🐿SNARKY SQUIRREL
PRREVIEWER
⚲SECURITY
{ }CODE QUALITY
β—†LANGGRAPH
βˆ‘SCORE
snarkyΒ·squirrel
Multi-Agent Β· LangGraph Β· Bedrock
Booting supervisor 00%
SUPERVISORSECURITYQUALITYSCORE
Agentic PR Reviewer

Snarky Squirrel

A multi-agent reviewer that reads your diff and scores it.

Automated pull-request reviewer that runs a multi-agent LangGraph pipeline, scores code quality and security findings on a 0–10 scale, and optionally posts a structured review comment to GitHub. Built on AWS Bedrock (Claude Haiku), DynamoDB, FastAPI, and Cognito auth.

Sample Output

Security
8.5
Code Quality
7.0
Critical Findings
0
Should Block
No

Agent Pipeline

01

Supervisor

Routes the pipeline and decides agent execution order via the LLM.

02

Security Agent

Scans the PR diff for vulnerabilities. Runs first.

β†’ security_findings
03

Code Quality Agent

Checks style, complexity, and best practices using prior findings.

β†’ code_quality_findings
04

PR Reviewer Agent

Produces a holistic review reading all prior findings.

β†’ pr_review_findings
05

Summary Agent

Aggregates all findings into a scored report and lineage trace.

β†’ summary_report

Score Formula

score = 10 βˆ’ (CRITICAL Γ— 5 + HIGH Γ— 2 + MEDIUM Γ— 1 + LOW Γ— 0.5)

A CRITICAL finding sets should_block = true.

Setup

Features

Multi-agent pipelineLangGraph supervisor + specialist agents with shared DynamoDB memory.
Flexible LLM backendsOllama, Docker Model Runner, or AWS Bedrock β€” switched via one env var.
Cognito authOAuth2 via AWS Cognito Hosted UI with RS256 JWT validation and invite-only access.
Data lineagePer-run agent trace stored in DynamoDB, surfaced in the web UI sidebar.
GitHub integrationFetches PR diffs via GitHub API. Posts review comments back β€” HMAC-verified webhooks.
Evaluation frameworkOffline, shadow, and online eval modes with thumbs feedback and aggregate metrics.
Cost~$0.05–0.12 per PR review on AWS (Bedrock Haiku + DynamoDB on-demand + t3.micro).

Links

Questions, issues, or ideas β€” open a GitHub issue or reach out directly.

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