Professor Synapse 🧙🏾‍♂️

TL;DR |

Professor Synapse 🧙🏾‍♂️ is a wise AI guide that helps users achieve their goals by summoning expert agents perfectly suited to their tasks. It gathers context, aligns with user preferences, and creates specialized agents using a structured template to provide targeted expertise and step-by-step guidance.

Introduction

Professor Synapse 🧙🏾‍♂️ is a wise AI guide that helps users achieve their goals by summoning expert agents perfectly suited to their specific tasks. It gathers context about your goals, then creates and orchestrates specialized agents using a structured template to provide targeted expertise and actionable guidance.

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Two Ways to Use Professor Synapse

1. Universal Prompt (Any AI)

The classic approach — copy and paste the prompt into any AI chat interface.

File: Prompt.md

Works with: ChatGPT, Claude, Gemini, or any LLM that accepts system prompts.

Setup:

1. Open Prompt.md and copy the contents
2. Paste into your AI's system prompt or custom instructions
3. Start chatting!

2. Claude Skill (Self-Building)

A more powerful version designed for Claude. This skill grows over time — it creates and saves expert agents for reuse, learns patterns from interactions, and maintains its own knowledge base.

Folder: professor-synapse/

Features:

• 🔎 Domain Researcher agent that browses the web before creating new experts
• 📚 Self-building agent library — created agents are saved for future sessions
• 🧠 Persistent memory — a shared, agent-tagged store that remembers across sessions, with ranked-fusion recall (see below)
• 💡 Pattern learning — captures what works and what doesn't (Global Learned Patterns in SKILL.md + per-agent patterns)
• 📋 Auto-generated index — agents are automatically catalogued
• 🎭 Multi-agent debates — convene multiple specialists for complex decisions
• 🔄 Versioned updates — pull tagged releases from GitHub (codeload tarball) without losing your agents or memory
• 🔧 Skill rebuilding — easy rebuild workflow for local changes

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Claude Skill Setup

Install

1. Download professor-synapse.zip from this repo

2. Add to Claude:

   • Open Claude → Settings → Capabilities → Skills
   • Click Add new skill
   • Upload professor-synapse.zip

3. Start using it:

   • Professor Synapse activates when you say things like:
     • "Help me with..."
     • "I need guidance on..."
     • "I need an expert for..."

💡 Grab the latest tagged release from the Releases page for a known-good version.

Updating

Just ask Professor Synapse to "check for updates." It compares its Version: against the latest release tag, downloads the canonical repo as a codeload tarball, and merges the update in — preserving your custom agents, learned patterns, and memory/ store. It then rebuilds the skill and hands you the new package to install via "Copy to your skills." See references/update-protocol.md for the full mechanics.

Skill Structure

professor-synapse/
├── SKILL.md                      # Identity, workflow + Global Learned Patterns
├── agents/
│   ├── INDEX.md                  # Auto-generated registry
│   ├── domain-researcher.md      # Base research agent
│   └── memory-agent.md           # 🧠 Memory Keeper
├── memory/
│   ├── memory.json               # Working memory (profile + active items)
│   └── longterm.db               # SQLite long-term store + change log
├── references/
│   ├── agent-template.md         # Structure for new agents
│   ├── summon-agent-protocol.md  # How to "become" an agent
│   ├── convener-protocol.md      # Multi-agent debate facilitation
│   ├── memory-protocol.md        # How recall/capture/cleanup work
│   ├── memory-data-model.md      # Memory schema + ranked-fusion search
│   ├── domain-expertise.md       # Domain mappings
│   ├── file-operations.md        # How to save/update files
│   ├── scripts-protocol.md       # Standards for agent scripts
│   ├── update-protocol.md        # Versioned update workflow (codeload)
│   ├── rebuild-protocol.md       # Local change rebuild workflow
│   └── changelog.md              # Version history
└── scripts/
    ├── memory.py                 # Shared agent-tagged memory CLI
    ├── test_memory.py            # Memory test suite (stdlib unittest)
    ├── rebuild-index.sh          # Regenerate INDEX.md
    └── update.sh                 # Fetch latest release + build merged update tree

Recommended: Claude Project Setup

For the best experience, create a dedicated Claude project for working with Professor Synapse:

1. Create a new project in Claude Desktop
2. Add these project instructions:

Begin the conversation with "🧙🏿‍♂️: [acknowledgment of user request]. Conjuring my professor-synapse skill to assist you."

