Claude Skills by monoes

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

monoswarm memory command (monomind)

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

monoswarm spawn command (monomind)

monoswarm status command (monomind)

monoswarm stop command (monomind)

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

Automatically select the optimal monoswarm topology based on task complexity — use pre-task hook recommendations, monoswarm init flags, and performance optimize CLI

Analyze and apply system-level performance optimizations — memory, CPU, and latency using npx monomind performance optimize

Real-world pair programming scenarios — JWT auth, memory leak debugging, TDD, code review, and refactoring with effective prompt patterns

Pair programming collaboration modes — driver, navigator, TDD, review, and debug modes with effective prompts for each

Pair programming session lifecycle — pre-session setup, context setting, mid-session quality checks, breakpoints, end-of-session recording, and multi-session continuity

Show the monomind statusline (version, git, swarm, security, hooks, token cost).

Execute predefined stream-chain pipelines for common development workflows — analysis, refactor, test, optimize. Each step feeds full context into the next.

Execute custom stream chains where you define the prompt sequence. Each step receives the full output of the previous step as context.

Show the Monomind token usage dashboard — reports spend and call counts for today, week, 30days, or month

Truth skill — assess system health, agent reliability, and task quality using real MCP metrics tools. Use when you want a holistic picture of how well the system is performing.

Toggle the Monomind statusline panel between full (multi-line dashboard) and compact (single-line) mode

Development workflow coordination pattern — hierarchical swarm for structured implementation tasks using real MCP tools and npx monomind workflow run -t development

Research workflow coordination pattern — mesh swarm for comprehensive exploration using real MCP tools and npx monomind workflow run -t research

Create and save custom workflow templates using npx monomind workflow template create — save successful workflows for reuse

Run multi-agent workflows using built-in templates (development, research, testing, security-audit, etc.) via real npx monomind workflow run CLI

Browse, inspect, and manage workflow templates — list built-in templates, show template details and stages, validate workflow files

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

monoswarm consensus command (monomind)

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

monoswarm init command (monomind)

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

monoswarm memory command (monomind)

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

monoswarm spawn command (monomind)

monoswarm status command (monomind)

monoswarm stop command (monomind)

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

Automatically select the optimal monoswarm topology based on task complexity — use pre-task hook recommendations, monoswarm init flags, and performance optimize CLI

Analyze and apply system-level performance optimizations — memory, CPU, and latency using npx monomind performance optimize

Real-world pair programming scenarios — JWT auth, memory leak debugging, TDD, code review, and refactoring with effective prompt patterns

Pair programming collaboration modes — driver, navigator, TDD, review, and debug modes with effective prompts for each

Pair programming session lifecycle — pre-session setup, context setting, mid-session quality checks, breakpoints, end-of-session recording, and multi-session continuity

Execute predefined stream-chain pipelines for common development workflows — analysis, refactor, test, optimize. Each step feeds full context into the next.

Execute custom stream chains where you define the prompt sequence. Each step receives the full output of the previous step as context.

Show the Monomind token usage dashboard — reports spend and call counts for today, week, 30days, or month

Truth skill — assess system health, agent reliability, and task quality using real MCP metrics tools. Use when you want a holistic picture of how well the system is performing.

Toggle the Monomind statusline panel between full (multi-line dashboard) and compact (single-line) mode

Development workflow coordination pattern — hierarchical swarm for structured implementation tasks using real MCP tools and npx monomind workflow run -t development