local-review

README

local-review

Local, BYOK code review for any language.
Runs against a git diff, hands it to whichever LLM you point it at, prints findings.
No SaaS, no telemetry, no signup.

Install • Quick Start • Multi-LLM • Checklist • Website

📋 Looking for the human-readable code review checklist this tool implements? See CHECKLIST.md — OWASP 2025-aligned, with severity tiers and concrete measurables. Use it for human reviews, or run local-review review to get an LLM pass against the same rules.

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What it is, what it isn't

✅ What it is	❌ What it isn't
A local CLI that reviews a git diff using LLMs you've already authenticated	A replacement for Claude's /review or /simplify — those are single-prompt commands; this is multi-LLM diff orchestration
An orchestrator that runs Claude / Gemini / Codex CLIs in parallel and merges findings into one report	"Code never leaves your machine" — the diff still goes to whichever LLM you authenticate (run Ollama for true offline)
BYOK — your API key, requests go direct to the vendor (no middleman server)	A SaaS — no hosted dashboard, no account, no team collaboration features
A pre-commit gate — exits non-zero on major / critical findings so hooks can block the commit	A linter or static analyzer — it's LLM-based, with the heuristic tradeoffs that implies
A single Go binary — no Node, no Python, no Docker, no telemetry	A chat interface — reads a diff, prints findings, exits

Why

Reviewer tools today are mostly:

• SaaS — your code leaves the building. Hard sell for enterprise.
• CI-only — you find out about issues after pushing the branch.
• Tied to a vendor — single-provider lock-in (OpenAI-only or Anthropic-only).
• Runtime-heavy — Node/Python/Java install required just to run the reviewer.

local-review is the opposite: a single static binary that runs locally on a diff, sends that diff to whatever LLM(s) you've authenticated, and prints findings. Privacy posture depends on which LLM(s) you point it at — see the Privacy section for the matrix. Run with Ollama for fully-offline review.

Install

curl -fsSL https://raw.githubusercontent.com/mshykov/local-review/main/install.sh | sh

Or grab a binary from Releases.

Or build from source:

go install github.com/mshykov/local-review/cmd/local-review@latest

Quick start

# 1. Install one or more LLM CLIs (each one is a "team mate" reviewing your code)
npm install -g @anthropic-ai/claude-code   # Claude   — free tier via `claude login`
npm install -g @google/gemini-cli          # Gemini   — free key from Google AI Studio
npm install -g @openai/codex               # Codex    — ChatGPT Plus or OPENAI_API_KEY

# 2. Authenticate the ones you want
claude login
export GEMINI_API_KEY=...
export OPENAI_API_KEY=...

# 3. Check who's ready
local-review doctor

# 4. Review your branch — every authenticated CLI runs in parallel and findings get merged
local-review review

That's it. local-review review is the canonical command — it runs every LLM CLI that's installed AND authenticated, in parallel, and prints a merged report.

By default findings at warning+ are shown and major/critical exit non-zero (good for pre-commit hooks).

If you don't have any LLM CLI installed, run local-review init to set up a single-LLM review against any OpenAI-compatible API instead.

Multi-LLM is the default

Every authenticated LLM CLI runs by default. No opt-in, no enabling — if you claude login, claude runs. If you export OPENAI_API_KEY=..., codex runs. If you don't authenticate one, it's silently skipped.

# Default: all active LLMs
local-review review

# Restrict to a subset (overrides config)
local-review review --only claude,gemini

# Pick a specific model for one agent
local-review review --claude-model claude-opus-4-7

# Use a specific agent to do the merge
local-review review --merge-with claude

Supported LLMs

LLM	Free Option	Installation
Claude	✅ Free tier via claude login (claude.ai account)	npm install -g @anthropic-ai/claude-code
Gemini	✅ Free API key from Google AI Studio	npm install -g @google/gemini-cli
Codex	⚠️ ChatGPT Plus ($20/mo) or OpenAI API key (pay-per-token)	npm install -g @openai/codex

