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Judges Panel

An MCP (Model Context Protocol) server that provides a panel of 45 specialized judges to evaluate AI-generated code β€” acting as an independent quality gate regardless of which project is being reviewed. Combines deterministic pattern matching & AST analysis (instant, offline, zero LLM calls) with LLM-powered deep-review prompts that let your AI assistant perform expert-persona analysis across all 45 domains.

Highlights:

  • Includes an App Builder Workflow (3-step) demo for release decisions, plain-language risk summaries, and prioritized fixes β€” see Try the Demo.

  • Includes V2 context-aware evaluation with policy profiles, evidence calibration, specialty feedback, confidence scoring, and uncertainty reporting.

  • Includes public repository URL reporting to clone a repo, run the full tribunal, and output a consolidated markdown report.

  • 200+ deterministic auto-fix patches (see src/patches/index.ts) plus LLM-powered deep review.

πŸ§ͺ Many commands in printHelp are experimental/roadmap. By default, we show GA commands only. Set JUDGES_SHOW_EXPERIMENTAL=1 to reveal stubs; these may not be wired yet.

CI npm npm downloads License: MIT Tests

πŸ”° Packages

  • CLI: @kevinrabun/judges-cli β†’ binary judges (use npx @kevinrabun/judges-cli eval --file app.ts).

  • MCP/API: @kevinrabun/judges β†’ programmatic API + MCP server (npm install @kevinrabun/judges).

  • VS Code extension: see vscode-extension/.

  • GitHub Action: uses: KevinRabun/judges@main (see CI quickstart).


Quickstart

CLI (one-off)

# Using the CLI package (recommended)
npx @kevinrabun/judges-cli eval --file src/app.ts

# Show GA commands only (default)
npx @kevinrabun/judges-cli --help

# Show experimental/roadmap commands
echo "JUDGES_SHOW_EXPERIMENTAL=1" >> $GITHUB_ENV
npx @kevinrabun/judges-cli --help

# License scan (supply-chain & license compliance)
npx @kevinrabun/judges-cli license-scan --dir .

CLI vs API: If you want to embed Judges in your app (MCP/API), install @kevinrabun/judges. For the command-line, use @kevinrabun/judges-cli (binary judges).

GitHub Action

name: Judges
on: [pull_request, push]
jobs:
  judges:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: KevinRabun/judges@main
        with:
          path: .
          diff-only: true           # evaluate only changed lines in PRs (default true)
          fail-on-findings: true    # fail on critical/high findings
          upload-sarif: true        # upload SARIF to GitHub Code Scanning

Programmatic API (MCP server included)

npm install @kevinrabun/judges
import { evaluateCode } from "@kevinrabun/judges/api";
const verdict = evaluateCode("const password = 'ProdSecret';", "typescript");
console.log(verdict.overallVerdict, verdict.overallScore);

MCP server

The MCP server runs on stdio and is started by your MCP client (VS Code, Claude Desktop, etc.). Configure it in your MCP settings (e.g. mcp.json):

{
  "servers": {
    "judges": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@kevinrabun/judges"]
    }
  }
}

Or run the server directly:

npx @kevinrabun/judges
# Starts the MCP server on stdio

Config file: .judgesrc.json (supports ${ENV_VAR} substitution via expandEnvPlaceholders). See Configuration.


Related MCP server: CodeBase Optimizer

Why Judges?

AI code generators (Copilot, Cursor, Claude, ChatGPT, etc.) write code fast β€” but they routinely produce insecure defaults, missing auth, hardcoded secrets, and poor error handling. Human reviewers catch some of this, but nobody reviews 45 dimensions consistently.

ESLint / Biome

SonarQube

Semgrep / CodeQL

Judges

Scope

Style + some bugs

Bugs + code smells

Security patterns

45 domains: security, cost, compliance, a11y, API design, cloud, UX, …

AI-generated code focus

No

No

Partial

Purpose-built for AI output failure modes

Setup

Config per project

Server + scanner

Cloud or local

One command: npx @kevinrabun/judges-cli eval file.ts

Auto-fix patches

Some

No

No

200+ deterministic patches β€” instant, offline

Non-technical output

No

Dashboard

No

Plain-language findings with What/Why/Next

MCP native

No

No

No

Yes β€” works inside Copilot, Claude, Cursor

SARIF output

No

Yes

Yes

Yes β€” upload to GitHub Code Scanning

Cost

Free

$$$$

Free/paid

Free / MIT

Judges doesn't replace linters β€” it covers the dimensions linters don't: authentication strategy, data sovereignty, cost patterns, accessibility, framework-specific anti-patterns, and architectural issues across multiple files.


Quick Start

Prereqs: Node.js >=18 (>=20 recommended), npx available. The judges CLI binary ships with @kevinrabun/judges-cli (preferred) and also works via npx @kevinrabun/judges.

Packages:

  • CLI: npm install -g @kevinrabun/judges-cli (or npx @kevinrabun/judges-cli ...)

  • MCP/API: npm install @kevinrabun/judges

Use @kevinrabun/judges for the MCP server and programmatic API. Use @kevinrabun/judges-cli when you want the judges terminal command.

Try it now (no clone needed)

# Install the CLI globally
npm install -g @kevinrabun/judges-cli

# Evaluate any file
judges eval src/app.ts

# Pipe from stdin
cat api.py | judges eval --language python

# Single judge
judges eval --judge cybersecurity server.ts

# SARIF output for CI
judges eval --file app.ts --format sarif > results.sarif

# HTML report with severity filters and dark/light theme
judges eval --file app.ts --format html > report.html

# Fail CI on findings (exit code 1)
judges eval --fail-on-findings src/api.ts

# Suppress known findings via baseline
judges eval --baseline baseline.json src/api.ts

# Use a named preset
judges eval --preset security-only src/api.ts

# Use a config file
judges eval --config .judgesrc.json src/api.ts

# Set a minimum score threshold (exit 1 if below)
judges eval --min-score 80 src/api.ts

# One-line summary for scripts
judges eval --summary src/api.ts

# Agentic skills (orchestrated judge sets)
judges skill ai-code-review --file src/app.ts
judges skill security-review --file src/api.ts --format json
judges skill release-gate --file src/app.ts
judges skills   # list available skills

> Full catalog: [`docs/skills.md`](docs/skills.md)


# List all 45 judges
judges list

Additional CLI Commands

# Interactive project setup wizard
judges init

# Preview auto-fix patches (dry run)
judges fix src/app.ts

# Apply patches directly
judges fix src/app.ts --apply

# License compliance scan (copyleft/unknown detection)
judges license-scan --format json --risk high

# Watch mode β€” re-evaluate on file save
judges watch src/

# Project-level report (local directory)
judges report . --format html --output report.html

# Evaluate a unified diff (pipe from git diff)
git diff HEAD~1 | judges diff

# Analyze dependencies for supply-chain risks
judges deps --path . --format json

# Run GitHub App server (zero-config PR reviews)
judges app serve --port 4567

# Run GitHub PR review (gh CLI required)
judges review --pr 123 --repo owner/name --diff-only

# Auto-tune presets and configs
judges tune --dir . --apply

# Create a baseline file to suppress known findings
judges baseline create --file src/api.ts -o baseline.json

# Generate CI template files
judges ci-templates --provider github
judges ci-templates --provider gitlab
judges ci-templates --provider azure
judges ci-templates --provider bitbucket

# Generate per-judge rule documentation
judges docs
judges docs --judge cybersecurity
judges docs --output docs/

# Install shell completions
judges completions bash   # eval "$(judges completions bash)"
judges completions zsh
judges completions fish
judges completions powershell

# Install pre-commit hook
judges hook install

# Uninstall pre-commit hook
judges hook uninstall

πŸ”Ž Tip: The CLI help now defaults to GA commands only. To see experimental/roadmap commands, run:

JUDGES_SHOW_EXPERIMENTAL=1 judges --help

GitHub App (self-hosted webhook)

Run a zero-config PR reviewer as a GitHub App:

# Run the webhook server locally
judges app serve --port 4567

Required env vars:

  • JUDGES_APP_ID – GitHub App ID

  • JUDGES_PRIVATE_KEY or JUDGES_PRIVATE_KEY_PATH – PEM private key

  • JUDGES_WEBHOOK_SECRET – signature verification secret

Optional:

  • JUDGES_MIN_SEVERITY (default: medium)

  • JUDGES_MAX_COMMENTS (default: 25)

  • JUDGES_TEST_DRY_RUN=1 to avoid live network calls during tests

For local testing, you can expose http://localhost:4567/webhook via ngrok http 4567 and configure the GitHub App webhook URL accordingly.

Use in GitHub Actions

Add Judges to your CI pipeline with zero configuration:

# .github/workflows/judges.yml
name: Judges Code Review
on: [pull_request]

jobs:
  judges:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      security-events: write  # only if using upload-sarif
    steps:
      - uses: actions/checkout@v4
      - uses: KevinRabun/judges@main
        with:
          path: src/api.ts        # file or directory
          format: text             # text | json | sarif | markdown
          upload-sarif: true       # upload to GitHub Code Scanning
          fail-on-findings: true   # fail CI on critical/high findings

Outputs available for downstream steps: verdict, score, findings, critical, high, sarif-file.

