By SwarmDo
Workflow automation across two surfaces: the 10 workflow_* MCP tools (create/run/execute/status/list/pause/resume/cancel/delete/template) with full state-machine lifecycle (created → running ↔ paused → completed/cancelled), and native Claude Code Workflow JS orchestration (.claude/workflows/*.js — agent/parallel/pipeline/phase fan-out). Includes GAIA benchmark component for Princeton HAL leaderboard submissions.
Report cumulative GAIA API spend and project cost for planned configurations
Show measured benchmark runs stored across sessions in the gaia-runs memory namespace
Fetch and display current HAL GAIA leaderboard scores and our positioning
Execute a GAIA benchmark run — shells out to gaia-bench run, streams progress, and writes JSON results
Package GAIA results into an Ed25519-signed, HAL-compatible submission archive
Specialized agent for executing GAIA benchmark runs, monitoring progress, and analyzing results
Specialized agent for packaging, signing, and coordinating HAL leaderboard submission of GAIA benchmark results
Workflow automation specialist for creating, executing, and managing multi-step processes
Side-by-side comparison of swarmdo vs HAL vs other GAIA harnesses — capability gaps, design decisions, and improvement roadmap
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix
Walk through a complete GAIA benchmark→submit flow — from key resolution through HAL-compatible package generation
Author a workflow — either an MCP workflow template (persisted, lifecycle) or a native .claude/workflows/*.js orchestration script (agent/parallel/pipeline fan-out)
Run a workflow — drive an MCP workflow lifecycle (execute/pause/resume/cancel) or invoke + resume a native .claude/workflows/*.js orchestration via the Workflow tool
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 |
npx claudepluginhub swarmdo/swarmdo --plugin swarmdo-workflowsAI 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)
v9.52.0 - Reliability wave: tangle contextual review correction loop with hard round ceiling, progress-supervised review rounds (per-agent stall watch, descendant-tree kills), council diversity and agy pin fixes, marketplace generator source-of-truth fix, provider troubleshooting runbook and cost-expectations docs. Run /octo:setup.
Harness-native ECC operator layer - 67 agents, 278 skills, 94 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Persistent file-based planning for AI coding agents. Crash-proof markdown plans (task_plan.md, findings.md, progress.md) that survive context loss and /clear, with an opt-in completion gate and multi-agent shared state. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard. Includes Arabic, German, Spanish, and Chinese (Simplified and Traditional).
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
The Claude Code knowledge system — 380+ skills, 182+ agents, 100+ commands, 40 hooks, 32 rules, and workflows.
Comprehensive feature development workflow with specialized agents for codebase exploration, architecture design, and quality review