How it works:

1. Detects installed LLM CLIs and which are authenticated (local-review doctor)
2. Runs every authenticated CLI in parallel
3. Saves each review to .local-review/reviews/<branch>/<commit>_<llm>.md
4. Merges findings (dedup, consensus tagging) into one report
5. Prints the merged report to stdout (also saved as <commit>_merged.md)

Authentication — what each LLM needs:

LLM	Default (preferred)	Alternative
Claude	claude login — Anthropic OAuth, works with the free tier on a claude.ai account	export ANTHROPIC_API_KEY=... (paid API access)
Gemini	export GEMINI_API_KEY=... — free key from Google AI Studio	gemini /auth for Google OAuth
Codex	codex login — uses your ChatGPT Plus subscription ($20/mo)	export OPENAI_API_KEY=... — pay-per-token; usually cheaper for occasional review use

Run local-review doctor to see which CLIs you have installed and authenticated. Each row that isn't ✓ ready tells you exactly what to fix.

Configuration is optional. If ~/.local-review.yml or ./.local-review.yml exists it overrides defaults; CLI flags override config:

# .local-review.yml — example: pin specific models, disable codex
llms:
  claude:
    model: claude-opus-4-7

  gemini:
    model: gemini-2.0-flash
    api_key_env: GEMINI_API_KEY

  codex:
    enabled: false           # opt-out (still runs if --only codex is passed)

merge:
  preferred_llm: auto        # or: claude, gemini, codex

See examples/.local-review-multi.yml for full schema.

Configure

local-review loads YAML from a cascade — built-in defaults → ~/.local-review.yml → ./.local-review.yml → CLI flags.

A minimal ~/.local-review.yml:

provider:
  base_url: https://api.openai.com/v1
  model: gpt-4o-mini
  api_key_env: LOCAL_REVIEW_API_KEY
review:
  min_severity: warning
  max_findings: 20

See examples/.local-review.yml for the full schema with comments.

Switching providers

local-review speaks the OpenAI chat-completions API — every major provider supports it:

Provider	base_url	Notes
OpenAI	https://api.openai.com/v1	Default. gpt-4o-mini is cheap; gpt-4o for harder reviews.
Anthropic	https://api.anthropic.com/v1	Anthropic's OpenAI-compatible endpoint. Use exact model names (e.g. claude-sonnet-4-6, claude-opus-4-7).
Mistral	https://api.mistral.ai/v1	EU-hosted; Codestral is code-tuned. See examples/.local-review.mistral.yml.
DeepSeek	https://api.deepseek.com/v1	Cheapest cloud option. See examples/.local-review.deepseek.yml.
Groq	https://api.groq.com/openai/v1	Fast inference; Llama, Qwen, etc.
Together	https://api.together.xyz/v1	Llama, Mixtral, Qwen — many open-weights options.
OpenRouter	https://openrouter.ai/api/v1	One key, all models.
Ollama	http://localhost:11434/v1	Fully offline. No data leaves your machine.
vLLM	http://your-host/v1	Self-hosted.

The fastest way to set any of these up is local-review init, which writes a working .local-review.yml from a preset.

Pre-commit hook

cp examples/pre-commit .git/hooks/pre-commit
chmod +x .git/hooks/pre-commit

Or with husky / lefthook: run local-review staged in the pre-commit step.

Bypass for emergencies: LOCAL_REVIEW_SKIP=1 git commit ....