Use with Docker (no Node.js required)

# Build the image
docker build -t judges .

# Evaluate a local file
docker run --rm -v $(pwd):/code judges eval --file /code/app.ts

# Pipe from stdin
cat api.py | docker run --rm -i judges eval --language python

# List judges
docker run --rm judges list

Or use as an MCP server

1. Install and Build

git clone https://github.com/KevinRabun/judges.git
cd judges
npm install
npm run build

2. Try the Demo

Run the included demo to see all 45 judges evaluate a purposely flawed API server:

npm run demo

This evaluates examples/sample-vulnerable-api.ts β€” a file intentionally packed with security holes, performance anti-patterns, and code quality issues β€” and prints a full verdict with per-judge scores and findings.

The demo now also includes an App Builder Workflow (3-step) section. In a single run, you get both tribunal output and workflow output:

  • Release decision (Ship now / Ship with caution / Do not ship)

  • Plain-language summaries of top risks

  • Prioritized remediation tasks and AI-fixable P0/P1 items

Sample workflow output (truncated):

╔══════════════════════════════════════════════════════════════╗
β•‘             App Builder Workflow Demo (3-Step)             β•‘
β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•

  Decision       : Do not ship
  Verdict        : FAIL (47/100)
  Risk Counts    : Critical 24 | High 27 | Medium 55

  Step 2 β€” Plain-Language Findings:
  - [CRITICAL] DATA-001: Hardcoded password detected
      What: ...
      Why : ...
      Next: ...

  Step 3 β€” Prioritized Tasks:
  - P0 | DEVELOPER | Effort L | DATA-001
      Task: ...
      Done: ...

  AI-Fixable Now (P0/P1):
  - P0 DATA-001: ...

Sample tribunal output (truncated):

╔══════════════════════════════════════════════════════════════╗
β•‘           Judges Panel β€” Full Tribunal Demo                 β•‘
β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•

  Overall Verdict : FAIL
  Overall Score   : 43/100
  Critical Issues : 15
  High Issues     : 17
  Total Findings  : 83
  Judges Run      : 33

  Per-Judge Breakdown:
  ────────────────────────────────────────────────────────────────
  ❌ Judge Data Security              0/100    7 finding(s)
  ❌ Judge Cybersecurity              0/100    7 finding(s)
  ❌ Judge Cost Effectiveness        52/100    5 finding(s)
  ⚠️  Judge Scalability              65/100    4 finding(s)
  ❌ Judge Cloud Readiness           61/100    4 finding(s)
  ❌ Judge Software Practices        45/100    6 finding(s)
  ❌ Judge Accessibility              0/100    8 finding(s)
  ❌ Judge API Design                 0/100    9 finding(s)
  ❌ Judge Reliability               54/100    3 finding(s)
  ❌ Judge Observability             45/100    5 finding(s)
  ❌ Judge Performance               27/100    5 finding(s)
  ❌ Judge Compliance                 0/100    4 finding(s)
  ⚠️  Judge Testing                  90/100    1 finding(s)
  ⚠️  Judge Documentation            70/100    4 finding(s)
  ⚠️  Judge Internationalization     65/100    4 finding(s)
  ⚠️  Judge Dependency Health        90/100    1 finding(s)
  ❌ Judge Concurrency               44/100    4 finding(s)
  ❌ Judge Ethics & Bias             65/100    2 finding(s)
  ❌ Judge Maintainability           52/100    4 finding(s)
  ❌ Judge Error Handling            27/100    3 finding(s)
  ❌ Judge Authentication             0/100    4 finding(s)
  ❌ Judge Database                   0/100    5 finding(s)
  ❌ Judge Caching                   62/100    3 finding(s)
  ❌ Judge Configuration Mgmt         0/100    3 finding(s)
  ⚠️  Judge Backwards Compat         80/100    2 finding(s)
  ⚠️  Judge Portability              72/100    2 finding(s)
  ❌ Judge UX                        52/100    4 finding(s)
  ❌ Judge Logging Privacy            0/100    4 finding(s)
  ❌ Judge Rate Limiting             27/100    4 finding(s)
  ⚠️  Judge CI/CD                    80/100    2 finding(s)

3. Run the Tests

npm test

Runs automated tests covering all judges, AST parsers, markdown formatters, and edge cases.

4. Connect to Your Editor

Install the Judges Panel extension from the Marketplace. It provides:

  • Inline diagnostics & quick-fixes on every file save

  • @judges chat participant β€” type @judges in Copilot Chat, or just ask for a "judges panel review" and Copilot routes automatically

  • Auto-configured MCP server β€” all 45 expert-persona prompts available to Copilot with zero setup

code --install-extension kevinrabun.judges-panel

VS Code β€” manual MCP config

If you prefer explicit workspace config (or want teammates without the extension to benefit), create .vscode/mcp.json:

{
  "servers": {
    "judges": {
      "command": "npx",
      "args": ["-y", "@kevinrabun/judges"]
    }
  }
}

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "judges": {
      "command": "npx",
      "args": ["-y", "@kevinrabun/judges"]
    }
  }
}

Cursor / other MCP clients

Use the same npx command for any MCP-compatible client:

{
  "command": "npx",
  "args": ["-y", "@kevinrabun/judges"]
}

5. Use Judges in GitHub Copilot PR Reviews

Yes β€” users can include Judges as part of GitHub-based review workflows, with one important caveat:

  • The hosted copilot-pull-request-reviewer on GitHub does not currently let you directly attach arbitrary local MCP servers the same way VS Code does.

  • The practical pattern is to run Judges in CI on each PR, publish a report/check, and have Copilot + human reviewers use that output during review.

Create .github/workflows/judges-pr-review.yml:

name: Judges PR Review

on:
  pull_request:
    types: [opened, synchronize, reopened]

jobs:
  judges:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write

    steps:
      - name: Checkout
        uses: actions/checkout@v4

      - name: Setup Node
        uses: actions/setup-node@v4
        with:
          node-version: 20
          cache: npm

      - name: Install
        run: npm ci

      - name: Generate Judges report
        run: |
          npx tsx -e "import { generateRepoReportFromLocalPath } from './src/reports/public-repo-report.ts';
          const result = generateRepoReportFromLocalPath({
            repoPath: process.cwd(),
            outputPath: 'judges-pr-report.md',
            maxFiles: 600,
            maxFindingsInReport: 150,
          });
          console.log('Overall:', result.overallVerdict, result.averageScore);"

      - name: Upload report artifact
        uses: actions/upload-artifact@v4
        with:
          name: judges-pr-report
          path: judges-pr-report.md

This gives every PR a reproducible Judges output your team (and Copilot) can reference.

Option B: Add Copilot custom instructions in-repo

Add .github/instructions/judges.instructions.md with guidance such as:

When reviewing pull requests:
1. Read the latest Judges report artifact/check output first.
2. Prioritize CRITICAL and HIGH findings in remediation guidance.
3. If findings conflict, defer to security/compliance-related Judges.
4. Include rule IDs (e.g., DATA-001, CYBER-004) in suggested fixes.

This helps keep Copilot feedback aligned with Judges findings.


CLI Reference

All commands support --help for usage details.

judges eval

Evaluate a file with all 45 judges or a single judge.

Flag

Description

--file <path> / positional

File to evaluate

--judge <id> / -j <id>

Single judge mode

--language <lang> / -l <lang>

Language hint (auto-detected from extension)

--format <fmt> / -f <fmt>

Output format: text, json, sarif, markdown, html, pdf, junit, codeclimate, github-actions

--output <path> / -o <path>

Write output to file

--fail-on-findings

Exit with code 1 if verdict is FAIL

--baseline <path> / -b <path>

JSON baseline file β€” suppress known findings

--summary

Print a single summary line (ideal for scripts)

--config <path>

Load a .judgesrc / .judgesrc.json config file

--preset <name>

Use a named preset (see Named Presets for all 22 options)

--min-score <n>

Exit with code 1 if overall score is below this threshold

--verbose

Print timing and debug information

--quiet

Suppress non-essential output

--no-color

Disable ANSI colors

judges init

Interactive wizard that generates project configuration:

  • .judgesrc.json β€” rule customization, disabled judges, severity thresholds

  • .github/workflows/judges.yml β€” GitHub Actions CI workflow

  • .gitlab-ci.judges.yml β€” GitLab CI pipeline (optional)

  • azure-pipelines.judges.yml β€” Azure Pipelines (optional)

judges fix

Preview or apply auto-fix patches from deterministic findings.

Flag

Description

positional

File to fix

--apply

Write patches to disk (default: dry run)

--judge <id>

Limit to a single judge's findings

judges watch

Continuously re-evaluate files on save.

Flag

Description

positional

File or directory to watch (default: .)

--judge <id>

Single judge mode

--fail-on-findings

Exit non-zero if any evaluation fails

judges report

Run a full project-level tribunal on a local directory.

