synapse
Multi-AI Agent Orchestration System with configurable models and role-based workflows. Use when you need to coordinate multiple AI agents (Claude, Gemini, Codex) for complex tasks like planning, code generation, analysis, review, and execution. Supports agentic workflow patterns: parallel specialists, pipeline, and swarm orchestration. Compatible with Claude Code, Cursor, and OpenCode. Triggers: 'orchestrate agents', 'multi-agent workflow', 'plan and execute', 'code review pipeline', 'run synapse', 'agentic workflow'.
Best use case
synapse is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Multi-AI Agent Orchestration System with configurable models and role-based workflows. Use when you need to coordinate multiple AI agents (Claude, Gemini, Codex) for complex tasks like planning, code generation, analysis, review, and execution. Supports agentic workflow patterns: parallel specialists, pipeline, and swarm orchestration. Compatible with Claude Code, Cursor, and OpenCode. Triggers: 'orchestrate agents', 'multi-agent workflow', 'plan and execute', 'code review pipeline', 'run synapse', 'agentic workflow'.
Teams using synapse should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/synapse/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How synapse Compares
| Feature / Agent | synapse | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Multi-AI Agent Orchestration System with configurable models and role-based workflows. Use when you need to coordinate multiple AI agents (Claude, Gemini, Codex) for complex tasks like planning, code generation, analysis, review, and execution. Supports agentic workflow patterns: parallel specialists, pipeline, and swarm orchestration. Compatible with Claude Code, Cursor, and OpenCode. Triggers: 'orchestrate agents', 'multi-agent workflow', 'plan and execute', 'code review pipeline', 'run synapse', 'agentic workflow'.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
Cursor vs Codex for AI Workflows
Compare Cursor and Codex for AI coding workflows, repository assistance, debugging, refactoring, and reusable developer skills.
SKILL.md Source
# Synapse AI Agent Orchestration Skill
Synapse is a distributed AI agent system that orchestrates three specialized services with configurable models and role-based workflows.
## Agent Roles
| Agent | Role | Capabilities | Default Model |
|-------|------|--------------|---------------|
| **Claude** | Orchestrator/Planner | Task planning, architecture design, code generation | claude-sonnet-4.5 |
| **Gemini** | Analyst/Reviewer | Large context analysis (>1M tokens), code review, security audits | gemini-3-pro-preview |
| **Codex** | Executor | Command execution, build processes, automated testing | gpt-5.2 |
## When to Apply
Use this skill when:
- Breaking down complex tasks into actionable multi-step plans
- Generating implementation code from descriptions or specifications
- Analyzing large codebases or content (especially >200k tokens via Gemini)
- Getting comprehensive code reviews with quality scoring
- Running sandboxed shell commands for builds, tests, or automation
- Executing full plan-analyze-code-review-execute workflows
- Orchestrating parallel or pipeline-based multi-agent workflows
**Do NOT use when:**
- Simple questions that don't require code generation
- Tasks that only need local file operations
- When Docker/Synapse services are not available
## Prerequisites
**Docker must be running with Synapse services active.**
```bash
# Clone Synapse (if not already)
git clone https://github.com/akillness/Synapse.git ~/Synapse
cd ~/Synapse
# Start services
docker compose up -d
# Verify all services are healthy
curl -s http://localhost:8000/health
# Expected: {"status": "healthy", "service": "gateway"}
```
## Installation
### Global Installation (Recommended)
```bash
# Clone synapse-skill
git clone https://github.com/akillness/synapse-skill.git
# For OpenCode
ln -s $(pwd)/synapse-skill ~/.config/opencode/skills/synapse
# For Claude Code / Other Agents
mkdir -p ~/.agents/skills
ln -s $(pwd)/synapse-skill ~/.agents/skills/synapse
```
### Environment Variables (Optional)
```bash
# Custom Synapse location
export SYNAPSE_HOME="$HOME/Synapse"
# Gateway URL (default: http://localhost:8000)
export SYNAPSE_GATEWAY_URL="http://localhost:8000"
```
### For Cursor IDE
Create `.cursor/rules/synapse.mdc` in your project:
```markdown
---
description: Synapse AI Agent Orchestration
globs: ["**/*"]
alwaysApply: true
---
# Synapse Skill Integration
When orchestrating multi-agent tasks, use Synapse endpoints:
- Plan: POST http://localhost:8000/api/v1/claude/plan
- Code: POST http://localhost:8000/api/v1/claude/code
- Analyze: POST http://localhost:8000/api/v1/gemini/analyze
- Review: POST http://localhost:8000/api/v1/gemini/review
- Execute: POST http://localhost:8000/api/v1/codex/execute
Use @planner for task breakdown, @reviewer for code review.
