "I have JIRA ticket [TICKET-ID]. Research, plan, and implement it."

Or use slash commands directly:

• /fix — route through the bug fix flow
• /build — route through the feature build flow
• /improve — route through the improvement flow
• /investigate — route through the investigation flow
• /jira:triage <TICKET-ID> — analytical triage gate: detect ambiguities, edge cases, and verification methodology
• /plan:improve-tests <target> — improve test quality by analyzing and strengthening weak or brittle tests

Ask Claude: "What commands are available?"