CLI

# Review (multi-LLM by default; falls back to single-LLM via configured provider if no CLI is active)
local-review review [<base>]         # canonical: current branch vs <base> (default: main)
local-review staged                  # review git diff --cached (pre-commit)
local-review commit [<rev>]          # review one commit (default: HEAD)
local-review branch [<base>]         # alias of `review` for muscle-memory

# Utilities
local-review init                    # interactive setup (writes .local-review.yml)
local-review doctor                  # check LLM installations + auth state
local-review config                  # print resolved config (API keys masked)
local-review version                 # print version

Common flags:

Flag	Purpose
--only <list>	Comma-separated agents to run (e.g. claude,gemini); overrides config
--claude-model <id>	Override claude's model (same for --gemini-model, --codex-model)
--merge-with <agent>	Pick which agent merges findings (default: auto)
--model <id>	Override provider.model (single-LLM fallback only)
--base-url <url>	Override provider.base_url (single-LLM fallback only)
--min-severity <tier>	nit / info / warning / major / critical (single-LLM fallback only)
--max-findings <n>	Cap output (single-LLM fallback only)
--json	Emit JSON (single-LLM fallback only — see below)

In multi-LLM mode the merger returns markdown, not structured findings, so --json, --min-severity, and --max-findings are ignored: they only take effect in the single-LLM fallback path (when no LLM CLI is authenticated and we hit the configured provider: directly). Multi-LLM emits a stderr warning when those flags are passed so you know they had no effect. A structured-JSON multi-LLM output mode (where the merger emits both markdown and a JSON envelope) is on the v0.7 roadmap.

Config wins by default; flags override config at runtime (e.g., --only codex runs codex even if your config sets codex.enabled: false).

Exit codes:

• 0 — no blocking findings
• 2 — major or critical findings present (pre-commit gate)
• non-zero — local-review itself failed (the hook ignores this and lets the commit through)

Prompt packs

local-review ships with packs for default, typescript, go, python, rust, with more coming. The CLI auto-picks based on the dominant language in your diff. Force a specific pack with review.prompt_pack: <id> in your YAML config.

Each pack is a markdown file (in internal/prompts/packs/) that defines:

• What to look for (priority-ordered)
• Severity tiering rules
• Hard rules ("never invent code that isn't in the diff")
• Output JSON schema

See docs/prompt-packs.md for how to write or override one.

What it does NOT do (yet)

• No multi-file refactor reasoning. local-review reviews diffs, not architectures.
• No auto-fix / auto-PR. Findings are advisory.
• No GitHub integration in the binary. The --json output is structured for piping into your CI's PR-comment tool of choice. (A local-review github mode is on the roadmap.)
• No telemetry. None. Ever.

For organizations

Distributing to a few hundred engineers? Two patterns work:

1. Org config repo. Drop a .local-review.yml in each project that sets org.config_url: https://your-internal-host/local-review.yml. (Org-config fetching is on the roadmap; today, just commit the YAML to each repo.)
2. One install command in onboarding. curl -fsSL <install.sh> | sh plus an env var = done.

Privacy

local-review is telemetry-free: no analytics, no auto-update calls, no signup, no SaaS. The only network traffic is to the LLM endpoint(s) you configure — either an HTTP call from local-review's built-in client (single-LLM mode) or the authenticated CLI subprocesses (multi-LLM mode). What "private" means therefore depends on which LLM(s) you point it at:

Mode	Where your diff goes
Single-LLM, provider.base_url: http://localhost:11434/v1 (Ollama)	Stays on your machine. Fully offline.
Single-LLM, any cloud provider (OpenAI, Anthropic, Mistral, etc.)	The provider you configured, over TLS. Their privacy policy applies.
Multi-LLM (default) — Claude / Gemini / Codex CLIs	Each authenticated CLI calls its own backend (Anthropic, Google AI, OpenAI). One review fans out to multiple cloud vendors. Your provider.base_url is irrelevant in this mode.
Multi-LLM with --only restricted to a fully-local agent	Roadmap. Will be possible once a fully-local-agent preset lands; today every multi-LLM agent (claude / gemini / codex) calls its own cloud backend.

If you need air-gapped review today, use single-LLM mode against a local Ollama and stay off local-review review (which fans out to authenticated cloud CLIs by default).

Develop

go test ./...
go build -o local-review ./cmd/local-review
./local-review staged

See CONTRIBUTING.md.

License

MIT. See LICENSE.