```
### For Claude Code (CLAUDE.md)
Add to your `~/.claude/CLAUDE.md`:
```markdown
## Synapse Integration
For multi-agent orchestration, use Synapse skill:
- Health check: curl http://localhost:8000/health
- Ensure Docker containers are running: docker ps | grep synaps
- Use /api/v1/workflow for full pipeline execution
```
### For OpenCode (oh-my-opencode.json)
Add Synapse-optimized agent configuration to `~/.config/opencode/oh-my-opencode.json`:
```json
{
"$schema": "https://raw.githubusercontent.com/code-yeongyu/oh-my-opencode/master/assets/oh-my-opencode.schema.json",
"agents": {
"synapse-planner": {
"model": "google/antigravity-claude-sonnet-4-5"
},
"synapse-analyst": {
"model": "google/antigravity-gemini-3-pro-high"
},
"synapse-coder": {
"model": "google/antigravity-claude-sonnet-4-5-thinking"
},
"synapse-reviewer": {
"model": "google/antigravity-gemini-3-pro-high"
},
"synapse-executor": {
"model": "openai/gpt-5.2-codex-high"
}
}
}
```
### OpenCode Model Provider Configuration
Add to `~/.config/opencode/opencode.json` for custom Synapse models:
```json
{
"provider": {
"synapse": {
"name": "Synapse Local",
"api": "openai",
"options": {
"baseURL": "http://localhost:8000/api/v1/"
},
"models": {
"claude-planner": {
"name": "Claude Planner (Synapse)",
"limit": { "context": 200000, "output": 64000 }
},
"gemini-analyst": {
"name": "Gemini Analyst (Synapse)",
"limit": { "context": 1000000, "output": 65536 }
},
"codex-executor": {
"name": "Codex Executor (Synapse)",
"limit": { "context": 272000, "output": 128000 }
}
}
}
}
}
```
### OpenCode Skill Integration
The skill is automatically loaded when symlinked to `~/.config/opencode/skills/synapse`.
**Trigger phrases for OpenCode:**
- "orchestrate agents" → Activates Synapse workflow
- "multi-agent workflow" → Starts parallel or pipeline execution
- "run synapse" → Executes full workflow
---
## Model Configuration
### Claude Service Models (2026)
| Model | API ID | Best For | Context | Cost (Input/Output) |
|-------|--------|----------|---------|---------------------|
| `claude-opus-4.5` | `claude-opus-4-5-20251101` | Complex reasoning, production code, sophisticated agents | 200K | $5/$25 per M |
| `claude-sonnet-4.5` | `claude-sonnet-4-5-20250929` | Task planning, code generation, architecture (Recommended) | 1M | $3/$15 per M |
| `claude-haiku-4.5` | `claude-haiku-4-5-20251201` | Fast responses, simple tasks, 90% of Sonnet performance | 200K | $0.80/$4 per M |
**Claude 4.5 Highlights:**
- **Opus 4.5**: State-of-the-art coding (80%+ SWE-bench), best for agents and computer use
- **Sonnet 4.5**: 1M token context window (5x increase), extended thinking mode
- **Haiku 4.5**: Cost-effective with 90% of Sonnet's performance
### Gemini Service Models (2026)
| Model | Best For | Context | Cost |
|-------|----------|---------|------|
| `gemini-3-pro-preview` | Complex reasoning, coding, agentic tasks (76.2% SWE-bench) | 1M | $2-4/M |
| `gemini-3-flash` | Sub-second latency, speed-critical, distilled from 3 Pro | 1M | Lower |
| `gemini-2.5-pro` | Large context analysis, code review, mature stability | 1M | $1.25/M |
| `gemini-2.5-flash` | Cost-efficient, high-volume ($0.15/M input) | 1M | $0.15/M |
