About sim-xia/blind-auditor
sim-xia/blind-auditor is an MCP server published by Sim-xia in the Developer Tools category: mCP tool for improving model coding quality by mandatory self-audition.
The repository has 11 stars and 2 forks, with the last commit 10 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/Sim-xia/Blind-AuditorThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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- !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
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README
🛡️ Blind Auditor - MCP Server
"Code -> audit -> amend -> audit again -> pass."
Blind Auditor is a mandatory code auditing system built on the MCP (Model Context Protocol). It uses a unique "Thinking Isolation" mechanism to force AI Agents to enter an independent "audit phase" and self-review their code before outputting the final result.
🧠 Core Philosophy: Thinking Isolation
Traditional AI coding is often "generate and output," which allows errors and biases to slip through. Blind Auditor introduces a middle layer:
- Intercept: When the Agent wants to output code, it must first submit it to Blind Auditor.
- Isolate: Blind Auditor does not return the result immediately. Instead, it injects a mandatory system instruction, forcing the Agent to pause its current persona and switch to a "Ruthless Auditor" role.
- Audit: In this isolated context, the Agent must scan the generated code line by line against the predefined
rules.json. - Release: The code is unlocked and returned to the user only when the audit score meets the threshold (default > 80) and there are no Critical issues.
🎯 Key Features
- 🛡️ Zero Trust Architecture: Default distrust of the Agent's initial draft; it must pass an audit.
- 💰 Zero Extra Cost: Reuses the host IDE's current session model, requiring no additional API Key.
- ⚖️ Bias Removal: Forces a perspective switch via Prompt injection to break generation inertia.
- 📏 Strict Compliance: Hard-codes team code standards (
rules.json) into the generation process, which is more effective than simple Prompts. - 🔄 Auto-Fix Loop: Automatically triggers a "fix-resubmit" loop upon audit failure until compliance is met or the maximum retry count is reached.
🚀 Quick Start
1. Prerequisites
This project requires Python 3.10+ and uv.
# Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Enter project directory
cd blind-auditor
# Install dependencies (automatically creates virtual environment)
uv sync
2. Configure Audit Rules (rules.json)
Create or edit rules.json in the project root. This is the auditor's "Rulebook".
{
"project_name": "MyCoreProject",
"strict_mode": true,
"max_retries": 3,
"rules": [
{
"id": "SEC-001",
"severity": "CRITICAL",
"description": "Strictly prohibit hardcoding any API Keys, passwords, or sensitive Tokens.",
"weight": 50
},
{
"id": "PERF-001",
"severity": "WARNING",
"description": "Avoid database queries or IO operations inside loops.",
"weight": 15
},
{
"id": "STYLE-001",
"severity": "PREFERENCE",
"description": "Use snake_case for variable names.",
"weight": 5
}
]
}
Configuration Fields:
severity:CRITICAL: Fatal error. If found, the audit fails immediately. Usually carries a high penalty.WARNING: Warning. Moderate penalty; accumulation can lead to failure.PREFERENCE: Style preference. Low penalty.
weight: The penalty points deducted when this rule is violated (Total score: 100).
3. Configure IDE (Antigravity / Cursor / Windsurf)
Step A: Add System Prompt (Critical)
To ensure the Agent knows it must use this tool, add the following instruction to your .cursorrules or IDE System Prompt settings:
# Blind Auditor Protocol
**CRITICAL INSTRUCTION**:
You are integrated with the **Blind Auditor MCP**.
Whenever you generate code for a user request, you **MUST NOT** output the code block directly to the user.
**Execution Protocol**:
1. **Draft**: Generate the code internally in your thought process.
2. **Submit**: Call the `submit_draft` tool with your code and language.
3. **Obey**: The tool will return a strict "Audit Instruction". You MUST follow it exactly to audit your own code.
4. **Finalize**: Only when the tool returns "✅ AUDIT PASSED" can you display the final code to the user.
**Prohibited**:
- Do NOT output code blocks before passing the audit.
- Do NOT skip the audit step for "simple" changes.
Step B: Configure MCP Server
Add the following to your MCP client configuration file (e.g., claude_desktop_config.json or IDE settings):
Note: Replace /path/to/your/blind-auditor with the actual absolute path where you cloned this repository.
{
"mcpServers": {
"blind-auditor": {
"command": "uv",
"args": ["run", "--directory", "/path/to/your/blind-auditor", "blind-auditor"]
}
}
}
🔧 Tool Details
1. submit_draft
Submit a code draft.
- Input:
code(content),language(programming language) - Behavior: Locks the session and returns mandatory audit instructions.
2. submit_audit_result
Submit your audit conclusion.
- Input:
passed(bool): Whether you believe it passed.issues(list): List of issues found.score(int): Score from 0-100.
- Behavior:
- If
score < 80, forcespassed=False. - If passed, unlocks the code.
- If failed, increments retry count and requires the Agent to fix and resubmit.
- If
3. reset_session
Resets the state and clears the retry count.
🔁 Workflow Diagram
graph TD
User["User Request"] --> Agent
Agent["Agent Generates Draft"] -->|1. submit_draft| MCP
MCP -->|2. Inject Audit Instructions| Agent
subgraph Isolation ["Thinking Isolation"]
Agent -->|3. Self-Review| Agent
Agent -->|4. submit_audit_result| MCP
end
MCP -->|5. Verdict| Decision{"Passed?"}
Decision -->|No - Issues Found| Retry["Retry Count +1"]
Retry -->|Limit Not Reached| Fix["Agent Fixes Code"]
Fix -->|Resubmit| Agent
Decision -->|Yes - Score >= 80| Final["✅ Output Final Code"]
Retry -->|Limit Reached| Force["⚠️ Force Output - With Warning"]
❓ Troubleshooting
Q: The Agent always outputs code directly without calling tools. A: Check if the System Prompt is configured correctly. You must explicitly tell the Agent "Do NOT output code directly". You can also manually remind it in the chat: "Please audit via Blind Auditor first".
Q: Why does it fail even if I give the code 100 points?
A: Check if any CRITICAL rules in rules.json were triggered. Current logic mainly relies on the score passed by the Agent, but if passed is True while score < 80, the system will force a rejection.
Q: Which programming languages are supported?
A: Theoretically, all languages are supported. Blind Auditor itself does not parse code syntax but relies on the Agent's understanding to match descriptions in rules.json.
🛠️ Development Guide
# Run server
uv run blind-auditor
# Or run directly with Python module
uv run python -m src.main
# Debug mode (output to stderr)
# View print statements in src/main.py
📄 License
MIT License
README fetched from the repository 1 hours ago. The original is authoritative.