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Agent skill

Agent Migration Plan

by ruvnet in ruvnet/ruflo

Agent skill for migration-plan - invoke with $agent-migration-plan

MITAuto-check passed

Install Agent Migration Plan

skills CLI
$ npx skills add ruvnet/ruflo --skill agent-migration-plan -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ruvnet/ruflo agent-migration-plan --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/agent-migration-plan .claude/skills/agent-migration-plan && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agent-migration-plan
GitHub stars
74k
Used in
3 other repos
Token cost
~4.6k tokens
SKILL.md length
428 words
Files
1
Skills in repo
264
Repo updated
First seen
Licence
MIT

At a glance

Agent skill for migration-plan - invoke with $agent-migration-plan

  • Works in 12 steps: Coordination Agents → GitHub Integration Agents → SPARC Methodology Agents → …
  • SKILL.md covers Overview, Agent Definition Format, Migration Categories and Implementation Guidelines, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Agent Migration Plan is an agent skill from ruvnet/ruflo. Agent skill for migration-plan - invoke with $agent-migration-plan

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with GitHub. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.

Example prompts

  • “/agent-migration-plan”

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Coordination Agents
  2. GitHub Integration Agents
  3. SPARC Methodology Agents
  4. Analysis Agents
  5. Memory Management Agents
  6. Automation Agents
  7. Optimization Agents
  8. Monitoring Agents
  9. Agent Activation
  10. Tool Restrictions
  11. Inter-Agent Communication
  12. Migration Steps

What it can do on your machine

Read from SKILL.md and the folder at commit 6051f67. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agent Migration Plan loads about 4.6k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 428 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~22
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ruvnet/ruflo at commit 6051f67, republished under its MIT licence (© ruvnet). 428 words, ~4,605 tokens.

Download SKILL.mdSave it as .claude/skills/agent-migration-plan/SKILL.md (or your agent's skills folder).
name
agent-migration-plan
description
Agent skill for migration-plan - invoke with $agent-migration-plan

name: migration-planner type: planning color: red description: Comprehensive migration plan for converting commands to agent-based system capabilities:

  • migration-planning
  • system-transformation
  • agent-mapping
  • compatibility-analysis
  • rollout-coordination priority: medium hooks: pre: | echo "📋 Agent System Migration Planner activated" echo "🔄 Analyzing current command structure for migration"

    Check existing command structure

    if [ -d ".claude$commands" ]; then echo "📁 Found existing command directory - will map to agents" find .claude$commands -name "*.md" | wc -l | xargs echo "Commands to migrate:" fi post: | echo "✅ Migration planning completed" echo "📊 Agent mapping strategy defined" echo "🚀 Ready for systematic agent system rollout"

Claude Flow Commands to Agent System Migration Plan

Overview

This document provides a comprehensive migration plan to convert existing .claude$commands to the new agent-based system. Each command is mapped to an equivalent agent with defined roles, responsibilities, capabilities, and tool access restrictions.

Agent Definition Format

Each agent uses YAML frontmatter with the following structure:

yaml
---
role: agent-type
name: Agent Display Name
responsibilities:
  - Primary responsibility
  - Secondary responsibility
capabilities:
  - capability-1
  - capability-2
tools:
  allowed:
    - tool-name
  restricted:
    - restricted-tool
triggers:
  - pattern: "regex pattern"
    priority: high|medium|low
  - keyword: "activation keyword"
---

Migration Categories

1. Coordination Agents
Swarm Initializer Agent

Command: .claude$commands$coordination$init.md

yaml
---
role: coordinator
name: Swarm Initializer
responsibilities:
  - Initialize agent swarms with optimal topology
  - Configure distributed coordination systems
  - Set up inter-agent communication channels
capabilities:
  - swarm-initialization
  - topology-optimization
  - resource-allocation
  - network-configuration
tools:
  allowed:
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__topology_optimize
    - mcp__claude-flow__memory_usage
    - TodoWrite
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "init.*swarm|create.*swarm|setup.*agents"
    priority: high
  - keyword: "swarm-init"
---
Agent Spawner

Command: .claude$commands$coordination$spawn.md

yaml
---
role: coordinator
name: Agent Spawner
responsibilities:
  - Create specialized cognitive patterns for task execution
  - Assign capabilities to agents based on requirements
  - Manage agent lifecycle and resource allocation
capabilities:
  - agent-creation
  - capability-assignment
  - resource-management
  - pattern-recognition
tools:
  allowed:
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__daa_agent_create
    - mcp__claude-flow__agent_list
    - mcp__claude-flow__memory_usage
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "spawn.*agent|create.*agent|add.*agent"
    priority: high
  - keyword: "agent-spawn"
---
Task Orchestrator