**Gemini 3 Highlights:**
- 35% better at software engineering tasks vs 2.5 Pro
- "Vibe coding" support for rapid prototyping
- Knowledge cutoff: January 2025
### Codex Service Models
| Model | Best For | Context | Cost |
|-------|----------|---------|------|
| `gpt-5.2` | Software engineering, agentic workflows | 400K | $1.25/$10 |
| `gpt-5.2-mini` | Cost-efficient coding (4x more usage) | 400K | $0.25/$2 |
| `gpt-5.1-thinking` | Ultra-complex reasoning | 400K | Higher |
---
## Agentic Workflow Patterns
### Pattern 1: Parallel Specialists
Multiple specialists review code simultaneously:
```
┌─────────────────────────────────────────────────────┐
│ ORCHESTRATOR │
│ (You / Claude) │
└────────────┬───────────┬───────────┬────────────────┘
│ │ │
┌───────▼───┐ ┌─────▼─────┐ ┌───▼───────┐
│ Security │ │Performance│ │ Simplicity│
│ Reviewer │ │ Reviewer │ │ Reviewer │
│ (Gemini) │ │ (Gemini) │ │ (Gemini) │
└───────────┘ └───────────┘ └───────────┘
```
**Workflow:**
```bash
# 1. Spawn parallel reviews
curl -X POST http://localhost:8000/api/v1/gemini/review \
-d '{"code": "<code>", "language": "python", "review_type": "security"}'
curl -X POST http://localhost:8000/api/v1/gemini/review \
-d '{"code": "<code>", "language": "python", "review_type": "performance"}'
curl -X POST http://localhost:8000/api/v1/gemini/review \
-d '{"code": "<code>", "language": "python", "review_type": "simplicity"}'
# 2. Aggregate results and synthesize
```
### Pattern 2: Pipeline (Sequential Dependencies)
Each stage depends on the previous:
```
┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐
│ Research │───▶│ Plan │───▶│Implement │───▶│ Test │───▶│ Review │
│ (Gemini) │ │ (Claude) │ │ (Claude) │ │ (Codex) │ │ (Gemini) │
└──────────┘ └──────────┘ └──────────┘ └──────────┘ └──────────┘
```
**Workflow:**
```bash
# Step 1: Research (Gemini analyzes requirements)
RESEARCH=$(curl -X POST http://localhost:8000/api/v1/gemini/analyze \
-d '{"content": "<requirements>", "analysis_type": "documentation"}')
# Step 2: Plan (Claude creates implementation plan)
PLAN=$(curl -X POST http://localhost:8000/api/v1/claude/plan \
-d "{\"task\": \"Implement based on: $RESEARCH\", \"constraints\": [\"python\", \"tests\"]}")
# Step 3: Implement (Claude generates code)
CODE=$(curl -X POST http://localhost:8000/api/v1/claude/code \
-d "{\"description\": \"$PLAN\", \"language\": \"python\"}")
# Step 4: Test (Codex executes tests)
TEST=$(curl -X POST http://localhost:8000/api/v1/codex/execute \
-d '{"command": "python -m pytest tests/", "timeout": 60}')
# Step 5: Review (Gemini reviews final code)
REVIEW=$(curl -X POST http://localhost:8000/api/v1/gemini/review \
-d "{\"code\": \"$CODE\", \"language\": \"python\"}")
```
### Pattern 3: Swarm (Self-Organizing)
Workers grab available tasks from a pool:
```
┌─────────────┐
│ Task Pool │
│ ┌─┬─┬─┬─┬─┐ │
│ │1│2│3│4│5│ │
│ └─┴─┴─┴─┴─┘ │
└──────┬──────┘
┌───────────────┼───────────────┐
│ │ │
┌─────▼─────┐ ┌─────▼─────┐ ┌─────▼─────┐
│ Worker 1 │ │ Worker 2 │ │ Worker 3 │
│ (Claude) │ │ (Gemini) │ │ (Codex) │
│ claims #1 │ │ claims #2 │ │ claims #3 │
└───────────┘ └───────────┘ └───────────┘
```
**Workflow:**
```bash
# Create task pool via workflow endpoint
curl -X POST http://localhost:8000/api/v1/workflow \