Then follow these instructions:
1. FIRST: Use the `view` tool to check /mnt/skills/user/ for the skill
2. Read the SKILL.md file for that skill

Why this helps:

• Automatically loads the skill at conversation start
• Reads the latest SKILL.md (including any updates)
• Ensures Professor Synapse has full context from your customizations

How the Skill Works

1. You ask for help → Professor Synapse greets you and gathers context
2. Assesses complexity → Determines if this needs one agent or multiple perspectives
3. Path A: Single Agent (most cases)
   • Checks agents/INDEX.md for a matching specialist
   • If match found → Loads and summons that agent
   • If no match → Summons 🔎 Domain Researcher to research the domain, then creates a new expert agent
4. Path B: Convener Mode (complex decisions)
   • Identifies multiple relevant perspectives
   • Hosts a structured debate among specialist agents
   • Synthesizes insights and presents options with trade-offs
5. Saves new agents → New agents are stored in agents/ for future reuse
6. Remembers → Recalls relevant context at the start of work and captures new facts/decisions afterward, each tagged with the acting agent (via scripts/memory.py)
7. Learns patterns → Cross-cutting insights go in SKILL.md's Global Learned Patterns; domain-specific ones go in each agent's own Learned Patterns section

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Features

Core Capabilities

• Expert Agent Summoning: Creates specialized agents tailored to your specific task and domain using a structured template.
• Contextual Understanding: Gathers detailed information about user goals and preferences through targeted questions.
• Orchestrated Conversations: Maintains clear communication between Professor Synapse and summoned agents using a defined conversation pattern.
• Wise Guidance: Provides critical yet respectful challenges to help users think deeply about their goals.
• Intellectual Humility: Admits uncertainty and asks clarifying questions rather than assuming.

Advanced Features

• Multi-Agent Debates (Convener Protocol): When facing complex decisions with trade-offs, Professor Synapse can convene multiple expert agents to debate from different perspectives, then synthesize their insights into actionable recommendations.

• Persistent Agent-Tagged Memory: A shared store (scripts/memory.py) that remembers across sessions. Every item is tagged with the agent that created it, so memory can be recalled broadly or filtered by agent. A working-memory layer (memory.json) holds the live profile and active items; a SQLite long-term store (longterm.db) holds archived decisions, notes, and facts plus a change log. The 🧠 Memory Keeper agent and the rest of the skill lean on it for recall and capture.

• Ranked-Fusion Recall: recall --query retrieves with SQLite FTS5 (stemming, prefix, column-weighted BM25 — hits in people/tags outrank free text) and re-ranks by fusing relevance, recency, and record kind via Reciprocal Rank Fusion. A brief verb gives a one-shot start-of-session prefetch. No external dependencies, no embeddings — it stays fast and portable.

• Versioned Updates: Each release is tagged; the skill carries a Version: marker and detects newer releases via releases/latest. The scripts/update.sh helper downloads the canonical repo as a single codeload source tarball, then merges it in while preserving your custom agents, learned patterns, and — critically — your memory/ store, flagging only the files that need a hand-merge.

• Skill Rebuilding: Easy workflow for rebuilding the skill after adding agents, scripts, or making any local changes. Uses skill-creator to package updates.

• Pattern Learning: Cross-cutting insights live in SKILL.md's Global Learned Patterns; domain-specific ones live in each agent's own Learned Patterns section. The index rebuild script ensures every agent has the section.

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ChatGPT GPT

You can use the official Professor Synapse GPT by clicking HERE

If you'd like to edit and use Professor Synapse as your own GPT, follow these steps:

1. Open ChatGPT: Ensure you have access to OpenAI's ChatGPT.
2. Create a GPT: Go to the GPT Editor and paste the prompt into your instructions.
3. Edit: Feel free to edit the prompt, but focus on the personality, name, persona if you're new to prompting.
4. Start Interacting: Begin a new chat and tell Professor Synapse what you want to accomplish.

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Interaction Flow

Professor Synapse uses a structured approach to help you achieve your goals:

1. Introduction: Greets you warmly and asks what you want to accomplish
2. Context Gathering: Asks targeted questions to understand your goals and preferences
3. Agent Summoning: Creates or loads an expert agent suited to your task
4. Orchestrated Conversation: Delegates to the expert while providing guidance
5. Learning: Captures patterns and insights for future interactions

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Contributions and Support

Feel free to explore, customize, and innovate with Professor Synapse! Please leave a ⭐ if you found this helpful.

Support the project: 💖 Donate

For more goodies:

• 🕸 Website
• 📺 Youtube
• 📖 Substack