TL;DR |
Professor Synapse ๐ง๐พโโ๏ธ 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.
Professor Synapse ๐ง๐พโโ๏ธ 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.
The classic approach โ 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:
Prompt.md and copy the contentsA more powerful version designed for Claude Desktop, installed as a .zip you upload in Settings. This skill grows over time โ it creates and saves expert agents for reuse, learns patterns from interactions, and maintains its own knowledge base. It includes a Claude-specific packaging workflow and versioned codeload updates.
Folder: professor-synapse-claude/ (distributed as professor-synapse-claude.zip)
The same self-building skill, but stripped of the Claude-only packaging machinery so you can drop it straight into any assistant's skills directory โ .claude/skills/, .codex/skills/, or wherever your tooling reads skills from. It's edited in place: new agents and memory writes take effect immediately, with nothing to repackage or reinstall. It even updates itself in place โ ask it to check for updates and it pulls the latest release over its own files, keeping your memory and customizations.
Folder: professor-synapse-skill/ (copy the folder into your skills directory)
Both skill flavors share these features:
Download professor-synapse-claude.zip from this repo
Add to Claude:
professor-synapse-claude.zipStart using it:
๐ก Grab the latest tagged release from the Releases page for a known-good version.
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 โ 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.
professor-synapse-claude/ # (professor-synapse-skill/ is the same tree minus the โฆ files)
โโโ SKILL.md # Identity, workflow + Global Learned Patterns
โโโ agents/
โ โโโ INDEX.md # Auto-generated registry
โ โโโ domain-researcher.md # Base research agent
โ โโโ memory-agent.md # ๐ง Memory Keeper
โโโ memory/
โ โโโ memory.json # Working memory (profile + active items)
โ โโโ longterm.db # SQLite long-term store + change log
โโโ references/
โ โโโ agent-template.md # Structure for new agents
โ โโโ summon-agent-protocol.md # How to "become" an agent
โ โโโ convener-protocol.md # Multi-agent debate facilitation
โ โโโ memory-protocol.md # How recall/capture/cleanup work
โ โโโ memory-data-model.md # Memory schema + ranked-fusion search
โ โโโ domain-expertise.md # Domain mappings
โ โโโ scripts-protocol.md # Standards for agent scripts
โ โโโ self-check.md # PASS/FAIL install verification
โ โโโ changelog.md # Version history (per-flavor โ they diverge)
โ โโโ update-protocol.md # โ Both flavors, differ: Claude repackages; portable applies in place
โ โโโ file-operations.md # โฆ Claude-only: save/update files + packaging
โ โโโ rebuild-protocol.md # โฆ Claude-only: local change rebuild workflow
โโโ scripts/
โโโ memory.py # Shared agent-tagged memory CLI
โโโ summon.py # Assemble an agent boot package
โโโ test_memory.py # Memory test suite (stdlib unittest)
โโโ test_summon.py # Summon test suite
โโโ rebuild-index.sh # Regenerate INDEX.md
โโโ update.sh # โ Both flavors, differ: Claude prepares a package; portable applies in place
โฆ = Claude flavor only. The portable
professor-synapse-skill/flavor omits these files and the SKILL.md packaging section, since it's edited in place and needs no packaging or rebuild-to-persist step. โ = present in both, but different. Both flavors self-update from GitHub (update-protocol.md+update.sh); the Claude flavor prepares a package the user installs via "Copy to your skills," while the portable flavor writes the merged update straight over its own files in place.
For the best experience, create a dedicated Claude project for working with Professor Synapse:
Begin the conversation with "๐ง๐ฟโโ๏ธ: [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:
For Codex, or any assistant that loads skills from a folder:
professor-synapse-skill/ folder into your assistant's skills directory โ e.g. .claude/skills/, .codex/skills/, or wherever your tooling reads skills from. (Rename it to professor-synapse/ if your tool keys skills by folder name.)Everything is edited in place: agents you create and memory the skill captures take effect immediately โ there's nothing to repackage or reinstall.
Updating: just ask Professor Synapse to "check for updates" (or "update yourself"). It compares its Version: against the latest release, downloads the canonical repo as a codeload tarball, merges it, and writes the new files straight over its own folder โ preserving your memory/ store, custom agents, and learned patterns. You don't download or move anything; running the update is the update. See references/update-protocol.md for the mechanics.
agents/INDEX.md for a matching specialistagents/ for future reusescripts/memory.py)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 ๐ง 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 โ 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 โ 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 โ critically โ 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.
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:
Professor Synapse uses a structured approach to help you achieve your goals:
Feel free to explore, customize, and innovate with Professor Synapse! Please leave a โญ if you found this helpful.
Support the project: ๐ Donate
For more goodies:
197 followers ยท starred Nov 2023
215 followers ยท starred Oct 2023
35 followers ยท starred Jan 2024
59 followers ยท starred Sep 2023
TL;DR |
Professor Synapse ๐ง๐พโโ๏ธ 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.