-d '{
"task": "Review all files in src/",
"mode": "swarm",
"workers": 3,
"constraints": ["parallel", "auto-assign"]
}'
```
### Pattern 4: Full Workflow (End-to-End)
Use the workflow endpoint for automatic orchestration:
```bash
curl -X POST http://localhost:8000/api/v1/workflow \
-H "Content-Type: application/json" \
-d '{
"task": "Build a user authentication module",
"constraints": ["FastAPI", "JWT", "PostgreSQL"],
"workflow_type": "pipeline",
"model_config": {
"planner": "claude-sonnet-4",
"analyst": "gemini-2.5-pro",
"coder": "claude-sonnet-4",
"executor": "gpt-5.2"
}
}'
```
---
## Role-Based Model Assignment
### Configuration Schema
```json
{
"roles": {
"planner": {
"service": "claude",
"model": "claude-sonnet-4.5",
"description": "Creates task plans and architecture designs"
},
"analyst": {
"service": "gemini",
"model": "gemini-3-pro-preview",
"description": "Analyzes content and performs code reviews"
},
"coder": {
"service": "claude",
"model": "claude-sonnet-4.5",
"description": "Generates implementation code"
},
"reviewer": {
"service": "gemini",
"model": "gemini-3-pro-preview",
"description": "Performs comprehensive code reviews"
},
"executor": {
"service": "codex",
"model": "gpt-5.2",
"description": "Executes commands and runs tests"
}
}
}
```
### Role Selection by Task Type
| Task Type | Primary Role | Model | Endpoint |
|-----------|--------------|-------|----------|
| Task breakdown | Planner | claude-sonnet-4 | `/api/v1/claude/plan` |
| Code generation | Coder | claude-sonnet-4 | `/api/v1/claude/code` |
| Large context analysis | Analyst | gemini-2.5-pro | `/api/v1/gemini/analyze` |
| Security review | Reviewer | gemini-3-pro-preview | `/api/v1/gemini/review` |
| Build & test | Executor | gpt-5.2 | `/api/v1/codex/execute` |
---
## API Reference
### Base URL
```
http://localhost:8000
```
### Endpoints Summary
| Service | Method | Endpoint | Purpose |
|---------|--------|----------|---------|
| System | GET | `/health` | Gateway health check |
| System | GET | `/metrics` | Pool and load balancer stats |
| Claude | GET | `/api/v1/claude/health` | Service health |
| Claude | POST | `/api/v1/claude/plan` | Create task plan |
| Claude | POST | `/api/v1/claude/code` | Generate code |
| Gemini | GET | `/api/v1/gemini/health` | Service health |
| Gemini | POST | `/api/v1/gemini/analyze` | Analyze content |
| Gemini | POST | `/api/v1/gemini/review` | Review code |
| Codex | GET | `/api/v1/codex/health` | Service health |
| Codex | POST | `/api/v1/codex/execute` | Execute command |
| Workflow | POST | `/api/v1/workflow` | Full pipeline |
---
## Quick Reference
| Use Case | Service | Endpoint | Key Fields |
|----------|---------|----------|------------|
| Break down task | Claude | `/api/v1/claude/plan` | `task`, `constraints`, `model` |
| Generate code | Claude | `/api/v1/claude/code` | `description`, `language`, `model` |
| Analyze codebase | Gemini | `/api/v1/gemini/analyze` | `content`, `analysis_type`, `model` |
| Code review | Gemini | `/api/v1/gemini/review` | `code`, `language`, `review_type`, `model` |
| Run command | Codex | `/api/v1/codex/execute` | `command`, `timeout`, `model` |
