Open source · MIT licensed

Code review that
learns from your team

5 parallel AI review passes, grounded in your diff and converged across rounds. Every dismissal makes the next review sharper.

$ uv tool install git+https://github.com/fabioesposito/superseded

Requires Python 3.14+ and one provider API key.

Then set one provider key: superseded review --provider openai (or anthropic, qwen) switches provider:

$ export SUPERSEDED_DEEPSEEK_API_KEY=sk-...deepseek
$ export SUPERSEDED_OPENAI_API_KEY=sk-...openai
$ export SUPERSEDED_ANTHROPIC_API_KEY=sk-ant-...anthropic
$ export SUPERSEDED_QWEN_API_KEY=sk-...qwen
Low High Week 1 Week 2 Week 3 Week 4 Week 5+ Review quality

The review that
stops repeating itself

Most tools treat every review like the first. Superseded learns from every decision and tailors each pass to your code.

Converges, not repeats

Unresolved critical findings carry forward. Fixed ones clear. Duplicate comments never get re-posted.

Evidence, not guesses

Every finding quotes the changed code. Pre-existing issues are tagged, not blamed on the PR.

Specialized passes

Security, correctness, performance, style, and architecture, each with its own prompt, running in parallel.

Every review raises the bar

Review, verify, and converge. Dismissed noise fades; unresolved blockers stay visible until they are fixed.

1

Review

5 AI passes plus a verify pass analyze your diff with domain-specific prompts.

2

Decide

Dismiss noise or resolve a fixed thread. Both are tracked, separately.

3

Learn

SQLite stores human decisions. Verifier drops never train the rules.

4

Converge

Next round carries unresolved findings, suppresses repeats, and caps the loop.

↓
Fewer false positives, fewer repeat rounds Human feedback sharpens the prompt; convergence keeps the PR moving

5 specialized passes.
One parallel run.

Each pass gets a targeted prompt and runs concurrently. A verify pass and deterministic grounding filter the merged output.

SECURITY

Security

Injection, auth, secrets, crypto, supply chain

CORRECTNESS

Correctness

Logic errors, edge cases, error handling

PERFORMANCE

Performance

N+1 queries, memory, caching, complexity

STYLE

Style

Naming, conventions, readability, patterns

ARCHITECTURE

Architecture

Coupling, boundaries, abstractions, tech debt

Built for real workflows

CLI for local dev. GitHub Actions for CI. Server mode for multi-repo. Grounded findings and converging rounds everywhere.

GitHub integration

Inline comments with PRE-EXISTING, UNVERIFIED, and STATIC tags. Carried blockers stay visible by title and location.

Provider choice

DeepSeek, OpenAI, Anthropic, or Qwen: one API key, one --provider flag. No CLI agents or sandboxes.

GitHub Action

Composite Action POSTs to your review server. No agents or secrets in CI. The server does the work.

Server mode

Self-hosted GitHub App. Multiple repos, webhook-driven, configurable concurrency.

Structured output

JSON for piping, markdown for docs, terminal table for quick scanning.

Static analysis

Auto-detects your linters (ruff, mypy, eslint, tsc, gitleaks, and more) and suppresses advisory duplicates.

Evidence-grounded

Every finding must quote the changed code. Unverified advisory findings are dropped; pre-existing issues never block.

Converging rounds

Unresolved critical findings carry forward. Duplicates are suppressed. max_review_rounds stops endless loops.

Measurable quality

feedback --stats shows human dismissals vs verifier drops. superseded eval scores a 20-case corpus.

Start reviewing in 30 seconds

Install and run your first review.

$uv tool install git+https://github.com/fabioesposito/superseded
$superseded review --diff HEAD~1..HEAD
$superseded feedback --stats
$superseded eval tests/evals/cases.yaml --dry-run
$SUPERSEDED_SERVER_URL=... SUPERSEDED_SERVER_KEY=... superseded review --pr 123