Flag

Description

positional

Directory path (default: .)

--format <fmt>

Output format: text, json, html, markdown

--output <path>

Write report to file

--max-files <n>

Maximum files to analyze (default: 600)

--max-file-bytes <n>

Skip files larger than this (default: 300000)

judges hook

Manage a Git pre-commit hook that runs Judges on staged files.

judges hook install    # add pre-commit hook
judges hook uninstall  # remove pre-commit hook

Detects Husky (.husky/pre-commit) and falls back to .git/hooks/pre-commit. Uses marker-based injection so it won't clobber existing hooks.

judges diff

Evaluate only the changed lines from a unified diff (e.g., git diff output).

Flag

Description

--file <path>

Read diff from file instead of stdin

--format <fmt>

Output format: text, json, sarif, junit, codeclimate

--output <path>

Write output to file

git diff HEAD~1 | judges diff
judges diff --file changes.patch --format sarif

judges deps

Analyze project dependencies for supply-chain risks.

Flag

Description

--path <dir>

Project root to scan (default: .)

--format <fmt>

Output format: text, json

judges deps --path .
judges deps --path ./backend --format json

judges baseline

Create a baseline file to suppress known findings in future evaluations.

judges baseline create --file src/api.ts
judges baseline create --file src/api.ts -o .judges-baseline.json

judges ci-templates

Generate CI/CD configuration templates for popular providers.

judges ci-templates --provider github   # .github/workflows/judges.yml
judges ci-templates --provider gitlab   # .gitlab-ci.judges.yml
judges ci-templates --provider azure    # azure-pipelines.judges.yml
judges ci-templates --provider bitbucket # bitbucket-pipelines.yml (snippet)

judges docs

Generate per-judge rule documentation in Markdown.

Flag

Description

--judge <id>

Generate docs for a single judge

--output <dir>

Write individual .md files per judge

judges docs                          # all judges to stdout
judges docs --judge cybersecurity    # single judge
judges docs --output docs/judges/    # write files to directory

judges completions

Generate shell completion scripts.

eval "$(judges completions bash)"        # Bash
eval "$(judges completions zsh)"         # Zsh
judges completions fish | source         # Fish
judges completions powershell            # PowerShell (Register-ArgumentCompleter)

Named Presets

Use --preset to apply pre-configured evaluation settings:

Preset

Description

strict

All severities, all judges β€” maximum thoroughness

lenient

Only high and critical findings β€” fast and focused

security-only

Security-focused β€” disables non-security judges (cost, scalability, docs, a11y, i18n, UX, etc.)

startup

Skip compliance, sovereignty, i18n judges β€” move fast

compliance

Only compliance, data-sovereignty, authentication β€” regulatory focus

performance

Only performance, scalability, caching, cost-effectiveness

react

Tuned for React/Next.js apps β€” enables accessibility, XSS protection

express

Tuned for Express.js APIs β€” middleware security, auth, CORS, rate limiting

fastapi

Tuned for Python FastAPI β€” input validation, async patterns, API security

django

Tuned for Django apps β€” template security, ORM misuse, CSRF

spring-boot

Tuned for Java Spring Boot β€” injection, configuration, actuator security

rails

Tuned for Ruby on Rails β€” mass assignment, CSRF, SQL injection

nextjs

Tuned for Next.js β€” server/client security, API routes, SSR/ISR

terraform

Tuned for Terraform/OpenTofu IaC β€” infrastructure security, compliance

kubernetes

Tuned for K8s manifests β€” security contexts, RBAC, resource limits

onboarding

Smart defaults for first-time adoption β€” suppresses noisy rules

fintech

Financial services β€” PCI DSS, cryptography, authentication, audit

healthtech

Healthcare β€” HIPAA compliance, data sovereignty, encryption, audit trails

saas

Multi-tenant SaaS β€” tenant isolation, rate limiting, scalability

government

Government/public sector β€” compliance, sovereignty, authentication

open-source

Open-source projects β€” documentation, backwards compatibility, security, dependency health

ai-review

AI-generated code review β€” hallucination detection, security, authentication, correctness

judges eval --preset security-only src/api.ts
judges eval --preset strict --format sarif src/app.ts > results.sarif

CI Output Formats

JUnit XML

Generate JUnit XML for Jenkins, Azure DevOps, GitHub Actions, or GitLab test result viewers:

judges eval --format junit src/api.ts > results.xml

Each judge maps to a <testsuite>, each finding becomes a <testcase> with <failure> for critical/high severity.

CodeClimate / GitLab Code Quality

Generate CodeClimate JSON for GitLab Code Quality or similar tools:

judges eval --format codeclimate src/api.ts > codequality.json

Score Badges

Generate SVG or text badges for your README:

import { generateBadgeSvg, generateBadgeText } from "@kevinrabun/judges/badge";

const svg = generateBadgeSvg(85);          // shields.io-style SVG
const text = generateBadgeText(85);        // "βœ“ judges 85/100"
const svg2 = generateBadgeSvg(75, "quality"); // custom label

The Judge Panel

Judge

Domain

Rule Prefix

What It Evaluates

Data Security

Data Security & Privacy

DATA-

Encryption, PII handling, secrets management, access controls

Cybersecurity

Cybersecurity & Threat Defense

CYBER-

Injection attacks, XSS, CSRF, auth flaws, OWASP Top 10

Cost Effectiveness

Cost Optimization & Resource Efficiency

COST-

Algorithm efficiency, N+1 queries, memory waste, caching strategy

Scalability

Scalability & Performance

SCALE-

Statelessness, horizontal scaling, concurrency, bottlenecks

Cloud Readiness

Cloud-Native Architecture & DevOps

CLOUD-

12-Factor compliance, containerization, graceful shutdown, IaC

Software Practices

Software Engineering Best Practices & Secure SDLC

SWDEV-

SOLID principles, type safety, error handling, input validation

Accessibility

Accessibility (a11y)

A11Y-

WCAG compliance, screen reader support, keyboard navigation, ARIA

API Design

API Design & Contracts

API-

REST conventions, versioning, pagination, error responses

Reliability

Reliability & Resilience

REL-

Error handling, timeouts, retries, circuit breakers

Observability

Monitoring & Diagnostics

OBS-

Structured logging, health checks, metrics, tracing

Performance

Runtime Performance

PERF-

N+1 queries, sync I/O, caching, memory leaks

Compliance

Regulatory & License Compliance

COMP-

GDPR/CCPA, PII protection, consent, data retention, audit trails

Data Sovereignty

Data, Technological & Operational Sovereignty

SOV-

Data residency, cross-border transfers, vendor key management, AI model portability, identity federation, circuit breakers, audit trails, data export

Testing

Test Quality & Coverage

TEST-

Test coverage, assertions, test isolation, naming

Documentation

Documentation & Developer Experience

DOC-

JSDoc/docstrings, magic numbers, TODOs, code comments

Internationalization

i18n & Localization

I18N-

Hardcoded strings, locale handling, currency formatting

Dependency Health

Supply Chain & Dependencies

DEPS-

Version pinning, deprecated packages, supply chain

Concurrency

Concurrency & Thread Safety

CONC-

Race conditions, unbounded parallelism, missing await

Ethics & Bias

AI/ML Fairness & Ethics

ETHICS-

Demographic logic, dark patterns, inclusive language

Maintainability

Code Maintainability & Technical Debt

MAINT-

Any types, magic numbers, deep nesting, dead code, file length

Error Handling

Error Handling & Fault Tolerance

ERR-

Empty catch blocks, missing error handlers, swallowed errors

Authentication

Authentication & Authorization

AUTH-

Hardcoded creds, missing auth middleware, token in query params

Database

Database Design & Query Efficiency

DB-

SQL injection, N+1 queries, connection pooling, transactions

Caching

Caching Strategy & Data Freshness

CACHE-

Unbounded caches, missing TTL, no HTTP cache headers

Configuration Management

Configuration & Secrets Management

CFG-

Hardcoded secrets, missing env vars, config validation

Backwards Compatibility

Backwards Compatibility & Versioning

COMPAT-

API versioning, breaking changes, response consistency

Portability

Platform Portability & Vendor Independence

PORTA-

OS-specific paths, vendor lock-in, hardcoded hosts

UX

User Experience & Interface Quality

UX-

Loading states, error messages, pagination, destructive actions

Logging Privacy

Logging Privacy & Data Redaction

LOGPRIV-

PII in logs, token logging, structured logging, redaction

Rate Limiting

Rate Limiting & Throttling

RATE-

Missing rate limits, unbounded queries, backoff strategy

CI/CD

CI/CD Pipeline & Deployment Safety

CICD-

Test infrastructure, lint config, Docker tags, build scripts

Code Structure

Structural Analysis

STRUCT-

Cyclomatic complexity, nesting depth, function length, dead code, type safety

Agent Instructions

Agent Instruction Markdown Quality & Safety

AGENT-

Instruction hierarchy, conflict detection, unsafe overrides, scope, validation, policy guidance