Professor Synapse ๐ง๐พโโ๏ธ 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.
The classic approach โ 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:
Prompt.md and copy the contentsA more powerful version designed for Claude Desktop, installed as a .zip you upload in Settings. This skill grows over time โ it creates and saves expert agents for reuse, learns patterns from interactions, and maintains its own knowledge base. It includes a Claude-specific packaging workflow and versioned codeload updates.
Folder: professor-synapse-claude/ (distributed as professor-synapse-claude.zip)
The same self-building skill, but stripped of the Claude-only packaging machinery so you can drop it straight into any assistant's skills directory โ .claude/skills/, .codex/skills/, or wherever your tooling reads skills from. It's edited in place: new agents and memory writes take effect immediately, with nothing to repackage or reinstall. It even updates itself in place โ ask it to check for updates and it pulls the latest release over its own files, keeping your memory and customizations.
Folder: professor-synapse-skill/ (copy the folder into your skills directory)
Both skill flavors share these features:
Download professor-synapse-claude.zip from this repo
Add to Claude:
professor-synapse-claude.zipStart using it:
๐ก Grab the latest tagged release from the Releases page for a known-good version.
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 โ 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.
professor-synapse-claude/ # (professor-synapse-skill/ is the same tree minus the โฆ files)
โโโ SKILL.md # Identity, workflow + Global Learned Patterns
โโโ agents/
โ โโโ INDEX.md # Auto-generated registry
โ โโโ domain-researcher.md # Base research agent
โ โโโ memory-agent.md # ๐ง Memory Keeper
โโโ memory/
โ โโโ memory.json # Working memory (profile + active items)
โ โโโ longterm.db # SQLite long-term store + change log
โโโ references/
โ โโโ agent-template.md # Structure for new agents
โ โโโ summon-agent-protocol.md # How to "become" an agent
โ โโโ convener-protocol.md # Multi-agent debate facilitation
โ โโโ memory-protocol.md # How recall/capture/cleanup work
โ โโโ memory-data-model.md # Memory schema + ranked-fusion search
โ โโโ domain-expertise.md # Domain mappings
โ โโโ scripts-protocol.md # Standards for agent scripts
โ โโโ self-check.md # PASS/FAIL install verification
โ โโโ changelog.md # Version history (per-flavor โ they diverge)
โ โโโ update-protocol.md # โ Both flavors, differ: Claude repackages; portable applies in place
โ โโโ file-operations.md # โฆ Claude-only: save/update files + packaging
โ โโโ rebuild-protocol.md # โฆ Claude-only: local change rebuild workflow
โโโ scripts/
โโโ memory.py # Shared agent-tagged memory CLI
โโโ summon.py # Assemble an agent boot package
โโโ test_memory.py # Memory test suite (stdlib unittest)
โโโ test_summon.py # Summon test suite
โโโ rebuild-index.sh # Regenerate INDEX.md
โโโ update.sh # โ Both flavors, differ: Claude prepares a package; portable applies in place
โฆ = Claude flavor only. The portable
professor-synapse-skill/flavor omits these files and the SKILL.md packaging section, since it's edited in place and needs no packaging or rebuild-to-persist step. โ = present in both, but different. Both flavors self-update from GitHub (update-protocol.md+update.sh); the Claude flavor prepares a package the user installs via "Copy to your skills," while the portable flavor writes the merged update straight over its own files in place.
For the best experience, create a dedicated Claude project for working with Professor Synapse:
Begin the conversation with "๐ง๐ฟโโ๏ธ: [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:
For Codex, or any assistant that loads skills from a folder:
professor-synapse-skill/ folder into your assistant's skills directory โ e.g. .claude/skills/, .codex/skills/, or wherever your tooling reads skills from. (Rename it to professor-synapse/ if your tool keys skills by folder name.)Everything is edited in place: agents you create and memory the skill captures take effect immediately โ there's nothing to repackage or reinstall.
Updating: just ask Professor Synapse to "check for updates" (or "update yourself"). It compares its Version: against the latest release, downloads the canonical repo as a codeload tarball, merges it, and writes the new files straight over its own folder โ preserving your memory/ store, custom agents, and learned patterns. You don't download or move anything; running the update is the update. See references/update-protocol.md for the mechanics.
agents/INDEX.md for a matching specialistagents/ for future reusescripts/memory.py)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 ๐ง 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 โ 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 โ 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 โ critically โ 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.
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:
Professor Synapse uses a structured approach to help you achieve your goals:
Feel free to explore, customize, and innovate with Professor Synapse! Please leave a โญ if you found this helpful.
Support the project: ๐ Donate
For more goodies:
197 followers ยท starred Nov 2023
215 followers ยท starred Oct 2023
35 followers ยท starred Jan 2024
59 followers ยท starred Sep 2023