| Full pipeline | Workflow | `/api/v1/workflow` | `task`, `constraints`, `workflow_type`, `model_config` |
---
## Running Tasks
### 1. Health Check (Always Start Here)
```bash
# Check all services
curl -s http://localhost:8000/api/v1/claude/health
curl -s http://localhost:8000/api/v1/gemini/health
curl -s http://localhost:8000/api/v1/codex/health
```
Expected response:
```json
{"status": "SERVING", "version": "1.0.0", "uptime_seconds": 123}
```
### 2. Create a Plan (Claude)
```bash
curl -X POST http://localhost:8000/api/v1/claude/plan \
-H "Content-Type: application/json" \
-d '{
"task": "Build a REST API with authentication",
"constraints": ["use FastAPI", "JWT tokens", "PostgreSQL"],
"model": "claude-sonnet-4"
}'
```
### 3. Generate Code (Claude)
```bash
curl -X POST http://localhost:8000/api/v1/claude/code \
-H "Content-Type: application/json" \
-d '{
"description": "A function to validate email addresses using regex",
"language": "python",
"model": "claude-sonnet-4"
}'
```
### 4. Analyze Content (Gemini)
```bash
curl -X POST http://localhost:8000/api/v1/gemini/analyze \
-H "Content-Type: application/json" \
-d '{
"content": "<large_codebase_content>",
"analysis_type": "code",
"model": "gemini-2.5-pro"
}'
```
### 5. Review Code (Gemini)
```bash
curl -X POST http://localhost:8000/api/v1/gemini/review \
-H "Content-Type: application/json" \
-d '{
"code": "def add(a, b):\n return a + b",
"language": "python",
"review_type": "comprehensive",
"model": "gemini-3-pro-preview"
}'
```
### 6. Execute Command (Codex)
```bash
curl -X POST http://localhost:8000/api/v1/codex/execute \
-H "Content-Type: application/json" \
-d '{
"command": "python -m pytest tests/",
"working_dir": "/tmp",
"timeout": 60,
"model": "gpt-5.2"
}'
```
**Allowed Commands:** `echo`, `ls`, `pwd`, `date`, `cat`, `head`, `tail`, `wc`, `grep`, `find`, `python`, `pip`, `npm`, `node`, `git`, `make`
---
## Common Workflows
### Code Development Workflow
```bash
# 1. Create plan
curl -X POST http://localhost:8000/api/v1/claude/plan \
-H "Content-Type: application/json" \
-d '{"task": "Implement user authentication", "model": "claude-sonnet-4"}'
# 2. Generate code
curl -X POST http://localhost:8000/api/v1/claude/code \
-H "Content-Type: application/json" \
-d '{"description": "JWT authentication middleware", "language": "python"}'
# 3. Review code
curl -X POST http://localhost:8000/api/v1/gemini/review \
-H "Content-Type: application/json" \
-d '{"code": "<generated_code>", "language": "python", "model": "gemini-3-pro-preview"}'
# 4. Run tests
curl -X POST http://localhost:8000/api/v1/codex/execute \
-H "Content-Type: application/json" \
-d '{"command": "python -m pytest tests/", "timeout": 60}'
```
### Code Analysis Workflow
```bash
# 1. Read file content
FILE_CONTENT=$(cat myfile.py | jq -Rs .)
# 2. Analyze with large context model
curl -X POST http://localhost:8000/api/v1/gemini/analyze \
-H "Content-Type: application/json" \
-d "{\"content\": $FILE_CONTENT, \"analysis_type\": \"code\", \"model\": \"gemini-2.5-pro\"}"
# 3. Review with detailed model
curl -X POST http://localhost:8000/api/v1/gemini/review \
-H "Content-Type: application/json" \
-d "{\"code\": $FILE_CONTENT, \"language\": \"python\", \"model\": \"gemini-3-pro-preview\"}"