AI Code Safety

AI-Generated Code Quality & Security

AICS-

Prompt injection, insecure LLM output handling, debug defaults, missing validation, unsafe deserialization of AI responses

Framework Safety

Framework-Specific Security & Best Practices

FW-

React hooks ordering, Express middleware chains, Next.js SSR/SSG pitfalls, Angular/Vue lifecycle patterns, Django/Flask/FastAPI safety, Spring Boot security, ASP.NET Core auth & CORS, Go Gin/Echo/Fiber patterns

IaC Security

Infrastructure as Code

IAC-

Terraform, Bicep, ARM template misconfigurations, hardcoded secrets, missing encryption, overly permissive network/IAM rules

Security

General Security Posture

SEC-

Holistic security assessment β€” insecure data flows, weak cryptography, unsafe deserialization

Hallucination Detection

AI-Hallucinated API & Import Validation

HALLU-

Detects hallucinated APIs, fabricated imports, and non-existent modules from AI code generators

Intent Alignment

Code–Comment Alignment & Stub Detection

INTENT-

Detects mismatches between stated intent and implementation, placeholder stubs, TODO-only functions

API Contract Conformance

API Design & REST Best Practices

API-

API endpoint input validation, REST conformance, request/response contract consistency

Multi-Turn Coherence

Code Coherence & Consistency

COH-

Self-contradicting patterns, duplicate definitions, dead code, inconsistent naming

Model Fingerprint Detection

AI Code Provenance & Model Attribution

MFPR-

Detects stylistic fingerprints characteristic of specific AI code generators

Over-Engineering

Simplicity & Pragmatism

OVER-

Unnecessary abstractions, wrapper-mania, premature generalization, over-complex patterns

Logic Review

Semantic Correctness & Logic Integrity

LOGIC-

Inverted conditions, dead code, name-body mismatch, off-by-one, incomplete control flow

False-Positive Review

False Positive Detection & Finding Accuracy

FPR-

Meta-judge reviewing pattern-based findings for false positives: string literal context, comment/docstring matches, test scaffolding, IaC template gating


How It Works

The tribunal operates in three layers:

  1. Pattern-Based Analysis β€” All tools (evaluate_code, evaluate_code_single_judge, evaluate_project, evaluate_diff) perform heuristic analysis using regex pattern matching to catch common anti-patterns. This layer is instant, deterministic, and runs entirely offline with zero external API calls.

  2. AST-Based Structural Analysis β€” The Code Structure judge (STRUCT-* rules) uses real Abstract Syntax Tree parsing to measure cyclomatic complexity, nesting depth, function length, parameter count, dead code, and type safety with precision that regex cannot achieve. All supported languages β€” TypeScript, JavaScript, Python, Rust, Go, Java, C#, and C++ β€” are parsed via tree-sitter WASM grammars (real syntax trees compiled to WebAssembly, in-process, zero native dependencies). A scope-tracking structural parser is kept as a fallback when WASM grammars are unavailable. No external AST server required.

  3. LLM-Powered Deep Analysis (Prompts) β€” The server exposes MCP prompts (e.g., judge-data-security, judge-cybersecurity) that provide each judge's expert persona as a system prompt. When used by an LLM-based client (Copilot, Claude, Cursor, etc.), the host LLM performs deeper, context-aware probabilistic analysis beyond what static patterns can detect. This is where the systemPrompt on each judge comes alive β€” Judges itself makes no LLM calls, but it provides the expert criteria so your AI assistant can act as 45 specialized reviewers.


Composable by Design

Judges Panel is a dual-layer review system: instant deterministic tools (offline, no API keys) for pattern and AST analysis, plus 45 expert-persona MCP prompts that unlock LLM-powered deep analysis when connected to an AI client. It does not try to be a CVE scanner or a linter. Those capabilities belong in dedicated MCP servers that an AI agent can orchestrate alongside Judges.

Built-in AST Analysis

Unlike earlier versions that recommended a separate AST MCP server, Judges Panel now includes real AST-based structural analysis out of the box:

  • TypeScript, JavaScript, Python, Rust, Go, Java, C#, C++ β€” All parsed with a unified tree-sitter WASM engine for full syntax-tree analysis (functions, complexity, nesting, dead code, type safety). Falls back to a scope-tracking structural parser when WASM grammars are unavailable

The Code Structure judge (STRUCT-*) uses these parsers to accurately measure:

Rule

Metric

Threshold

STRUCT-001

Cyclomatic complexity

> 10 per function (high)

STRUCT-002

Nesting depth

> 4 levels (medium)

STRUCT-003

Function length

> 50 lines (medium)

STRUCT-004

Parameter count

> 5 parameters (medium)

STRUCT-005

Dead code

Unreachable statements (low)

STRUCT-006

Weak types

any, dynamic, Object, interface{}, unsafe (medium)

STRUCT-007

File complexity

> 40 total cyclomatic complexity (high)

STRUCT-008

Extreme complexity

> 20 per function (critical)

STRUCT-009

Extreme parameters

> 8 parameters (high)

STRUCT-010

Extreme function length

> 150 lines (high)

When your AI coding assistant connects to multiple MCP servers, each one contributes its specialty:

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                   AI Coding Assistant                   β”‚
β”‚              (Claude, Copilot, Cursor, etc.)            β”‚
β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
       β”‚                  β”‚          β”‚
       β–Ό                  β–Ό          β–Ό
  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”  β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”
  β”‚   Judges     β”‚  β”‚  CVE / β”‚  β”‚ Linter β”‚
  β”‚   Panel      β”‚  β”‚  SBOM  β”‚  β”‚ Server β”‚
  β”‚ ─────────────│  β””β”€β”€β”€β”€β”€β”€β”€β”€β”˜  β””β”€β”€β”€β”€β”€β”€β”€β”€β”˜
  β”‚ 44 Heuristic β”‚   Vuln DB     Style &
  β”‚   judges     β”‚   scanning    correctness
  β”‚ + AST judge  β”‚
  β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
   Patterns +
   structural
   analysis

Layer

What It Does

Example Servers

Judges Panel

45-judge quality gate β€” security patterns, AST analysis, cost, scalability, a11y, compliance, sovereignty, ethics, dependency health, agent instruction governance, AI code safety, framework safety

This server

CVE / SBOM

Vulnerability scanning against live databases β€” known CVEs, license risks, supply chain

OSV, Snyk, Trivy, Grype MCP servers

Linting

Language-specific style and correctness rules

ESLint, Ruff, Clippy MCP servers

Runtime Profiling

Memory, CPU, latency measurement on running code

Custom profiling MCP servers

What This Means in Practice

When you ask your AI assistant "Is this code production-ready?", the agent can:

  1. Judges Panel β†’ Scan for hardcoded secrets, missing error handling, N+1 queries, accessibility gaps, compliance issues, plus analyze cyclomatic complexity, detect dead code, and flag deeply nested functions via AST

  2. CVE Server β†’ Check every dependency in package.json against known vulnerabilities

  3. Linter Server β†’ Enforce team style rules, catch language-specific gotchas

Each server returns structured findings. The AI synthesizes everything into a single, actionable review β€” no single server needs to do it all.


MCP Tools

evaluate_v2

Run a V2 context-aware tribunal evaluation designed to raise feedback quality toward lead engineer/architect-level review:

  • Policy profile calibration (default, startup, regulated, healthcare, fintech, public-sector)

  • Context ingestion (architecture notes, constraints, standards, known risks, data-boundary model)

  • Runtime evidence hooks (tests, coverage, latency, error rate, vulnerability counts)

  • Specialty feedback aggregation by judge/domain

  • Confidence scoring and explicit uncertainty reporting

Supports:

  • Code mode: code + language

  • Project mode: files[]

Parameter

Type

Required

Description

code

string

conditional

Source code for single-file mode

language

string

conditional

Programming language for single-file mode

files

array

conditional

{ path, content, language }[] for project mode

context

string

no

High-level review context

includeAstFindings

boolean

no

Include AST/code-structure findings (default: true)

minConfidence

number

no

Minimum finding confidence to include (0-1, default: 0)

policyProfile

enum

no

default, startup, regulated, healthcare, fintech, public-sector

evaluationContext

object

no

Structured architecture/constraint context

evidence

object

no

Runtime/operational evidence for confidence calibration

evaluate_app_builder_flow

Run a 3-step app-builder workflow for technical and non-technical stakeholders:

  1. Tribunal review (code/project/diff)

  2. Plain-language translation of top risks

  3. Prioritized remediation tasks with AI-fixable P0/P1 extraction

Supports:

  • Code mode: code + language

  • Project mode: files[]

  • Diff mode: code + language + changedLines[]

Parameter

Type

Required

Description

code

string

conditional

Full source content (code/diff mode)

language

string

conditional

Programming language (code/diff mode)

files

array

conditional

{ path, content, language }[] for project mode

changedLines

number[]

no

1-based changed lines for diff mode

context

string

no

Optional business/technical context

maxFindings

number

no

Max translated top findings (default: 10)

maxTasks

number

no

Max generated tasks (default: 20)

includeAstFindings

boolean

no

Include AST/code-structure findings (default: true)

minConfidence

number

no

Minimum finding confidence to include (0-1, default: 0)

evaluate_public_repo_report

Clone a public repository URL, run the full judges panel across eligible source files, and generate a consolidated markdown report.

