An AI engineering board for issues, PRs, and repository reviews.
CodeCouncil turns software work into a multi-agent engineering workflow:
plan → code → test → review → security check → merge recommendation
It is not just another coding chatbot.
It behaves more like a small engineering board where different AI roles collaborate to analyze an issue, inspect a repository, review changes, surface risks, and recommend whether a change is ready to move forward.
Most AI coding tools optimize for:
- faster code generation
- longer prompts
- more autonomous edits
- better autocomplete
CodeCouncil optimizes for something else:
- clear task breakdown
- multi-role engineering review
- test and quality visibility
- security and maintainability checks
- final merge recommendation with evidence
In other words:
CodeCouncil is not just an AI that writes code.
It is an AI engineering board that helps teams reason before they merge.
CodeCouncil models software delivery as a board of specialized roles.
Typical roles include:
- Planner Agent — breaks down issues into implementation steps
- Coder Agent — proposes file changes and patch directions
- Test Agent — runs tests and identifies missing coverage
- Reviewer Agent — checks correctness, style, and design issues
- Security Reviewer — flags secrets, risky config, unsafe patterns
- Architecture Reviewer — inspects module boundaries and system shape
- Performance Reviewer — highlights potential bottlenecks
- Maintainability Reviewer — surfaces long-term complexity risks
Instead of asking a single model to do everything, CodeCouncil lets multiple roles contribute to a shared engineering verdict.
Software work is often fragmented:
- issues are vague
- repository context is scattered
- code changes are hard to evaluate quickly
- reviews are inconsistent
- risks are found too late
- merge decisions are under-explained
CodeCouncil helps by creating a visible workflow around the questions:
- What exactly needs to be built?
- Which files are likely involved?
- What tests should exist?
- What are the review concerns?
- Are there security or maintainability risks?
- Is this ready to merge, or not yet?
Turn a GitHub issue or task into an engineering workflow:
- clarify scope
- break down tasks
- identify likely files
- suggest implementation direction
- check tests and risks
- produce a merge-readiness recommendation
Review a change like an AI review board:
- summarize the diff
- identify correctness issues
- surface review comments
- check security-sensitive changes
- summarize confidence and risk
Review an entire repository like a technical council:
- architecture review
- performance review
- security review
- maintainability review
- overall engineering health summary
Issue / Repo URL
↓
Context loading
↓
Planner Agent
↓
Coder / Reviewer / Test / Security / Architecture Agents
↓
Evidence board
↓
Merge / revision recommendation