Claude Skills by monoes

Mastermind plugins — install, enable, disable, uninstall, and inspect plugins for an org. Plugins extend agent capabilities with workers, events, and custom tools. Supports npm packages and local paths.

Mastermind profile — view and edit the current operator profile (display name, preferences) and inspect any user's activity statistics, completion rate, and token usage. Merges ProfileSettings.tsx and UserProfile.tsx.

Shared protocol for all mastermind domain skills — brain-load, brain-write, output schema, memory scoring, and task briefing standard. Never invoked directly; referenced by domain skills and master.

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable — requires technical rigor and verification, not performative agreement or blind implementation

Mastermind release domain — versioning, changelog, deployment coordination. Spawns a Release Manager who coordinates testing and devops agents for a safe, traceable release pipeline.

REPEAT POSTAMBLE — executes inter-session repeat/tillend loop continuation after any mastermind or monomind command completes. Calls ScheduleWakeup when work remains.

Mastermind research domain — market research, competitor analysis, user research, trend scanning. Spawns a Research Manager coordinating a mesh of researcher agents for comprehensive intelligence gathering.

Mastermind review domain — code review, content review, strategy review, security audit. Spawns a Review Manager coordinating a mesh of specialist reviewers for multi-angle assessment.

Mastermind routine-detail — deep inspection and management of a single routine: trigger config (schedule/webhook), variables, concurrency/catchup policies, run history, webhook rotation, and revision tracking.

Mastermind routines — schedule recurring tasks that trigger agent heartbeats on a cron-like schedule within a running org. Configure concurrency policy and catch-up behavior.

Start a saved org via the Org Runtime v2 daemon (monomind org run/serve). Migrates v1-shaped configs first. The legacy prompt-orchestrated path lives in runorgv1.

Mastermind search — fuzzy cross-org search across tasks, goals, agents, approvals, routines, projects, and activity log. Returns ranked results with org context.

Mastermind secrets — manage org-scoped API keys and secrets consumed by agents. Store, rotate, list, and audit secrets without exposing values in logs or state files.

Use when creating new mastermind skills, editing existing mastermind skills, or verifying mastermind skills work before deployment

Mastermind skills — list, sync, and map skills available to org agents. Scans .claude/skills/ directory and shows which roles have access to which skill domains.

Mastermind stoporg — stop a running scheduled org loop by setting its status to "stopped". The next scheduled wakeup will read the status, skip all work, and not reschedule. Loop dies within one interval — no orphaned wakeups.

Mastermind tasks — view, create, assign, and move tasks on an org's task board. Supports parent-child chains, goal linkage, and status filtering.

Tech Port — deep-analyzes a foreign project, reviews the current monomind target to avoid conflicts and duplication, produces a scored port plan with mono-branded naming, and executes approved ports with full brand normalization.

Mastermind threads — list, view, and create conversation threads within an org. Threads are human-or-agent discussions attached to issues, goals, or the org itself. Reads from -threads.jsonl org state files.

Mastermind tree-control — pause, hold, release, or preview recovery for an issue/task tree in an org. Lets board members stop runaway loops, hold trees during review, and resume work when ready. Mirrors Paperclip's issue-tree-control API.

Mastermind workspace-detail — deep per-execution-workspace inspection and runtime control. Manage services, provision/teardown/cleanup commands, linked issues and routines, runtime logs, and configuration for a single execution workspace.

Mastermind workspaces — manage isolated git worktree workspaces per project. List, attach, detach, stop, and prune workspaces. Grouped by project with running service counts and agent assignments.

Use when starting feature work that needs isolation from the current workspace or before executing implementation plans — ensures an isolated workspace exists via native tools or git worktree fallback

Use when a request may need a Mastermind workflow such as planning, review, debugging, research, execution, organization work, or memory.

Use monomind's persistent memory store (local SQLite + local embeddings) to save, search, list, and retrieve cross-session knowledge — patterns, solutions, decisions. Trigger on "remember this", "store in memory", "search memory", "have we solved this before", "recall past decisions", or before starting work that benefits from prior context (debugging, refactors, repeated tasks).

Generate images via Gemini's browser session using the monoagentcli tool, always scoped to the "monoes" profile — no API key, no billing, browser-automated.

Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, research users, build a component system, generate design images, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, respon...

Full technical writing workbench — writes, reviews, fixes, scaffolds, and audits project docs per Google Developer Documentation Style Guide + industry best practices. Autodiscovers doc tasks. Enforces tone, formatting, accessibility, inclusive language, readability, terminology consistency, Diátaxis doc typing, and word-list compliance. Scaffolds 16 template types (README, ADR, RFC, runbook, migration, API ref, etc.). Measures doc coverage and maturity.

Whole-repo audit for over-engineering. Like monolean-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. Use when the user says "audit this codebase", "audit for over-engineering", "what can I delete from this repo", "find bloat", "monolean-audit", or "/monolean-audit". One-shot report, does not apply fixes.

Harvest every `monolean:` comment in the codebase into a debt ledger, so the deliberate shortcuts and deferrals monolean leaves behind get tracked instead of rotting into "later means never". Use when the user says "monolean debt", "/monolean-debt", "what did monolean defer", "list the shortcuts", "monolean ledger", or "what did we mark to do later". One-shot report, changes nothing.

Quick-reference card for all monolean modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /monolean-help, "monolean help", "what monolean commands", "how do I use monolean".

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "monolean", "be lean", "lean mode", "simplest solution", "minimal solution", "yagni", "do less", or "shorte...

HTML-native animation system using GSAP — timeline-driven, API-controllable animations that run in the browser without video rendering or React. Covers timeline control, WebSocket/REST-driven playback, effects, and sequencing.

Coordinate in-process multi-agent work with monomind — topology selection, agent lifecycle, shared memory, and vote-based consensus. Use when scaling beyond a single agent on tasks with clear decomposition, or when a decision needs a recorded vote before work proceeds.

AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Monomind swarms

Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.

Build the knowledge graph from code, docs (md/txt/rst), and PDFs — full index with optional Codex LLM semantic extraction

Search the knowledge graph using BM25 keyword search, semantic (embedding) search, or hybrid RRF-merged results — filter by node type (Section, Function, Class, File, Concept)

Show knowledge graph statistics — node counts by type, edge type breakdown, and top concepts by importance score

Watch for file changes and incrementally rebuild the knowledge graph — keeps the graph fresh during active development or documentation writing

Scan all docs and PDFs and build a searchable knowledge graph — optimized for documentation-heavy projects with Codex LLM semantic extraction

Analysis swarm strategy — distributed codebase, performance, and security analysis through coordinated mesh agents

Development swarm strategy — hierarchical team coordination for building features with architect → coder → tester flow

Swarm pattern examples — concrete recipes for research, development, analysis, and testing swarms with real MCP tool invocations

Maintenance swarm strategy — sequential coordinated system maintenance for dependency updates, security audits, and documentation

Main monoswarm skill — initializes and starts multi-agent swarms for research, development, analysis, testing, optimization, and maintenance tasks, with optional vote-based consensus

Optimization swarm strategy — performance profiling, bottleneck detection, and coordinated optimization through specialized mesh agents

Research swarm strategy — parallel information gathering with mesh topology for deep research, literature review, and knowledge synthesis

Testing swarm strategy — distributed parallel test execution with specialized unit, integration, E2E, and performance testing agents