```
---
## Error Handling
### Service Unavailable (503)
```json
{"detail": "Service not ready"}
```
**Solution:** Check if Docker containers are running:
```bash
docker ps | grep synaps
```
### Connection Refused
**Solution:** Start Synapse services:
```bash
cd ~/Synapse # or $SYNAPSE_HOME
docker compose up -d
```
### Command Not Allowed (Codex)
```json
{"success": false, "stderr": "Command not allowed"}
```
**Solution:** Use only allowed commands (echo, ls, pwd, python, etc.)
---
## Troubleshooting
### Check Service Status
```bash
# All containers running?
docker ps --format "table {{.Names}}\t{{.Status}}" | grep synaps
# Gateway health
curl -s http://localhost:8000/health
# Individual service health
curl -s http://localhost:8000/api/v1/claude/health
curl -s http://localhost:8000/api/v1/gemini/health
curl -s http://localhost:8000/api/v1/codex/health
```
### Restart Services
```bash
cd ~/Synapse # or $SYNAPSE_HOME
docker compose down
docker compose up -d
```
### View Logs
```bash
docker logs synaps-gateway
docker logs synaps-claude
docker logs synaps-gemini
docker logs synaps-codex
```
---
## Service Ports
| Service | Port | Protocol |
|---------|------|----------|
| Gateway | 8000 | HTTP/REST |
| Claude | 5011 | gRPC |
| Gemini | 5012 | gRPC |
| Codex | 5013 | gRPC |
| Prometheus | 9090 | HTTP |
| Grafana | 3000 | HTTP |
---
## Integration with AI Agents
This skill can be used by any AI coding agent that supports HTTP requests:
- **OpenCode/Claude Code**: Use bash tool with curl commands
- **Cursor**: Use terminal or HTTP client extensions
- **GitHub Copilot**: Use inline curl in terminal
- **Windsurf**: Use built-in terminal
### Example Agent Integration
```
User: "Create a plan to build a web scraper"
Agent uses Synapse skill:
1. curl POST /api/v1/claude/plan with task and model config
2. Parse response and present steps to user
3. Offer to generate code for each step
4. Execute tests via Codex
5. Review final code via Gemini
```
### Swarm Mode Integration
For complex multi-file tasks, use swarm orchestration:
```
User: "Review all authentication files for security issues"
Agent orchestrates:
1. Spawn parallel Gemini reviewers for each file
2. Aggregate findings
3. Generate summary report
4. Propose fixes via Claude
```
---
## Current Status (v2.3.0)
### Service Health (Verified 2026-01-28)
| Service | Endpoint | Status | Response |
|---------|----------|--------|----------|
| Gateway | `/health` | ✅ healthy | `{"status": "healthy"}` |
| Claude | `/api/v1/claude/plan` | ✅ success | 5-step plan generated |
| Gemini | `/api/v1/gemini/analyze` | ✅ success | Code analysis complete |
| Gemini | `/api/v1/gemini/review` | ✅ success | Score 95/100 |
| Codex | `/api/v1/codex/execute` | ✅ success | Command executed |
### Connection Pool Metrics
```
Claude Pool Gemini Pool Codex Pool
┌────────────┐ ┌────────────┐ ┌────────────┐
│ Size: 2 │ │ Size: 2 │ │ Size: 2 │
│ Avail: 2 │ │ Avail: 2 │ │ Avail: 2 │
│ Acquired:3 │ │ Acquired:4 │ │ Acquired:3 │
│ Released:3 │ │ Released:4 │ │ Released:3 │
└────────────┘ └────────────┘ └────────────┘
Load Balancer Status: All endpoints healthy (1/1 each)
Avg Response Time (Claude): 21.47ms
```
### Architecture Overview
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ SYNAPSE WORKFLOW ARCHITECTURE │
└─────────────────────────────────────────────────────────────────────────────┘
┌──────────────┐
│ Gateway │ :8000
│ (REST) │
└──────┬───────┘
│
┌──────────────────────┼──────────────────────┐
│ │ │
▼ ▼ ▼
┌────────────────┐ ┌────────────────┐ ┌────────────────┐
│ Claude │ │ Gemini │ │ Codex │
│ :5011 │ │ :5012 │ │ :5013 │
│ (gRPC) │ │ (gRPC) │ │ (gRPC) │
└────────────────┘ └────────────────┘ └────────────────┘
│ │ │
▼ ▼ ▼
┌────────────┐ ┌────────────┐ ┌────────────┐
│ /plan │ │ /analyze │ │ /execute │
│ /code │ │ /review │ │ │
└────────────┘ └────────────┘ └────────────┘
```
---
## Improvement Roadmap
### 1. Unified Workflow Endpoint Enhancement
**Current**: Individual service calls required
```bash
curl /api/v1/claude/plan → curl /api/v1/claude/code → curl /api/v1/gemini/review → curl /api/v1/codex/execute
```
**Planned**: Single workflow call with `workflow_type` parameter
```bash
curl /api/v1/workflow -d '{"task": "...", "workflow_type": "pipeline|parallel|swarm"}'
```
### 2. MCP Tool Direct Integration
**Current**: curl-based access via Bash tool
```
Bash → curl → Gateway → Service
```
**Planned**: Native MCP server tools
```
mcp__synapse__plan → Gateway → Claude
mcp__synapse__analyze → Gateway → Gemini
mcp__synapse__execute → Gateway → Codex
```
### 3. Enhanced Error Handling
**Current**: Simple error response
```json
{"detail": "Service not ready"}
```
**Planned**: Rich error with retry guidance
```json
{
"error": "Service not ready",
"retry_after": 5,
"fallback_available": true,
"fallback_service": "gemini-2.5-flash"
}
```
