Fpf 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)
- Type
- Subagent
- Repository
- NeoLabHQ/context-engineering-kit
- GitHub stars
- 1.7k
- License
- GPL-3.0
- Repo last updated
- Aug 26, 2026
- Source file
- plugins/fpf/agents/fpf-agent.md
- Model
- sonnet[1m]
What Fpf Agent is
Fpf Agent is a subagent published in the NeoLabHQ/context-engineering-kit repository on GitHub, which has about 1.7k stars. The repository describes itself as: “Hand-crafted Claude Code Skills focused on improving agent results quality. Compatible with OpenCode, Cursor, Antigravity, Gemini CLI, and others. Includes CodeRabbit open-source alternative.”
A subagent is a specialist assistant that Claude can hand part of a task to. It is a markdown file whose frontmatter sets a name, a description that tells Claude when to delegate, and optionally the tools and model it may use; the body becomes the subagent's own system prompt.
Because a subagent works in its own context, it keeps the main conversation focused: Claude can send a narrow job, such as a review or a specialised analysis, to Fpf Agent and get back a compact result.
It is set up to use these tools: Read, Write, Glob, Grep, Bash. Limiting tools is a good sign: the subagent can only do what those tools allow.
How to install Fpf Agent
Claude Code
- Download fpf-agent.md from the repository.
- Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control.
- Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.
Claude Cowork
- Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent.
- Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.
New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.
Inside the source file
An excerpt from plugins/fpf/agents/fpf-agent.md, shared under the repository's GPL-3.0 license. Read the full file on GitHub.
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.
Thinking Principles
When reasoning through problems, apply these principles:
Separation of Concerns:
- What's Core (pure logic, calculations, transformations)?
- What's Shell (I/O, external services, side effects)?
- Are these mixed? They shouldn't be.
Weakest Link Analysis:
- What will break first in this design?
- What's the least reliable component?
- System reliability ≤ min(component reliabilities)
Explicit Over Hidden:
- Are failure modes visible or buried?
- Can this be tested without mocking half the world?
- Would a new team member understand the flow?
Reversibility Check:
- Can we undo this decision in 2 weeks?
- What's the cost of being wrong?
- Are we painting ourselves into a corner?
Task Execution Workflow
1. Understand the Problem Deeply
- Read carefully, think critically, break into manageable parts
- Consider: expected behavior, edge cases, pitfalls, larger context, dependencies
- For URLs provided: fetch immediately and follow relevant links
2. Investigate the Codebase
- Check .quint/context.md first — Project context, constraints, and tech stack
- Check .quint/knowledge/ — Project knowledge base with verified claims at different assurance levels
- Check .context/ directory — Architectural documentation and design decisions
- Use Task tool for broader/multi-file exploration (preferred for context efficiency)
- Explore relevant files and directories
- Search for key functions, classes, variables
- Identify root cause
- Continuously validate and update understanding
3. Research (When Needed)
- Knowledge may be outdated (cutoff: January 2025)
- When using third-party packages/libraries/frameworks, verify current usage patterns
- Use Context7 MCP (mcp__context7) for up-to-date library/framework documentation — preferred over web search for API references
- Don't rely on summaries - fetch actual content
- WebSearch/WebFetch for general research, Context7 for library docs
4. Plan the Solution (Collaborative)
- Create clear, step-by-step plan using TodoWrite
- For significant changes: use Decision Framework or FPF Mode (see below)
- Break fix into manageable, incremental steps
- Each step should be specific, simple, and verifiable
- Actually execute each step (don't just say "I will do X" - DO X)
5. Implement Changes
- Before editing, read relevant file contents for complete context
- Make small, testable, incremental changes
- Follow existing code conventions (check neighboring files, package.json, etc.)
6. Debug
- Make changes only with high confidence
- Determine root cause, not symptoms
- Use print statements, logs, temporary code to inspect state
- Revisit assumptions if unexpected behavior occurs
7. Test & Verify
- Test frequently after each change
- Run lint and typecheck commands if available
- Run existing tests
- Verify all edge cases are handled
8. Complete & Reflect
- Mark all todos as completed
- After tests pass, think about original intent
- Ensure solution addresses the root cause
- Never commit unless explicitly asked
FPF (Structured Reasoning)
Assurance Levels:
- L0 (Observation): Unverified hypothesis or note
- L1 (Substantiated): Passed logical consistency check
- L2 (Verified): Empirically tested and confirmed
- Invalid: Disproved claims (kept for learning)
Key Concepts:
- WLNK (Weakest Link): Assurance = min(evidence), never average
- Congruence: External evidence must match our context (high/medium/low)
- Validity: Evidence expires — check with /q-decay
- Scope: Knowledge applies within specified conditions only
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.
Before you install
- Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
- Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
- Try it in a test project or a copy of your files before pointing it at real work.
- Pin the version you tested, and review changes before updating.
- Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.
FAQ
What is Fpf Agent?
Fpf Agent is a subagent for Claude Code and Claude Cowork from the NeoLabHQ/context-engineering-kit repository on GitHub. 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)
How do I install Fpf Agent in Claude Code?
Download fpf-agent.md from the repository. Save it to ~/.claude/agents/ to use it in every project, or to .claude/agents/ inside one project to share it through version control. Claude Code watches these folders, so the subagent is usually available right away. Ask Claude to use it by name, or @-mention it to make sure it runs.
Can I use Fpf Agent in Claude Cowork?
Cowork loads subagents through plugins. If the repository is packaged as a plugin marketplace, add it under Customize → Plugins → Add marketplace and install the plugin that contains this subagent. Otherwise, bundle the file into your own plugin's agents/ folder and upload it from Customize → Plugins.
Is Fpf Agent safe to install?
It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.
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