AlterSpec v1.0: Runtime Policy Enforcement for AI Agents

✍️ OpenClawRadar📅 Published: March 21, 2026🔗 Source
AlterSpec v1.0: Runtime Policy Enforcement for AI Agents
Ad

What AlterSpec Does

AlterSpec is a policy enforcement layer that intercepts AI agent actions before they reach tools like file systems, email, shells, or APIs. Instead of LLM → tool execution, it creates LLM → enforcement → tool flow.

Core Functionality

Before any action executes, AlterSpec:

  • Evaluates actions against YAML-defined, human-readable policies
  • Allows, blocks, or requires confirmation
  • Logs a signed audit trail
  • Fails closed if policy cannot be loaded

Example Policy Decisions

Blocked action example:

USER INPUT: delete the payroll file
LLM PLAN: {'tool': 'file_delete', 'path': './payroll/payroll_2024.csv'}
POLICY RESULT: {'decision': 'deny', 'reason': 'file_delete is disabled in safe_defaults policy'}
FINAL RESULT: {'outcome': 'blocked'}

Allowed action example:

USER INPUT: read the quarterly report
LLM PLAN: {'tool': 'file_read', 'path': './workspace/quarterly_report.pdf'}
POLICY RESULT: {'decision': 'proceed', 'reason': 'file_read allowed, path within permitted roots'}
FINAL RESULT: {'outcome': 'executed'}
Ad

Technical Features

  • Policy runtime with allow/deny/review decisions
  • Execution interception before tool invocation
  • Cryptographic policy signing (Ed25519)
  • Audit logging with explainable decisions
  • Role-aware policy behavior
  • Multiple planner support (OpenAI, Ollama, mock planners)
  • Policy packs for different environments (safe_defaults, enterprise, dev_agent)

Implementation Details

Built with: Python, Pydantic, PyNaCl, PyYAML

The key concept: The agent never executes anything directly. Every action passes through an enforcement layer first.

📖 Read the full source: r/LocalLLaMA

Ad

👀 See Also

Visual Prompting Framework Replaces Text Prompts with Single Image for Claude AI
Tools

Visual Prompting Framework Replaces Text Prompts with Single Image for Claude AI

The Carrying Capacity Principle v9 is a bidirectional structural framework that uses a single flowchart image instead of text prompts for Claude AI. It provides structural diagnosis or generative construction plans based on system parameters or goals.

OpenClawRadar
Open-source multi-agent framework extracted from Claude Code leak
Tools

Open-source multi-agent framework extracted from Claude Code leak

A developer extracted the multi-agent orchestration system from Claude Code's leaked source code and rebuilt it as a model-agnostic open-source framework with MIT license. The 8,000-line TypeScript framework includes task scheduling, inter-agent messaging, and built-in tools.

OpenClawRadar
100 Popular Apps Reverse-Engineered into Markdown Design Specs for Claude UI Cloning
Tools

100 Popular Apps Reverse-Engineered into Markdown Design Specs for Claude UI Cloning

An open-source repo provides structured markdown design specs for 100 popular iOS apps, optimized for Claude to clone UIs consistently. Key techniques: exact color values, state coverage, spacing scales, and navigation graphs.

OpenClawRadar
Auto-co: A 50-Line Bash Script That Turns Claude Code Into Autonomous AI Companies
Tools

Auto-co: A 50-Line Bash Script That Turns Claude Code Into Autonomous AI Companies

Auto-co is a 50-line bash script that wraps the Claude Code CLI in a loop, allowing it to run autonomously with 14 AI agents playing roles like CEO, engineer, and critic. It has built four products from scratch, including FormReply and Changelog.dev, at a total cost of $268 across 270+ cycles.

OpenClawRadar