Command: .claude$commands$coordination$orchestrate.md

yaml
---
role: orchestrator
name: Task Orchestrator
responsibilities:
  - Decompose complex tasks into manageable subtasks
  - Coordinate parallel and sequential execution strategies
  - Monitor task progress and dependencies
  - Synthesize results from multiple agents
capabilities:
  - task-decomposition
  - execution-planning
  - dependency-management
  - result-aggregation
  - progress-tracking
tools:
  allowed:
    - mcp__claude-flow__task_orchestrate
    - mcp__claude-flow__task_status
    - mcp__claude-flow__task_results
    - mcp__claude-flow__parallel_execute
    - TodoWrite
    - TodoRead
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "orchestrate|coordinate.*task|manage.*workflow"
    priority: high
  - keyword: "orchestrate"
---
2. GitHub Integration Agents
PR Manager Agent

Command: .claude$commands$github$pr-manager.md

yaml
---
role: github-specialist
name: Pull Request Manager
responsibilities:
  - Manage complete pull request lifecycle
  - Coordinate multi-reviewer workflows
  - Handle merge strategies and conflict resolution
  - Track PR progress with issue integration
capabilities:
  - pr-creation
  - review-coordination
  - merge-management
  - conflict-resolution
  - status-tracking
tools:
  allowed:
    - Bash  # For gh CLI commands
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__task_orchestrate
    - mcp__claude-flow__memory_usage
    - TodoWrite
    - Read
  restricted:
    - Write  # Should use gh CLI for GitHub operations
    - Edit
triggers:
  - pattern: "pr|pull.?request|merge.*request"
    priority: high
  - keyword: "pr-manager"
---
Code Review Swarm Agent

Command: .claude$commands$github$code-review-swarm.md

yaml
---
role: reviewer
name: Code Review Coordinator
responsibilities:
  - Orchestrate multi-agent code reviews
  - Ensure code quality and standards compliance
  - Coordinate security and performance reviews
  - Generate comprehensive review reports
capabilities:
  - code-analysis
  - quality-assessment
  - security-scanning
  - performance-review
  - report-generation
tools:
  allowed:
    - Bash  # For gh CLI
    - Read
    - Grep
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__github_code_review
    - mcp__claude-flow__memory_usage
  restricted:
    - Write
    - Edit
triggers:
  - pattern: "review.*code|code.*review|check.*pr"
    priority: high
  - keyword: "code-review"
---
Release Manager Agent

Command: .claude$commands$github$release-manager.md

yaml
---
role: release-coordinator
name: Release Manager
responsibilities:
  - Coordinate release preparation and deployment
  - Manage version tagging and changelog generation
  - Orchestrate multi-repository releases
  - Handle rollback procedures
capabilities:
  - release-planning
  - version-management
  - changelog-generation
  - deployment-coordination
  - rollback-execution
tools:
  allowed:
    - Bash
    - Read
    - mcp__claude-flow__github_release_coord
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__task_orchestrate
    - TodoWrite
  restricted:
    - Write  # Use version control for releases
    - Edit
triggers:
  - pattern: "release|deploy|tag.*version|create.*release"
    priority: high
  - keyword: "release-manager"
---
3. SPARC Methodology Agents
SPARC Orchestrator Agent

Command: .claude$commands$sparc$orchestrator.md

yaml
---
role: sparc-coordinator
name: SPARC Orchestrator
responsibilities:
  - Coordinate SPARC methodology phases
  - Manage task decomposition and agent allocation
  - Track progress across all SPARC phases
  - Synthesize results from specialized agents
capabilities:
  - sparc-coordination
  - phase-management
  - task-planning
  - resource-allocation
  - result-synthesis
tools:
  allowed:
    - mcp__claude-flow__sparc_mode
    - mcp__claude-flow__swarm_init
    - mcp__claude-flow__agent_spawn
    - mcp__claude-flow__task_orchestrate
    - TodoWrite
    - TodoRead
    - mcp__claude-flow__memory_usage
  restricted:
    - Bash
    - Write
    - Edit
triggers:
  - pattern: "sparc.*orchestrat|coordinate.*sparc"
    priority: high
  - keyword: "sparc-orchestrator"
---
SPARC Coder Agent

Command: .claude$commands$sparc$coder.md

yaml
---
role: implementer
name: SPARC Implementation Specialist
responsibilities:
  - Transform specifications into working code
  - Implement TDD practices with parallel test creation
  - Ensure code quality and standards compliance
  - Optimize implementation for performance
capabilities:
  - code-generation
  - test-implementation
  - refactoring
  - optimization
  - documentation
tools:
  allowed:
    - Read
    - Write
    - Edit
    - MultiEdit
    - Bash
    - mcp__claude-flow__sparc_mode
    - TodoWrite
  restricted:
    - mcp__claude-flow__swarm_init  # Focus on implementation
triggers:
  - pattern: "implement|code|develop|build.*feature"
    priority: high
  - keyword: "sparc-coder"
---
SPARC Tester Agent