Parameter

Type

Required

Description

repoUrl

string

yes

Public repository URL (https://...)

branch

string

no

Optional branch name

outputPath

string

no

Optional path to write report markdown

maxFiles

number

no

Max files analyzed (default: 600)

maxFileBytes

number

no

Max file size in bytes (default: 300000)

maxFindingsInReport

number

no

Max detailed findings in output (default: 150)

credentialMode

string

no

Credential detection mode: standard (default) or strict

includeAstFindings

boolean

no

Include AST/code-structure findings (default: true)

minConfidence

number

no

Minimum finding confidence to include (0-1, default: 0)

enableMustFixGate

boolean

no

Enable must-fix gate summary for high-confidence dangerous findings (default: false)

mustFixMinConfidence

number

no

Confidence threshold for must-fix gate triggers (0-1, default: 0.85)

mustFixDangerousRulePrefixes

string[]

no

Optional dangerous rule prefixes for gate matching (e.g., AUTH, CYBER, DATA)

keepClone

boolean

no

Keep cloned repo on disk for inspection

Quick examples

Generate a report from CLI:

npm run report:public-repo -- --repoUrl https://github.com/microsoft/vscode --output reports/vscode-judges-report.md

# stricter credential-signal mode (optional)
npm run report:public-repo -- --repoUrl https://github.com/openclaw/openclaw --credentialMode strict --output reports/openclaw-judges-report-strict.md

# judge findings only (exclude AST/code-structure findings)
npm run report:public-repo -- --repoUrl https://github.com/openclaw/openclaw --includeAstFindings false --output reports/openclaw-judges-report-no-ast.md

# show only findings at 80%+ confidence
npm run report:public-repo -- --repoUrl https://github.com/openclaw/openclaw --minConfidence 0.8 --output reports/openclaw-judges-report-high-confidence.md

# include must-fix gate summary in the generated report
npm run report:public-repo -- --repoUrl https://github.com/openclaw/openclaw --enableMustFixGate true --mustFixMinConfidence 0.9 --mustFixDangerousPrefix AUTH --mustFixDangerousPrefix CYBER --output reports/openclaw-judges-report-mustfix.md

# opinionated quick-start mode (recommended first run)
npm run report:quickstart -- --repoUrl https://github.com/openclaw/openclaw --output reports/openclaw-quickstart.md

Call from MCP client:

{
  "tool": "evaluate_public_repo_report",
  "arguments": {
    "repoUrl": "https://github.com/microsoft/vscode",
    "branch": "main",
    "maxFiles": 400,
    "maxFindingsInReport": 120,
    "credentialMode": "strict",
    "includeAstFindings": false,
    "minConfidence": 0.8,
    "enableMustFixGate": true,
    "mustFixMinConfidence": 0.9,
    "mustFixDangerousRulePrefixes": ["AUTH", "CYBER", "DATA"],
    "outputPath": "reports/vscode-judges-report.md"
  }
}

Typical response summary includes:

  • overall verdict and average score

  • analyzed file count and total findings

  • per-judge score table

  • highest-risk findings and lowest-scoring files

Sample report snippet:

# Public Repository Full Judges Report

Generated from https://github.com/microsoft/vscode on 2026-02-21T12:00:00.000Z.

## Executive Summary
- Overall verdict: WARNING
- Average file score: 78/100
- Total findings: 412 (critical 3, high 29, medium 114, low 185, info 81)

get_judges

List all available judges with their domains and descriptions.

evaluate_code

Submit code to the full judges panel. all 45 judges evaluate independently and return a combined verdict.

Parameter

Type

Required

Description

code

string

yes

The source code to evaluate

language

string

yes

Programming language (e.g., typescript, python)

context

string

no

Additional context about the code

includeAstFindings

boolean

no

Include AST/code-structure findings (default: true)

minConfidence

number

no

Minimum finding confidence to include (0-1, default: 0)

config

object

no

Inline configuration (see Configuration)

evaluate_code_single_judge

Submit code to a specific judge for targeted review.

Parameter

Type

Required

Description

code

string

yes

The source code to evaluate

language

string

yes

Programming language

judgeId

string

yes

See judge IDs below

context

string

no

Additional context

minConfidence

number

no

Minimum finding confidence to include (0-1, default: 0)

config

object

no

Inline configuration (see Configuration)

evaluate_project

Submit multiple files for project-level analysis. all 45 judges evaluate each file, plus cross-file architectural analysis detects code duplication, inconsistent error handling, and dependency cycles.

Parameter

Type

Required

Description

files

array

yes

Array of { path, content, language } objects

context

string

no

Optional project context

includeAstFindings

boolean

no

Include AST/code-structure findings (default: true)

minConfidence

number

no

Minimum finding confidence to include (0-1, default: 0)

config

object

no

Inline configuration (see Configuration)

evaluate_diff

Evaluate only the changed lines in a code diff. Runs all 45 judges on the full file but filters findings to lines you specify. Ideal for PR reviews and incremental analysis.

Parameter

Type

Required

Description

code

string

yes

The full file content (post-change)

language

string

yes

Programming language

changedLines

number[]

yes

1-based line numbers that were changed

context

string

no

Optional context about the change

includeAstFindings

boolean

no

Include AST/code-structure findings (default: true)

minConfidence

number

no

Minimum finding confidence to include (0-1, default: 0)

config

object

no

Inline configuration (see Configuration)

analyze_dependencies

Analyze a dependency manifest file for supply-chain risks, version pinning issues, typosquatting indicators, and dependency hygiene. Supports package.json, requirements.txt, Cargo.toml, go.mod, pom.xml, and .csproj files.

Parameter

Type

Required

Description

manifest

string

yes

Contents of the dependency manifest file

manifestType

string

yes

File type: package.json, requirements.txt, etc.

context

string

no

Optional context

evaluate_git_diff

Evaluate only changed lines from a git diff. Provide either repoPath for a live git diff or diffText for a pre-computed unified diff.

Parameter

Type

Required

Description

repoPath

string

conditional

Absolute path to the git repository

base

string

no

Git ref to diff against (default: HEAD~1)

diffText

string

conditional

Pre-computed unified diff text

confidenceFilter

number

no

Minimum confidence threshold for findings (0–1)

autoTune

boolean

no

Apply feedback-driven auto-tuning (default: false)

maxPromptChars

number

no

Max character budget for LLM prompts (default: 100000, 0 = unlimited)

config

object

no

Inline configuration

re_evaluate_with_context

Re-run the tribunal with prior findings as context for iterative refinement. Supports dispute resolution, developer context injection, and focus-area filtering.

Parameter

Type

Required

Description

code

string

yes

Source code to re-evaluate

language

string

yes

Programming language

disputedRuleIds

string[]

no

Rule IDs the developer disputes as false positives

acceptedRuleIds

string[]

no

Rule IDs the developer accepts

developerContext

string

no

Free-form explanation of developer intent

focusAreas

string[]

no

Specific areas to focus on (e.g., ["security"])

confidenceFilter

number

no

Minimum confidence threshold (default: 0.5)

filePath

string

no

File path for context-aware evaluation

deepReview

boolean

no

Include LLM deep-review prompt section

relatedFiles

array

no

Cross-file context { path, snippet, relationship? }[]

maxPromptChars

number

no

Max character budget for LLM prompts (default: 100000, 0 = unlimited)

Additional MCP Tools

Tool

Description

evaluate_file

Read a file from disk and submit it to the full panel. Auto-detects language from extension.

evaluate_code_streaming

Streaming evaluation β€” returns per-judge results as each judge completes with running aggregates.

evaluate_focused

Run only specified judges. Use after an initial full evaluation to re-check specific areas.

evaluate_batch

Evaluate multiple code files in a single call. Returns per-file verdicts plus aggregate statistics.

evaluate_then_fix

Evaluate code and automatically generate fix patches for all findings with auto-fix support.

evaluate_with_progress

Evaluate with progress callbacks for long-running evaluations.

evaluate_policy_aware

Policy-aware evaluation with named profiles (startup, regulated, healthcare, fintech, public-sector).

fix_code

Evaluate code and apply all available auto-fix patches. Returns fixed code with applied/remaining summary.

explain_finding

Explain a finding in plain language with OWASP/CWE references, risk context, and remediation guidance.

triage_finding

Set triage status of a finding (accepted-risk, deferred, wont-fix, false-positive) with attribution.

record_feedback

Record user feedback (true-positive, false-positive, wont-fix) to calibrate confidence scores.

get_finding_stats

Finding lifecycle statistics: open, fixed, recurring, and triaged counts plus trends.

get_suppression_analytics

Analyze suppression patterns: FP rates by rule, suppression rates, auto-suppress candidates.

list_triaged_findings

List triaged findings, optionally filtered by triage status.

benchmark_gate

Run benchmarks against quality thresholds. Returns pass/fail with F1, precision, recall metrics.

run_benchmark

Run the full benchmark suite with per-judge, per-category, per-difficulty breakdowns.

scaffold_judge

Generate boilerplate files to add a new judge: definition, evaluator skeleton, and registration.

scaffold_plugin

Generate a starter plugin template with custom rules, judges, and lifecycle hooks.

session_status

Current evaluation session state: evaluation count, frameworks, verdict history, stability.

list_files

List files and directories in the workspace for project exploration.

read_file

Read file contents from the workspace.

