By SwarmDo
Long-horizon goal planning, deep research orchestration, and adaptive replanning using GOAP algorithms
Multi-source research specialist that gathers, cross-references, and synthesizes information with evidence grading and contradiction resolution
Recursive parallel multi-source investigator that fans out across web, memory, knowledge-graph, codebase, and ADR index to build a graph-structured dossier on a seed entity, with budget caps, de-duplication, and provenance per claim
GOAP specialist that creates optimal action plans using A* search through state spaces, with adaptive replanning, trajectory learning, and multi-mode execution
Long-horizon objective tracker that persists progress across sessions with milestone checkpoints, drift detection, and adaptive timeline management
Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings
Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
Create and execute Goal-Oriented Action Plans (GOAP) with precondition analysis, cost optimization, and adaptive replanning
Track long-horizon objectives across multiple sessions with milestone checkpoints, progress persistence, and drift detection
Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations
Uses power tools
Uses Bash, Write, or Edit tools
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Based on the original, hugely popular ruflo — renamed, self-contained, and MIT-licensed. Full lineage in NOTICE.
An agent meta-harness for Claude Code and Codex.
Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work. Swarmdo is the harness — the execution layer around Claude Code and Codex that adds 100+ specialized agents, coordinated swarms, self-learning memory, federated comms across machines, and enterprise security guardrails. So agents don't just run, they collaborate.
One npx swarmdo init gives Claude Code a nervous system: agents self-organize into swarms, learn from every task, remember across sessions, and — with federation — securely talk to agents on other machines without leaking data. You keep writing code. Swarmdo handles the coordination.
Self-Learning / Self-Optimizing Agent Architecture
User --> Swarmdo (CLI/MCP) --> Router --> Swarm --> Agents --> Memory --> LLM Providers
^ |
+---- Learning Loop <-------+
New to Swarmdo? You don't need to learn 314 MCP tools or 26 CLI commands. After
init, just use Claude Code normally — the hooks system automatically routes tasks, learns from successful patterns, and coordinates agents in the background.
Swarmdo is now Swarmdo — named by
the upstream author, who loves Rust, flow states, and building things that feel inevitable. The "Ru" is the the upstream author. The "flo" is working until 3am. Underneath, powered byCognitum.Oneagentic architecture, running a supercharged Rust-based AI engine, embeddings, memory, and plugin system.
There are two different install paths with very different surface areas. Pick based on what you need (#1744):
| Claude Code Plugin | CLI install (npx swarmdo init) | |
|---|---|---|
| What it gives you | Slash commands + a few skills + agent definitions per-plugin | Full Swarmdo loop — 98 agents, 60+ commands, 30 skills, MCP server, hooks, daemon |
| Files in your workspace | Zero | .claude/, .swarmdo/, CLAUDE.md, helpers, settings |
| MCP server registered | No (memory_store, swarm_init, etc. unavailable to Claude) | Yes |
| Hooks installed | No | Yes |
| Best for | Try a single plugin's commands without committing to the full install | Production use — everything works as documented |
# Add the marketplace
/plugin marketplace add upstream/swarmdo
# Install core + any plugins you need
/plugin install swarmdo-core@swarmdo
/plugin install swarmdo-swarm@swarmdo
/plugin install swarmdo-rag-memory@swarmdo
/plugin install swarmdo-neural-trader@swarmdo
This adds slash commands and agent definitions only. The Swarmdo MCP server is NOT registered, so memory_store, swarm_init, agent_spawn, etc. won't be callable from Claude. For the full loop, use Path B below.
| Plugin | What it does |
|---|---|
| swarmdo-core | Foundation — server, health checks, plugin discovery |
| swarmdo-swarm | Coordinate multiple agents as a team |
| swarmdo-autopilot | Let agents run autonomously in a loop |
| swarmdo-loop-workers | Schedule background tasks on a timer |
| swarmdo-workflows | Reusable multi-step task templates |
| swarmdo-federation | Agents on different machines collaborate securely |
AI agent orchestration for Claude Code: swarm coordination, 314 MCP tools, 60+ agent types, persistent AgentDB memory with HNSW vector search, self-learning hooks, SPARC methodology, and GitHub automation
Ponytail for swarmdo — makes agents think like the laziest senior dev in the room: YAGNI, stdlib before dependencies, one line before fifty. Intensity levels lite/full/ultra plus audit, review, debt, and gain sub-skills. Vendored from DietrichGebert/sdo-ponytail (MIT).
Cross-installation agent federation with zero-trust security, peer discovery, consensus-based task routing, and per-call budget circuit breaker (ADR-097)
Self-learning vector database via npx [email protected] — HNSW, adaptive LoRA embeddings, code-graph clustering, hooks routing, brain/SONA, 103 MCP tools
ADR lifecycle management — create, index, supersede, check compliance, and link Architecture Decision Records to code via AgentDB hierarchical store + causal edges (supersedes/amends/depends-on/related)
npx claudepluginhub swarmdo/swarmdo --plugin swarmdo-goalsUltra-compressed communication mode. Cuts 65% of output tokens (measured) while keeping full technical accuracy by speaking like a caveman.
Comprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.
Unified capability management center for Skills, Agents, and Commands.
Standalone image generation plugin using Nano Banana MCP server. Generates and edits images, icons, diagrams, patterns, and visual assets via Gemini image models. No Gemini CLI dependency required.
Write feature specs, plan roadmaps, and synthesize user research faster. Keep stakeholders updated and stay ahead of the competitive landscape.