Command: .claude$commands$sparc$tester.md

yaml
---
role: quality-assurance
name: SPARC Testing Specialist
responsibilities:
  - Design comprehensive test strategies
  - Implement parallel test execution
  - Ensure coverage requirements are met
  - Coordinate testing across different levels
capabilities:
  - test-design
  - test-implementation
  - coverage-analysis
  - performance-testing
  - security-testing
tools:
  allowed:
    - Read
    - Write
    - Edit
    - Bash
    - mcp__claude-flow__sparc_mode
    - TodoWrite
    - mcp__claude-flow__parallel_execute
  restricted:
    - mcp__claude-flow__swarm_init
triggers:
  - pattern: "test|verify|validate|check.*quality"
    priority: high
  - keyword: "sparc-tester"
---
4. Analysis Agents
Performance Analyzer Agent

Command: .claude$commands$analysis$performance-bottlenecks.md

yaml
---
role: analyst
name: Performance Bottleneck Analyzer
responsibilities:
  - Identify performance bottlenecks in workflows
  - Analyze execution patterns and resource usage
  - Recommend optimization strategies
  - Monitor improvement metrics
capabilities:
  - performance-analysis
  - bottleneck-detection
  - metric-collection
  - pattern-recognition
  - optimization-planning
tools:
  allowed:
    - mcp__claude-flow__bottleneck_analyze
    - mcp__claude-flow__performance_report
    - mcp__claude-flow__metrics_collect
    - mcp__claude-flow__trend_analysis
    - Read
    - Grep
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "analyze.*performance|bottleneck|slow.*execution"
    priority: high
  - keyword: "performance-analyzer"
---
Token Efficiency Analyst Agent

Command: .claude$commands$analysis$token-efficiency.md

yaml
---
role: analyst
name: Token Efficiency Analyzer
responsibilities:
  - Monitor token consumption across operations
  - Identify inefficient token usage patterns
  - Recommend optimization strategies
  - Track cost implications
capabilities:
  - token-analysis
  - cost-optimization
  - usage-tracking
  - pattern-detection
  - report-generation
tools:
  allowed:
    - mcp__claude-flow__token_usage
    - mcp__claude-flow__cost_analysis
    - mcp__claude-flow__usage_stats
    - mcp__claude-flow__memory_analytics
    - Read
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "token.*usage|analyze.*cost|efficiency.*report"
    priority: medium
  - keyword: "token-analyzer"
---
5. Memory Management Agents
Memory Coordinator Agent

Command: .claude$commands$memory$usage.md

yaml
---
role: memory-manager
name: Memory Coordination Specialist
responsibilities:
  - Manage persistent memory across sessions
  - Coordinate memory namespaces and TTL
  - Optimize memory usage and compression
  - Facilitate cross-agent memory sharing
capabilities:
  - memory-management
  - namespace-coordination
  - data-persistence
  - compression-optimization
  - synchronization
tools:
  allowed:
    - mcp__claude-flow__memory_usage
    - mcp__claude-flow__memory_search
    - mcp__claude-flow__memory_namespace
    - mcp__claude-flow__memory_compress
    - mcp__claude-flow__memory_sync
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "memory|remember|store.*context|retrieve.*data"
    priority: high
  - keyword: "memory-manager"
---
Neural Pattern Agent

Command: .claude$commands$memory$neural.md

yaml
---
role: ai-specialist
name: Neural Pattern Coordinator
responsibilities:
  - Train and manage neural patterns
  - Coordinate cognitive behavior analysis
  - Implement adaptive learning strategies
  - Optimize AI model performance
capabilities:
  - neural-training
  - pattern-recognition
  - cognitive-analysis
  - model-optimization
  - transfer-learning
tools:
  allowed:
    - mcp__claude-flow__neural_train
    - mcp__claude-flow__neural_patterns
    - mcp__claude-flow__neural_predict
    - mcp__claude-flow__cognitive_analyze
    - mcp__claude-flow__learning_adapt
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "neural|ai.*pattern|cognitive|machine.*learning"
    priority: high
  - keyword: "neural-patterns"
---
6. Automation Agents
Smart Agent Coordinator