Judge IDs

data-security Β· cybersecurity Β· security Β· cost-effectiveness Β· scalability Β· cloud-readiness Β· software-practices Β· accessibility Β· api-design Β· api-contract Β· reliability Β· observability Β· performance Β· compliance Β· data-sovereignty Β· testing Β· documentation Β· internationalization Β· dependency-health Β· concurrency Β· ethics-bias Β· maintainability Β· error-handling Β· authentication Β· database Β· caching Β· configuration-management Β· backwards-compatibility Β· portability Β· ux Β· logging-privacy Β· rate-limiting Β· ci-cd Β· code-structure Β· agent-instructions Β· ai-code-safety Β· framework-safety Β· iac-security Β· hallucination-detection Β· intent-alignment Β· multi-turn-coherence Β· model-fingerprint Β· over-engineering Β· logic-review Β· false-positive-review


MCP Prompts

Each judge has a corresponding prompt for LLM-powered deep analysis:

Prompt

Description

judge-data-security

Deep data security review

judge-cybersecurity

Deep cybersecurity review

judge-cost-effectiveness

Deep cost optimization review

judge-scalability

Deep scalability review

judge-cloud-readiness

Deep cloud readiness review

judge-software-practices

Deep software practices review

judge-accessibility

Deep accessibility/WCAG review

judge-api-design

Deep API design review

judge-reliability

Deep reliability & resilience review

judge-observability

Deep observability & monitoring review

judge-performance

Deep performance optimization review

judge-compliance

Deep regulatory compliance review

judge-data-sovereignty

Deep data, technological & operational sovereignty review

judge-testing

Deep testing quality review

judge-documentation

Deep documentation quality review

judge-internationalization

Deep i18n review

judge-dependency-health

Deep dependency health review

judge-concurrency

Deep concurrency & async safety review

judge-ethics-bias

Deep ethics & bias review

judge-maintainability

Deep maintainability & tech debt review

judge-error-handling

Deep error handling review

judge-authentication

Deep authentication & authorization review

judge-database

Deep database design & query review

judge-caching

Deep caching strategy review

judge-configuration-management

Deep configuration & secrets review

judge-backwards-compatibility

Deep backwards compatibility review

judge-portability

Deep platform portability review

judge-ux

Deep user experience review

judge-logging-privacy

Deep logging privacy review

judge-rate-limiting

Deep rate limiting review

judge-ci-cd

Deep CI/CD pipeline review

judge-code-structure

Deep AST-based structural analysis review

judge-agent-instructions

Deep review of agent instruction markdown quality and safety

judge-ai-code-safety

Deep review of AI-generated code risks: prompt injection, insecure LLM output handling, debug defaults, missing validation

judge-framework-safety

Deep review of framework-specific safety: React hooks, Express middleware, Next.js SSR/SSG, Angular/Vue, Django, Spring Boot, ASP.NET Core, Flask, FastAPI, Go frameworks

judge-iac-security

Deep review of infrastructure-as-code security: Terraform, Bicep, ARM template misconfigurations

judge-security

Deep holistic security posture review: insecure data flows, weak cryptography, unsafe deserialization

judge-hallucination-detection

Deep review of AI-hallucinated APIs, fabricated imports, non-existent modules

judge-intent-alignment

Deep review of code–comment alignment, stub detection, placeholder functions

judge-api-contract

Deep review of API contract conformance, input validation, REST best practices

judge-multi-turn-coherence

Deep review of code coherence: self-contradictions, duplicate definitions, dead code

judge-model-fingerprint

Deep review of AI code provenance and model attribution fingerprints

judge-over-engineering

Deep review of unnecessary abstractions, wrapper-mania, premature generalization

judge-logic-review

Deep review of logic correctness, semantic mismatches, and dead code in AI-generated code

judge-false-positive-review

Meta-judge review of pattern-based findings for false positive detection and accuracy


Configuration

Create a .judgesrc.json (or .judgesrc) file in your project root to customize evaluation behavior. See .judgesrc.example.json for a copy-paste-ready template, or reference the JSON Schema for full IDE autocompletion.

{
  "$schema": "https://github.com/KevinRabun/judges/blob/main/judgesrc.schema.json",
  "preset": "strict",
  "minSeverity": "medium",
  "disabledRules": ["COST-*", "I18N-001"],
  "disabledJudges": ["accessibility", "ethics-bias"],
  "ruleOverrides": {
    "SEC-003": { "severity": "critical" },
    "DOC-*": { "disabled": true }
  },
  "languages": ["typescript", "python"],
  "format": "text",
  "failOnFindings": false,
  "baseline": "",
  "regulatoryScope": ["GDPR", "PCI-DSS", "SOC2"],
  "consensusThreshold": 0.7
}

Field

Type

Default

Description

$schema

string

β€”

JSON Schema URL for IDE validation

preset

string

β€”

Named preset (see Named Presets for all 22 options)

minSeverity

string

"info"

Minimum severity to report: critical Β· high Β· medium Β· low Β· info

disabledRules

string[]

[]

Rule IDs or prefix wildcards to suppress (e.g. "COST-*", "SEC-003")

disabledJudges

string[]

[]

Judge IDs to skip entirely (e.g. "cost-effectiveness")

ruleOverrides

object

{}

Per-rule overrides keyed by rule ID or wildcard β€” { disabled?: boolean, severity?: string }

languages

string[]

[]

Restrict analysis to specific languages (empty = all)

format

string

"text"

Default output format: text Β· json Β· sarif Β· markdown Β· html Β· pdf Β· junit Β· codeclimate Β· github-actions

failOnFindings

boolean

false

Exit code 1 when verdict is fail β€” useful for CI gates

baseline

string

""

Path to a baseline JSON file β€” matching findings are suppressed

plugins

string[]

[]

Plugin module specifiers (npm packages or relative paths) that export custom judges

judgeWeights

object

{}

Weighted importance per judge for aggregated scoring (e.g. { "cybersecurity": 2.0 })

failOnScoreBelow

number

β€”

Minimum score (0–100) for the run to pass; complements failOnFindings

regulatoryScope

string[]

β€”

Regulatory frameworks in scope (e.g. ["GDPR", "PCI-DSS"]). Findings citing ONLY out-of-scope frameworks are suppressed. Run judges list --frameworks for supported values.

consensusThreshold

number

β€”

Consensus suppression (0–1). If this fraction of judges report zero findings, minority findings are suppressed. Recommended: 0.7 for CI.

escalationThreshold

number

β€”

Confidence threshold (0–1) below which findings are flagged for human review

overrides

array

[]

Path-scoped config overrides (e.g. [{ "files": "**/*.test.ts", "disabledJudges": ["documentation"] }])

customRules

array

[]

User-defined regex-based rules for business logic validation

All evaluation tools (CLI and MCP) accept the same configuration fields via --config <path> or inline config parameter.


Advanced Features

Inline Suppressions

Suppress specific findings directly in source code using comment directives:

const x = eval(input); // judges-ignore SEC-001
// judges-ignore-next-line CYBER-002
const y = dangerousOperation();
// judges-file-ignore DOC-*    ← suppress globally for this file

Supported comment styles: //, #, /* */. Supports comma-separated rule IDs and wildcards (*, SEC-*).

Auto-Fix Patches

Certain findings include machine-applicable patches in the patch field:

Pattern

Auto-Fix

new Buffer(x)

β†’ Buffer.from(x)

http:// URLs (non-localhost)

β†’ https://

Math.random()

β†’ crypto.randomUUID()

Patches include oldText, newText, startLine, and endLine for automated application.

Cross-Evaluator Deduplication

When multiple judges flag the same issue (e.g., both Data Security and Cybersecurity detect SQL injection on line 15), findings are automatically deduplicated. The highest-severity finding wins, and the description is annotated with cross-references (e.g., "Also identified by: CYBER-003").

Human Focus Guide

Every tribunal evaluation includes a humanFocusGuide that categorizes findings into three buckets for human reviewers:

Bucket

Description

When to use

βœ… Trust

High-confidence (β‰₯80%), evidence-backed findings with AST/taint confirmation

Act directly β€” these have strong automated evidence

πŸ” Verify

Lower-confidence or absence-based findings

Use your judgment β€” the issue may exist elsewhere in the project

πŸ”¦ Blind Spots

Areas automated analysis cannot evaluate

Focus your manual review time here

Blind spots are detected from code characteristics: complex branching logic, external service calls, financial calculations, PII handling, state machines, and complex regex. The guide appears in CLI text/markdown output, JSON/SARIF output, and GitHub Action step summaries.

