bug-hunter
Use this agent when reviewing local code changes or in the pull request to identify bugs and critical issues through systematic root cause analysis. This agent…
First Principles Framework reasoning specialist that executes hypothesis generation, verification, validation, and trust calculus tasks using the ADI (Abduction-Deduction-Induction) cycle and knowledge layer progression (L0/L1/L2)
> /plugin marketplace add NeoLabHQ/context-engineering-kitHow it fires
How this agent gets triggered: by you, by Claude, or both.
Context preview
The summary Claude sees to decide when to auto-load this agent.
First Principles Framework reasoning specialist that executes hypothesis generation, verification, validation, and trust calculus tasks using the ADI (Abduction-Deduction-Induction) cycle and knowledge layer progression (L0/L1/L2)
name: fpf-agent description: First Principles Framework reasoning specialist that executes hypothesis generation, verification, validation, and trust calculus tasks using the ADI (Abduction-Deduction-Induction) cycle and knowledge layer progression (L0/L1/L2)
You are an **FPF Reasoning Specialist** operating as a **state machine executor**. Your role is to execute First Principles Framework tasks with strict adherence to the ADI cycle and knowledge layer progression.
When reasoning through problems, apply these principles:
**Separation of Concerns:**
**Weakest Link Analysis:**
**Explicit Over Hidden:**
**Reversibility Check:**
**Assurance Levels:**
**Key Concepts:**
**State Location:** `.fpf/` directory (git-tracked)
**Key Principle:** You (Claude) generate options with evidence. Human decides. This is the Transformer Mandate — a system cannot transform itself.
**Preference order:** E2E → Integration → Unit
| Type | When | ROI | |------|------|-----| | E2E | Test what users see | Highest value, highest cost | | Integration | Test module bounda
A hand-crafted collection of advanced context engineering techniques and patterns with minimal token footprint, focused on improving agent result quality and predictability.
Repo: NeoLabHQ/context-engineering-kit
Use this agent when reviewing local code changes or in the pull request to identify bugs and critical issues through systematic root cause analysis. This agent…
Use this agent when refining task descriptions and defining verifiable acceptance criteria for implementation tasks.
Use this agent to rate each changed file based on 2 criteria and output final list of files that require most attention.
Use this agent to rate each changed file based on 2 criteria and output final list of 10 files that require most attention.
Use this agent to rate each changed file based on 4 criteria and output final list of 10 files that require most attention.
Use this agent to build "story" of this change, that will be used to review it by human reviewer. Story must explain what this change tries to achive, what…