Agent Rigor – Stop your AI coding assistant from doom-looping

Strict empirical discipline for your AI coding assistant.

Stop watching your AI agent code itself into a corner. Give it discipline.

Most AI coding agents fail not because they lack intelligence, but because they lack discipline. When left to their own devices, they:

• ❌ Skip planning and jump straight to implementation.
• ❌ Write plausible-looking code that doesn't actually work.
• ❌ Get trapped in "doom loops" (fix-forward spirals).
• ❌ Forget what they learned between sessions (context amnesia).
• ❌ Suffer from "context rot" by too many instructions at once.

Agent Rigor solves this. It provides a structured, multi-layer progressive disclosure framework: a set of mandatory protocols, verification gates, and anti-rationalization safeguards that force empirical discipline at every step.

Actionable Protocols: Every instruction is a verifiable step with exit criteria, not an essay.** Empirical Sovereignty**: Claims require evidence. "Seems right" is never sufficient.** Atomic State Transitions**: The codebase moves between known-good states. Broken states are never committed.** Anti-Rationalization**: Every skill actively anticipates and rebuts the excuses agents use to skip discipline.** Progressive Disclosure**: The agent reads only the files it needs for the current phase, saving tokens and preventing instruction neglect.

The system is organized into a robust 3-tier hierarchy using Progressive Disclosure to prevent context window collapse.

L1: Apex Kernel (: Always-on routing and non-negotiable laws.SYSTEM_CORE.md

)L2: Phase Directors (: Just-in-time orchestration loaded only when entering a phase.00_PHASE_DIRECTOR.md

)L3: Skill Protocols (: Deep execution guidelines loadedskills/*.md

)onlywhen requested by the Director.

graph TD
    A[Phase 1: Mission Synthesis] -->|PLAN.md| B(Phase 2: Execution Engine)
    B -->|Committed Code| C{Phase 3: Verification Matrix}
    C -->|CRITICAL Findings| B
    C -->|Zero Findings| D[Phase 4: Cognitive Persistence]
    D -->|Context Snapshot| A
    
    subgraph Phase 6: Adaptive Protocols
    Z[Self-Correction / Scope Defense / Consolidation]
    end
    
    B -.->|3-Strike Failure| Z
    Z -.->|Recovery| B

1. Mission Synthesis | Requirements & Planning | Requirement Distillation, Strategic Decomposition |
2. Execution Engine | Implementation & Testing | Convergent Iteration, State Checkpointing |
3. Verification Matrix | Quality & Review Gates | Pentagonal Audit, Entropy Reduction |
4. Cognitive Persistence | Memory & Knowledge | Context Lifecycle, Structural Cartography |
5. Interface Protocols | Safe Environment Interaction | Bounded Observation, Semantic Navigation |
6. Adaptive Protocols | The Immune System | Recursive Self-Correction, Scope Containment |

Get Agent Rigor working in your project in under 2 minutes.

Run the installation script in your project root:

curl -sSL https://raw.githubusercontent.com/MeherBhaskar/agent-rigor/main/install.sh | bash

(Alternatively, clone this repo into an .agents/ directory).

Simply prompt your agent with:

"I need to build [feature]. Read

.agents/SYSTEM_CORE.md

and begin Phase 1 (Mission Synthesis)."

The agent will automatically read the Phase 1 Director, create a PLAN.md

, and orchestrate its own work through implementation, review, and context saving.

Agent Rigor is pure markdown and platform-agnostic. It works natively with:

*See the *

examples/

folder for ready-to-use configuration templates.We welcome contributions to make agents smarter and more disciplined! Please see our Contributing Guidelines to understand how to design skills that agents actually follow.