Regulatory Scope

Configure which regulatory frameworks apply to your project in .judgesrc:

{ "regulatoryScope": ["GDPR", "PCI-DSS", "SOC2"] }

Findings that cite ONLY out-of-scope frameworks are suppressed. Findings with no regulatory reference (general code quality) are always kept. Run judges list --frameworks to see all 17 supported frameworks (GDPR, CCPA, HIPAA, PCI-DSS, SOC2, SOX, COPPA, FedRAMP, NIST, ISO27001, ePrivacy, DORA, NIS2, EU-AI-Act, and more).

Self-Teaching Amendments

The LLM benchmark system auto-generates precision amendments for judges with high false-positive rates. Amendments are data-driven corrections injected into prompts that improve accuracy over successive benchmark runs.

The self-teaching loop:

  1. Run benchmark β†’ analyzer identifies judges below 70% precision

  2. Generates targeted amendments (e.g., "Judge ERR: do not flag clean Express code with framework error middleware")

  3. Next benchmark run loads amendments β†’ precision improves

  4. Run judges codify-amendments to bake amendments permanently into the distributed package

Taint Flow Analysis

The engine performs inter-procedural taint tracking to trace data from user-controlled sources (e.g., req.body, process.env) through transformations to security-sensitive sinks (e.g., eval(), exec(), SQL queries). Taint flows are used to boost confidence on true-positive findings and suppress false positives where sanitization is detected.

Positive Signal Detection

Code that demonstrates good practices receives score bonuses (capped at +15):

Signal

Bonus

Parameterized queries

+3

Security headers (helmet)

+3

Auth middleware (passport, etc.)

+3

Proper error handling

+2

Input validation libs (zod, joi, etc.)

+2

Rate limiting

+2

Structured logging (pino, winston)

+2

CORS configuration

+1

Strict mode / strictNullChecks

+1

Test patterns (describe/it/expect)

+1

Framework-Aware Rules

Judges include framework-specific detection for Express, Django, Flask, FastAPI, Spring, ASP.NET, Rails, and more. Framework middleware (e.g., helmet(), express-rate-limit, passport.authenticate()) is recognized as mitigation, reducing false positives.

Cross-File Import Resolution

In project-level analysis, imports are resolved across files. If one file imports a security middleware module from another file in the project, findings about missing security controls are automatically adjusted with reduced confidence.


Scoring

Each judge scores the code from 0 to 100:

Severity

Score Deduction

Critical

βˆ’30 points

High

βˆ’18 points

Medium

βˆ’10 points

Low

βˆ’5 points

Info

βˆ’2 points

Verdict logic:

  • FAIL β€” Any critical finding, or score < 60

  • WARNING β€” Any high finding, any medium finding, or score < 80

  • PASS β€” Score β‰₯ 80 with no critical, high, or medium findings

The overall tribunal score is the average of all 45 judges. The overall verdict fails if any judge fails.


Project Structure

judges/
β”œβ”€β”€ src/
β”‚   β”œβ”€β”€ index.ts              # MCP server entry point β€” tools, prompts, transport
β”‚   β”œβ”€β”€ api.ts                # Programmatic API entry point
β”‚   β”œβ”€β”€ cli.ts                # CLI argument parser and command router
β”‚   β”œβ”€β”€ types.ts              # TypeScript interfaces (Finding, JudgeEvaluation, etc.)
β”‚   β”œβ”€β”€ config.ts             # .judgesrc configuration parser and validation
β”‚   β”œβ”€β”€ errors.ts             # Custom error types (ConfigError, EvaluationError, ParseError)
β”‚   β”œβ”€β”€ language-patterns.ts  # Multi-language regex pattern constants and helpers
β”‚   β”œβ”€β”€ judge-registry.ts     # Unified JudgeRegistry β€” single source of truth for all judges
β”‚   β”œβ”€β”€ plugins.ts            # Plugin API faΓ§ade (delegates to JudgeRegistry)
β”‚   β”œβ”€β”€ scoring.ts            # Confidence scoring and calibration
β”‚   β”œβ”€β”€ dedup.ts              # Finding deduplication engine
β”‚   β”œβ”€β”€ fingerprint.ts        # Finding fingerprint generation
β”‚   β”œβ”€β”€ comparison.ts         # Tool comparison benchmark data
β”‚   β”œβ”€β”€ cache.ts              # Evaluation result caching
β”‚   β”œβ”€β”€ calibration.ts        # Confidence calibration from feedback data
β”‚   β”œβ”€β”€ fix-history.ts        # Auto-fix application history tracking
β”‚   β”œβ”€β”€ ast/                  # AST analysis engine (built-in, no external deps)
β”‚   β”‚   β”œβ”€β”€ index.ts          # analyzeStructure() β€” routes to correct parser
β”‚   β”‚   β”œβ”€β”€ types.ts          # FunctionInfo, CodeStructure interfaces
β”‚   β”‚   β”œβ”€β”€ tree-sitter-ast.ts    # Tree-sitter WASM parser (all 8 languages)
β”‚   β”‚   β”œβ”€β”€ structural-parser.ts  # Fallback scope-tracking parser
β”‚   β”‚   β”œβ”€β”€ cross-file-taint.ts   # Cross-file taint propagation analysis
β”‚   β”‚   └── taint-tracker.ts      # Single-file taint flow tracking
β”‚   β”œβ”€β”€ evaluators/           # Analysis engine for each judge
β”‚   β”‚   β”œβ”€β”€ index.ts          # evaluateWithJudge(), evaluateWithTribunal(), evaluateProject(), etc.
β”‚   β”‚   β”œβ”€β”€ shared.ts         # Scoring, verdict logic, markdown formatters
β”‚   β”‚   └── *.ts              # One analyzer per judge (45 files)
β”‚   β”œβ”€β”€ formatters/           # Output formatters
β”‚   β”‚   β”œβ”€β”€ sarif.ts              # SARIF 2.1.0 output
β”‚   β”‚   β”œβ”€β”€ html.ts               # Self-contained HTML report (dark/light theme, filters)
β”‚   β”‚   β”œβ”€β”€ junit.ts              # JUnit XML output (Jenkins, Azure DevOps, GitHub Actions)
β”‚   β”‚   β”œβ”€β”€ codeclimate.ts        # CodeClimate/GitLab Code Quality JSON
β”‚   β”‚   β”œβ”€β”€ diagnostics.ts        # Diagnostics formatter
β”‚   β”‚   └── badge.ts              # SVG and text badge generator
β”‚   β”œβ”€β”€ commands/             # CLI subcommands
β”‚   β”‚   β”œβ”€β”€ init.ts               # Interactive project setup wizard
β”‚   β”‚   β”œβ”€β”€ fix.ts                # Auto-fix patch preview and application
β”‚   β”‚   β”œβ”€β”€ watch.ts              # Watch mode β€” re-evaluate on save
β”‚   β”‚   β”œβ”€β”€ report.ts             # Project-level local report
β”‚   β”‚   β”œβ”€β”€ hook.ts               # Pre-commit hook install/uninstall
β”‚   β”‚   β”œβ”€β”€ ci-templates.ts       # GitLab, Azure, Bitbucket CI templates
β”‚   β”‚   β”œβ”€β”€ diff.ts               # Evaluate unified diff (git diff)
β”‚   β”‚   β”œβ”€β”€ deps.ts               # Dependency supply-chain analysis
β”‚   β”‚   β”œβ”€β”€ baseline.ts           # Create baseline for finding suppression
β”‚   β”‚   β”œβ”€β”€ completions.ts        # Shell completions (bash/zsh/fish/PowerShell)
β”‚   β”‚   β”œβ”€β”€ docs.ts               # Per-judge rule documentation generator
β”‚   β”‚   β”œβ”€β”€ feedback.ts           # False-positive tracking & finding feedback
β”‚   β”‚   β”œβ”€β”€ benchmark.ts          # Detection accuracy benchmark suite
β”‚   β”‚   β”œβ”€β”€ rule.ts               # Custom rule authoring wizard
β”‚   β”‚   β”œβ”€β”€ language-packs.ts     # Language-specific rule pack presets
β”‚   β”‚   └── config-share.ts       # Shareable team/org configuration
β”‚   β”œβ”€β”€ presets.ts            # Named evaluation presets (strict, lenient, security-only, …)
β”‚   β”œβ”€β”€ patches/
β”‚   β”‚   └── index.ts              # 201 deterministic auto-fix patch rules
β”‚   β”œβ”€β”€ tools/                # MCP tool registrations
β”‚   β”‚   β”œβ”€β”€ register.ts           # Tool registration orchestrator
β”‚   β”‚   β”œβ”€β”€ register-evaluation.ts    # Evaluation tools (evaluate_code, etc.)
β”‚   β”‚   β”œβ”€β”€ register-workflow.ts      # Workflow tools (app builder, reports, etc.)
β”‚   β”‚   β”œβ”€β”€ prompts.ts            # MCP prompt registrations (per-judge prompts)
β”‚   β”‚   └── schemas.ts            # Zod schemas for tool parameters
β”‚   β”œβ”€β”€ reports/
β”‚   β”‚   └── public-repo-report.ts   # Public repo clone + full tribunal report generation
β”‚   └── judges/               # Judge definitions (id, name, domain, system prompt)
β”‚       β”œβ”€β”€ index.ts          # Side-effect imports + re-exports (JUDGES, getJudge, getJudgeSummaries)
β”‚       └── *.ts              # One self-registering definition per judge (45 files)
β”œβ”€β”€ scripts/
β”‚   β”œβ”€β”€ generate-public-repo-report.ts  # Run: npm run report:public-repo -- --repoUrl <url>
β”‚   β”œβ”€β”€ daily-popular-repo-autofix.ts   # Run: npm run automation:daily-popular
β”‚   └── debug-fp.ts                     # Debug false-positive findings
β”œβ”€β”€ examples/
β”‚   β”œβ”€β”€ sample-vulnerable-api.ts  # Intentionally flawed code (triggers all judges)
β”‚   β”œβ”€β”€ demo.ts                   # Run: npm run demo
β”‚   └── quickstart.ts             # Quick-start evaluation example
β”œβ”€β”€ tests/
β”‚   β”œβ”€β”€ judges.test.ts            # Core judge evaluation tests
β”‚   β”œβ”€β”€ negative.test.ts          # Negative / FP-avoidance tests
β”‚   β”œβ”€β”€ subsystems.test.ts        # Subsystem integration tests
β”‚   β”œβ”€β”€ extension-logic.test.ts   # VS Code extension logic tests
β”‚   └── tool-routing.test.ts      # MCP tool routing tests
β”œβ”€β”€ grammars/                 # Tree-sitter WASM grammar files
β”‚   β”œβ”€β”€ tree-sitter-typescript.wasm
β”‚   β”œβ”€β”€ tree-sitter-cpp.wasm
β”‚   β”œβ”€β”€ tree-sitter-python.wasm
β”‚   β”œβ”€β”€ tree-sitter-go.wasm
β”‚   β”œβ”€β”€ tree-sitter-rust.wasm
β”‚   β”œβ”€β”€ tree-sitter-java.wasm
β”‚   └── tree-sitter-c_sharp.wasm
β”œβ”€β”€ judgesrc.schema.json      # JSON Schema for .judgesrc config files
β”œβ”€β”€ server.json               # MCP Registry manifest
β”œβ”€β”€ package.json
β”œβ”€β”€ tsconfig.json
└── README.md

