swarmdo

Foundation plugin — registers the swarmdo MCP server (300+ tools across memory/agentdb/embeddings/hooks/aidefence/neural/autopilot/browser/agent/swarm), provides 3 generalist agents (coder/researcher/reviewer), 3 first-run skills, and a curated plugin-discovery catalog

Agent teams, swarm coordination, Monitor streams, and worktree isolation — wraps 4 swarm_* + 8 agent_* MCP tools (12 total) plus 6 topologies (hierarchical / mesh / hierarchical-mesh / ring / star / adaptive)

Cache-aware /loop workers and CronCreate background automation — wraps 5 hooks_worker-* MCP tools (list/dispatch/status/detect/cancel) and exposes 12 background worker triggers (ultralearn, optimize, consolidate, predict, audit, map, preload, deepdive, document, refactor, benchmark, testgaps)

Security review, dependency scanning, policy gates, and CVE monitoring

SwarmVector memory with HNSW search, AgentDB, and semantic retrieval

Test gap detection, coverage analysis, and automated test generation — drives the testgaps background worker via hooks_worker-dispatch; SPARC Refinement-phase canonical owner

Documentation generation, API docs (JSDoc/TSDoc/OpenAPI), and drift detection — drives the `document` background worker via hooks_worker-dispatch; uses Haiku model for cost-efficient docs work

Autonomous /loop-driven task completion with learning, prediction, and progress tracking — wraps 10 autopilot_* MCP tools (status/enable/disable/config/reset/log/progress/learn/history/predict)

User-facing surface for Swarmdo's self-learning system: 6 neural_* + 10 hooks_intelligence_* + 9 routing/meta hooks + 4 SONA/MicroLoRA tools (29 total). Implements the 4-step pipeline (RETRIEVE → JUDGE → DISTILL → CONSOLIDATE) and IPFS-based cross-project pattern transfer.

Substrate plugin for Swarmdo memory: AgentDB controller bridge (15 agentdb_* MCP tools), SwarmVector ONNX embeddings (10 embeddings_* tools incl. RaBitQ 32x quantization), and WASM HNSW pattern router (3 swarmllm_hnsw_* tools)

AI safety scanning, PII detection, prompt injection defense, and adaptive threat learning

Session-as-skill browser automation: Playwright + RVF cognitive containers + swarmvector trajectories + AgentDB selector memory + AIDefence PII/injection gates

Advanced git workflows with diff analysis, risk scoring, change classification (feature/bugfix/refactor/...), and reviewer recommendations — wraps 6 analyze_* MCP tools (diff, diff-risk, diff-classify, diff-reviewers, file-risk, diff-stats)

Agent runtimes for swarmdo — local WASM-sandboxed agents (rvagent: 10 wasm_agent_*/wasm_gallery_* MCP tools, built on @swarmvector/rvagent-wasm + @swarmvector/swarmllm-wasm per ADR-070) plus Anthropic Claude Managed Agents as a cloud backend (managed_agent_* MCP tools per ADR-115). One interface, local-vs-cloud runtimes.

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.

Dynamic Agentic Architecture — 8 daa_* MCP tools for adaptive agents (create/adapt), cognitive patterns, workflows (create/execute), knowledge sharing, and learning/performance metrics. Feeds the JUDGE phase of the 4-step intelligence pipeline.

SwarmLLM local inference with chat formatting (Claude/GPT/Gemini/Ollama/Cohere), model configuration, MicroLoRA fine-tuning, and SONA real-time adaptation

RVF format for portable agent memory, session persistence, and cross-platform transfer

Scaffold, validate, and publish new Claude Code plugins with the canonical plugin contract — ADR + smoke + Compatibility + namespace coordination + MCP-tool drift warnings

Long-horizon goal planning, deep research orchestration, and adaptive replanning using GOAP algorithms

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)

Token usage tracking, model cost attribution per agent, budget alerts, and optimization recommendations — uses memory_* (namespace-routed) for cost-tracking and cost-patterns; pairs with federation budget circuit breaker (ADR-097)

Domain-Driven Design scaffolding — bounded contexts, aggregate roots, domain events, value objects, repositories, and anti-corruption layers; navigable domain graph stored in AgentDB

Cross-installation agent federation with zero-trust security, peer discovery, consensus-based task routing, and per-call budget circuit breaker (ADR-097)

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

IoT device lifecycle, telemetry anomaly detection, fleet management, and witness chain verification for Cognitum Seed hardware

Knowledge graph construction — entity extraction, relation mapping, and pathfinder graph traversal

Market data ingestion — feed normalization, OHLCV vectorization, and HNSW-indexed pattern matching

Schema migration management — generate, validate, dry-run, and rollback database migrations

Neural trading via npx neural-trader — self-learning strategies, Rust/NAPI backtesting, 112+ MCP tools, swarm coordination, and portfolio optimization

Structured logging, distributed tracing, and metrics — correlate agent swarm activity with application telemetry

Self-learning vector database via npx [email protected] — HNSW, adaptive LoRA embeddings, code-graph clustering, hooks routing, brain/SONA, 103 MCP tools

SPARC methodology — Specification, Pseudocode, Architecture, Refinement, Completion phases with gate checks

MetaHarness integration for swarmdo — surfaces score/genome/mint/mcp-scan/threat-model via skills; pairs with @metaharness/router (ADR-148/149) for cost-optimal model routing; honors ADR-150's architectural constraint that MetaHarness remains an optional augmentation, never a required runtime dependency

Competitive ruliology for Swarmdo swarms — arenas, tournaments, and adaptive co-evolution of program strategies (ADR-147/148). Strategies-as-programs compete under payoff games; tournaments produce Wolfram-style competitive arrays; hill-climb and mutual co-evolution discover winners empirically.

Caveman token compression for swarmdo — compress memory files (CLAUDE.md, todos) into few-token caveman-speak while preserving all technical substance. Vendored from JuliusBrussee/sdo-caveman (MIT).

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).