First Principles Framework (FPF) Plugin
Plugin ActiveFirst Principles Framework (FPF) for structured reasoning using workflow command pattern. Implements ADI (Abduction-Deduction-Induction) cycle via propose-hypotheses workflow with fpf-agent for hypothesis generation, logical verification, empirical validation, and auditable decision-making. Includes utility commands for status, query, decay, actualize, and reset.
To make AI decision-making transparent, auditable, and evidence-based by enforcing a systematic hypothesis-driven reasoning process.
Features
- Implements FPF ADI cycle for structured reasoning
- Generates, verifies, and validates competing hypotheses
- Audits trust scores for evidence-based validation
- Provides commands for managing decision cycles and knowledge
- Creates auditable decision rationale records (DRRs)
Use Cases
- Making critical architectural or technical decisions with an auditable trail
- Preventing premature conclusions by systematically evaluating alternatives
- Building and leveraging project knowledge over time
- Ensuring AI-assisted development processes are transparent and accountable
Non-Goals
- Making unsupervised AI decisions
- Replacing human judgment in the decision-making process
- Providing a general-purpose LLM interaction tool
Workflow
- Initialize FPF context with problem statement
- Generate competing hypotheses (Abduction)
- Allow user to add hypotheses
- Verify logic of each hypothesis (Deduction)
- Validate evidence for logically sound hypotheses (Induction)
- Audit trust scores for validated hypotheses
- Present decision comparison and select winner
- Record decision rationale (DRR) and present summary
Practices
- Structured Reasoning
- Knowledge Management
- Auditability
Practical Utility
- warning:Production readinessThe plugin's core functionality, especially its reliance on a large FPF specification (~600k tokens) loaded into a sub-agent with a Sonnet[1m] model, may quickly consume token limits and could hinder practical use in real workflows without careful management.
Installation
First, add the marketplace
/plugin marketplace add NeoLabHQ/context-engineering-kit/plugin install fpf@context-engineering-kitContains 6 extensions
Skill (6)
Reconcile the project's FPF state with recent repository changes
Manage evidence freshness by identifying stale decisions and providing governance actions
Execute complete FPF cycle from hypothesis generation to decision
Search the FPF knowledge base and display hypothesis details with assurance information
Reset the FPF reasoning cycle to start fresh
Display the current state of the FPF knowledge base
Quality Score
Trust Signals
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