agentic-ai-prompt-research
Research into agentic AI coding assistants focusing on prompt patterns and security
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Decision brief
agentic-ai-prompt-research explores functionality and security aspects of agentic AI in coding assistance. This research includes reconstructed prompts for secure coordination.
Good fit when
- If you are specifically interested in the working mechanisms of agentic AI with a focus on Claude, it is suited for your needs.
- Consider using this tool if your project emphasizes security classification within prompt patterns.
Avoid when
- Avoid if your primary interest lies in generic AI agent behavior without emphasis on secure coordination methods.
- Not suitable for those whose research does not center around specific prompts and their reconstruction techniques.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
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- Not a fork · Personal account
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git clone https://github.com/Leonxlnx/agentic-ai-prompt-researchSimilar tools
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Evidence and technical details
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Overview
Investigates workings of agentic AI in code assistance with emphasis on reconstructed prompts and secure coordination methods.
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README
Claude Code System Prompts
A research project exploring how modern agentic AI coding assistants work under the hood. This repository contains our best understanding of the prompt architecture, agent coordination patterns, and security mechanisms that power tools like Claude Code.
Everything here is based on behavioral observation, output analysis, community discussions, and publicly shared information. These are reconstructed approximations, not verbatim copies. The actual implementation may differ significantly.
What This Project Is
This is an educational deep-dive into the design patterns behind agentic coding assistants. We analyze how these systems:
- Assemble dynamic system prompts at runtime
- Coordinate multiple specialized sub-agents
- Classify and auto-approve tool calls safely
- Manage context windows through intelligent compaction
- Handle memory, skills, and user preferences
The goal is to help AI engineers, researchers, and builders learn from these architectural patterns and apply them in their own projects.
What This Project Is Not
This is not a leak, dump, or direct copy of any proprietary system. The prompts documented here are our best reconstructions based on observable behavior. They represent one interpretation of how these systems likely work.
Documented Patterns
Core Identity
| # | Pattern | Description |
|---|---|---|
| 01 | Main System Prompt | How the master prompt is dynamically assembled from modular sections |
| 02 | Simple Mode | Minimal prompt variant for lightweight operation |
| 03 | Default Agent Prompt | Base instructions inherited by all sub-agents |
| 04 | Cyber Risk Instruction | Security boundaries between authorized and prohibited actions |
Orchestration
| # | Pattern | Description |
|---|---|---|
| 05 | Coordinator System Prompt | Multi-worker orchestration with phased workflows |
| 06 | Teammate Prompt Addendum | Communication protocols for multi-agent collaboration |
Specialized Agents
| # | Pattern | Description |
|---|---|---|
| 07 | Verification Agent | Adversarial testing agent that validates implementations |
| 08 | Explore Agent | Read-only codebase exploration with no-modify constraints |
| 09 | Agent Creation Architect | Generates new agent configurations from requirements |
| 10 | Status Line Setup Agent | Terminal status line configuration across shells |
Security and Permissions
| # | Pattern | Description |
|---|---|---|
| 11 | Permission Explainer | Risk assessment before tool approval |
| 12 | Auto Mode Classifier | Multi-stage security classifier for autonomous tool execution |
Tool Descriptions
| # | Pattern | Description |
|---|---|---|
| 13 | Tool-Specific Prompts | How individual tools (Bash, Edit, Agent, etc.) describe themselves |
Utility Patterns
| # | Pattern | Description |
|---|---|---|
| 14 | Tool Use Summary | Generating concise labels for completed tool batches |
| 15 | Session Search | Semantic search across past conversation sessions |
| 16 | Memory Selection | Selecting relevant memory files for query context |
| 17 | Auto Mode Critique | Reviewing user-written classifier rules |
| 20 | Session Title | Lightweight title generation for session management |
| 2 |
For agents
This page has a .md twin and JSON over the API.