Menu
AI-powered code review CLI — deterministic pipelines + LLM agent, battle-tested at Alibaba scale
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
In-process vector database for AI applications — embed vector search, hybrid retrieval, and full-text search directly into your application without managing a separate server.
LLM-powered knowledge extraction CLI — transform unstructured text into structured knowledge (graphs, hypergraphs, spatio-temporal graphs) with a single command.
Give your AI agent one-click internet access — Twitter, Reddit, YouTube, GitHub, Bilibili, and more. Zero API fees.
Generate token-efficient CLIs for AI agents by reading API docs and studying community patterns. Prints Go binaries + Claude Code skills + MCP servers.
Terminal AI coding agent with video input, subagents, MCP support, and ACP editor integration
AI agent skill that enforces minimal code output — 80-94% less code, prevents over-engineering
Baseado na classificação ocupacional SOC
| name | open-code-review |
| description | AI-powered code review CLI — deterministic pipelines + LLM agent, battle-tested at Alibaba scale |
| version | 1.0.0 |
| author | Hermes Agent |
| license | Apache-2.0 |
| platforms | ["linux","macos"] |
| metadata | {"hermes":{"tags":["code-review","ai","cli","security","devops"],"related_skills":["github-code-review"]}} |
Production-proven AI code review tool from Alibaba. Reads Git diffs, sends changed files to a configurable LLM, and generates structured review comments with line-level precision.
# Clone and build
git clone https://github.com/alibaba/open-code-review.git
cd open-code-review
go build -o ocr ./cmd/ocr
# Or download pre-built binary from releases
# Review current branch against main
ocr review --base main --head HEAD
# Review specific commit
ocr review --commit abc123
# Review with custom LLM endpoint
ocr review --base main --endpoint https://your-llm-endpoint/v1
# GitHub Actions example
- name: AI Code Review
run: |
ocr review --base ${{ github.event.pull_request.base.sha }} \
--head ${{ github.event.pull_request.head.sha }} \
--format github
# .ocr.yaml
llm:
provider: openai
model: gpt-4
endpoint: https://api.openai.com/v1
rules:
- npe
- thread-safety
- xss
- sql-injection
- custom-rules.yaml
--max-files to batch.# Run against a known-good commit
ocr review --commit HEAD --verbose
# Check output format
ocr review --base HEAD~1 --head HEAD --format json | jq .