### 4. SSE Streaming Response Support
**Current**: Full response wait
```python
response = await service.plan(request) # Waits for completion
```
**Planned**: Real-time progress streaming
```python
async for chunk in service.plan_stream(request):
yield chunk # Real-time progress updates
```
### 5. Redis Caching Layer
**Planned Architecture**:
```
Request
│
▼
┌─────────────┐ Cache Hit ┌─────────────┐
│ Gateway │ ─────────────────▶ │ Redis │
└──────┬──────┘ └─────────────┘
│ Cache Miss
▼
┌─────────────┐
│ Service │
└─────────────┘
```
### 6. Quick Commands (Planned)
```bash
# Shorthand commands for common operations
synapse plan "Build REST API" # → Claude Plan
synapse review "def foo(): ..." # → Gemini Review
synapse run "pytest tests/" # → Codex Execute
synapse flow "Create feature X" # → Full Pipeline
```
### 7. Auto Service Detection
**Planned Features**:
- Docker container status check on skill activation
- Automatic unhealthy service restart prompt
- Service dependency validationRelated Skills
synapse-action-development
Explains how to create Synapse plugin actions. Use when the user asks to "create an action", "write an action", uses "@action decorator", "BaseAction class", "function-based action", "class-based action", "Pydantic params", "ActionPipeline", "DataType", "input_type", "output_type", "semantic types", "YOLODataset", "ModelWeights", "pipeline chaining", or needs help with synapse plugin action development.
bgo
Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.
synthflow-ai-automation
Automate Synthflow AI tasks via Rube MCP (Composio). Always search tools first for current schemas.
sync-agents
Synchronize GitHub Copilot instructions, custom agents, and skills into detected AI coding agent configurations in this repository. Use when asked to mirror .github/copilot-instructions.md, .github/instructions, .github/agents, or .github/skills into Claude, Codex, Cursor, Gemini, Windsurf, and related tooling.
swot-pestle-analysis
Strategic environmental analysis using SWOT, PESTLE, and Porter's Five Forces. Creates structured assessments with Mermaid visualizations for competitive positioning and strategic planning.
switchailocal
Unified LLM proxy for AI agents. Route all model requests through http://localhost:18080/v1. Provides FREE access to Gemini CLI, Claude CLI, Codex, and Vibe via your existing subscriptions. Use when: (1) making LLM calls using provider prefixes, (2) switching between CLI/Local/Cloud providers, (3) needing to attach local files/folders to prompts via CLI, (4) requiring intelligent routing between models, or (5) needing to monitor provider health and analytics.
swift-actor-persistence
Use when building a thread-safe data persistence layer in Swift using actors with in-memory cache and file storage.
swamp-vault
Manage swamp vaults for secure secret storage. Use when creating vaults, storing secrets, retrieving secrets, listing vault keys, or working with vault expressions in workflows. Triggers on "vault", "secret", "secrets", "credentials", "api key storage", "secure storage", "password", "token", "key management", "sensitive data", "encrypt", "aws secrets manager", "store secret", "put secret", "get secret", "credential storage", or vault-related CLI commands.
supadata-automation
Automate Supadata tasks via Rube MCP (Composio). Always search tools first for current schemas.
Suno Song Creator
This skill should be used when the user asks to "create a Suno prompt", "write a Suno song", "generate music with Suno", "help me with Suno", "make a song prompt", "create lyrics for Suno", "build a music prompt", or mentions Suno AI music generation. Provides comprehensive guidance for creating professional Suno prompts using advanced prompting strategies, structured formatting within 1000 character limit (NO blank lines between sections), parameter optimization, genre-specific techniques, interactive questioning with efficient project name collection, automated artist/song research via sub-agent (web fetching + pattern extraction), automatic file export to organized project directories, AI-slop avoidance for authentic human-centered lyrics, copyright-safe style descriptions that avoid artist/album/song names, character counting utilities for accurate verification, and optional independent quality review via sub-agent for professional assessment.
summarize
Summarize or extract text/transcripts from URLs, podcasts, and local files.
subgraph-explorer
Explore and query blockchain subgraphs through a private MCP server running in Docker. Use this skill when exploring GraphQL subgraphs, querying blockchain data from subgraphs (NFT transfers, DEX swaps, DeFi metrics), examining subgraph schemas, or exporting discovered queries for project use. The skill manages Docker-based MCP server interaction and provides utilities for query development and export.