Scripts

Command

Description

npm run build

Compile TypeScript to dist/

npm run dev

Watch mode β€” recompile on save

npm test

Run the full test suite

npm run demo

Run the sample tribunal demo

npm run report:public-repo -- --repoUrl <url>

Generate a full tribunal report for a public repository URL

npm run report:quickstart -- --repoUrl <url>

Run opinionated high-signal report defaults for fast adoption

npm run automation:daily-popular

Analyze up to 10 rotating popular repos/day and open up to 5 remediation PRs per repo

npm start

Start the MCP server

npm run clean

Remove dist/

judges init

Interactive project setup wizard

judges fix <file>

Preview auto-fix patches (add --apply to write)

judges watch <dir>

Watch mode β€” re-evaluate on file save

judges report <dir>

Full tribunal report on a local directory

judges hook install

Install a Git pre-commit hook

judges diff

Evaluate changed lines from unified diff

judges deps

Analyze dependencies for supply-chain risks

judges baseline create

Create baseline for finding suppression

judges ci-templates

Generate CI pipeline templates

judges docs

Generate per-judge rule documentation

judges completions <shell>

Shell completion scripts

judges feedback submit

Mark findings as true positive, false positive, or won't fix

judges feedback stats

Show false-positive rate statistics

judges benchmark run

Run detection accuracy benchmark suite

judges rule create

Interactive custom rule creation wizard

judges rule list

List custom evaluation rules

judges pack list

List available language packs

judges config export

Export config as shareable package

judges config import <src>

Import a shared configuration

judges compare

Compare judges against other code review tools

judges list

List all 45 judges with domains and descriptions

judges list --frameworks

List supported regulatory frameworks and .judgesrc usage

judges codify-amendments

Bake self-teaching amendments into judge source files


This repo includes a scheduled workflow at .github/workflows/daily-popular-repo-autofix.yml that:

  • selects up to 10 repositories per day from a default pool of 100+ popular repos (or a manually supplied target),

  • runs the full Judges evaluation across supported source languages,

  • applies only conservative, single-line remediations that reduce matching finding counts,

  • opens up to 5 PRs per repository with attribution to both Judges and the target repository,

  • skips repositories unless they are public and PR creation is possible with existing GitHub auth (no additional auth flow).

  • enforces hard runtime caps of 10 repositories/day and 5 PRs/repository.

Each run writes daily-autofix-summary.json (or SUMMARY_PATH) with per-repository telemetry, including:

  • runAggregate β€” compact run-level totals and cross-repo top prioritized rules,

  • runAggregate.totalCandidatesDiscovered and runAggregate.totalCandidatesAfterLocationDedupe β€” signal how much overlap was removed before attempting fixes,

  • runAggregate.totalCandidatesAfterPriorityThreshold β€” candidates that remain after applying minimum priority score,

  • runAggregate.dedupeReductionPercent β€” percent reduction from location dedupe for quick runtime-efficiency tracking,

  • runAggregate.priorityThresholdReductionPercent β€” percent reduction from minimum-priority filtering after dedupe,

  • priorityRulePrefixesUsed β€” dangerous rule prefixes used during prioritization,

  • minPriorityScoreUsed β€” minimum candidatePriorityScore applied for candidate inclusion,

  • candidatesDiscovered, candidatesAfterLocationDedupe, and candidatesAfterPriorityThreshold β€” per-repo candidate counts after each filter stage,

  • topPrioritizedRuleCounts β€” most common rule IDs among ranked candidates,

  • topPrioritizedCandidates β€” top ranked candidate samples (rule, severity, confidence, file, line, priority score).

Optional runtime control:

  • AUTOFIX_MIN_PRIORITY_SCORE β€” minimum candidate priority score required after dedupe (default: 0, disabled).

Required secret:

  • JUDGES_AUTOFIX_GH_TOKEN β€” GitHub token with permission to fork/push/create PRs for target repositories.

Manual run:

gh workflow run "Judges Daily Full-Run Autofix PRs" -f targetRepoUrl=https://github.com/owner/repo

Programmatic API

Judges can be consumed as a library (not just via MCP). Import from @kevinrabun/judges/api:

import {
  evaluateCode,
  evaluateProject,
  evaluateCodeSingleJudge,
  getJudge,
  JUDGES,
  findingsToSarif,
} from "@kevinrabun/judges/api";

// Full tribunal evaluation
const verdict = evaluateCode("const x = eval(input);", "typescript");
console.log(verdict.overallScore, verdict.overallVerdict);

// Single judge
const result = evaluateCodeSingleJudge("cybersecurity", code, "typescript");

// SARIF output for CI integration
const sarif = findingsToSarif(verdict.evaluations.flatMap(e => e.findings));

Package Exports

Entry Point

Description

@kevinrabun/judges/api

Programmatic API (default)

@kevinrabun/judges/server

MCP server entry point

@kevinrabun/judges/sarif

SARIF 2.1.0 formatter

@kevinrabun/judges/junit

JUnit XML formatter

@kevinrabun/judges/codeclimate

CodeClimate/GitLab Code Quality JSON

@kevinrabun/judges/badge

SVG and text badge generator

@kevinrabun/judges/diagnostics

Diagnostics formatter

@kevinrabun/judges/plugins

Plugin system API (see Plugin Guide)

@kevinrabun/judges/fingerprint

Finding fingerprint utilities

@kevinrabun/judges/comparison

Tool comparison benchmarks

SARIF Output

Convert findings to SARIF 2.1.0 for GitHub Code Scanning, Azure DevOps, and other CI/CD tools:

import { findingsToSarif, evaluationToSarif, verdictToSarif } from "@kevinrabun/judges/sarif";

const sarif = verdictToSarif(verdict, "src/app.ts");
fs.writeFileSync("results.sarif", JSON.stringify(sarif, null, 2));

Custom Error Types

All thrown errors extend JudgesError with a machine-readable code property:

Error Class

Code

When

ConfigError

JUDGES_CONFIG_INVALID

Malformed .judgesrc or invalid inline config

EvaluationError

JUDGES_EVALUATION_FAILED

Unknown judge, analyzer crash

ParseError

JUDGES_PARSE_FAILED

Unparseable source code or input data

import { ConfigError, EvaluationError } from "@kevinrabun/judges/api";
try {
  evaluateCode(code, "typescript");
} catch (e) {
  if (e instanceof ConfigError) console.error("Config issue:", e.code);
}

License

MIT

A
license - permissive license
-
quality - not tested
-
maintenance - not tested

Maintenance

–Maintainers
–Response time
0dRelease cycle
255Releases (12mo)
Commit activity
Issues opened vs closed

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