Command: .claude$commands$automation$smart-agents.md

yaml
---
role: automation-specialist
name: Smart Agent Coordinator
responsibilities:
  - Automate agent spawning based on task requirements
  - Implement intelligent capability matching
  - Manage dynamic agent allocation
  - Optimize resource utilization
capabilities:
  - intelligent-spawning
  - capability-matching
  - resource-optimization
  - pattern-learning
  - auto-scaling
tools:
  allowed:
    - mcp__claude-flow__daa_agent_create
    - mcp__claude-flow__daa_capability_match
    - mcp__claude-flow__daa_resource_alloc
    - mcp__claude-flow__swarm_scale
    - mcp__claude-flow__agent_metrics
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "smart.*agent|auto.*spawn|intelligent.*coordination"
    priority: high
  - keyword: "smart-agents"
---
Self-Healing Coordinator Agent

Command: .claude$commands$automation$self-healing.md

yaml
---
role: reliability-engineer
name: Self-Healing System Coordinator
responsibilities:
  - Detect and recover from system failures
  - Implement fault tolerance strategies
  - Coordinate automatic recovery procedures
  - Monitor system health continuously
capabilities:
  - fault-detection
  - automatic-recovery
  - health-monitoring
  - resilience-planning
  - error-analysis
tools:
  allowed:
    - mcp__claude-flow__daa_fault_tolerance
    - mcp__claude-flow__health_check
    - mcp__claude-flow__error_analysis
    - mcp__claude-flow__diagnostic_run
    - Bash  # For system commands
  restricted:
    - Write  # Prevent accidental file modifications during recovery
    - Edit
triggers:
  - pattern: "self.*heal|auto.*recover|fault.*toleran|system.*health"
    priority: high
  - keyword: "self-healing"
---
7. Optimization Agents
Parallel Execution Optimizer Agent

Command: .claude$commands$optimization$parallel-execution.md

yaml
---
role: optimizer
name: Parallel Execution Optimizer
responsibilities:
  - Optimize task execution for parallelism
  - Identify parallelization opportunities
  - Coordinate concurrent operations
  - Monitor parallel execution efficiency
capabilities:
  - parallelization-analysis
  - execution-optimization
  - load-balancing
  - performance-monitoring
  - bottleneck-removal
tools:
  allowed:
    - mcp__claude-flow__parallel_execute
    - mcp__claude-flow__load_balance
    - mcp__claude-flow__batch_process
    - mcp__claude-flow__performance_report
    - TodoWrite
  restricted:
    - Write
    - Edit
triggers:
  - pattern: "parallel|concurrent|simultaneous|batch.*execution"
    priority: high
  - keyword: "parallel-optimizer"
---
Auto-Topology Optimizer Agent

Command: .claude$commands$optimization$auto-topology.md

yaml
---
role: optimizer
name: Topology Optimization Specialist
responsibilities:
  - Analyze and optimize swarm topology
  - Adapt topology based on workload
  - Balance communication overhead
  - Ensure optimal agent distribution
capabilities:
  - topology-analysis
  - graph-optimization
  - network-design
  - load-distribution
  - adaptive-configuration
tools:
  allowed:
    - mcp__claude-flow__topology_optimize
    - mcp__claude-flow__swarm_monitor
    - mcp__claude-flow__coordination_sync
    - mcp__claude-flow__swarm_status
    - mcp__claude-flow__metrics_collect
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "topology|optimize.*swarm|network.*structure"
    priority: medium
  - keyword: "topology-optimizer"
---
8. Monitoring Agents
Swarm Monitor Agent

Command: .claude$commands$monitoring$status.md

yaml
---
role: monitor
name: Swarm Status Monitor
responsibilities:
  - Monitor swarm health and performance
  - Track agent status and utilization
  - Generate real-time status reports
  - Alert on anomalies or failures
capabilities:
  - health-monitoring
  - performance-tracking
  - status-reporting
  - anomaly-detection
  - alert-generation
tools:
  allowed:
    - mcp__claude-flow__swarm_status
    - mcp__claude-flow__swarm_monitor
    - mcp__claude-flow__agent_metrics
    - mcp__claude-flow__health_check
    - mcp__claude-flow__performance_report
  restricted:
    - Write
    - Edit
    - Bash
triggers:
  - pattern: "monitor|status|health.*check|swarm.*status"
    priority: medium
  - keyword: "swarm-monitor"
---
Show full SKILL.md (169 more words)Show less

Implementation Guidelines

1. Agent Activation
  • Agents are activated by pattern matching in user messages
  • Higher priority patterns take precedence
  • Multiple agents can be activated for complex tasks
2. Tool Restrictions
  • Each agent has specific allowed and restricted tools
  • Restrictions ensure agents stay within their domain
  • Critical operations require specialized agents
3. Inter-Agent Communication
  • Agents communicate through shared memory
  • Task orchestrator coordinates multi-agent workflows
  • Results are aggregated by coordinator agents
4. Migration Steps
  1. Create .claude$agents/ directory structure
  2. Convert each command to agent definition format
  3. Update activation patterns for natural language
  4. Test agent interactions and handoffs
  5. Implement gradual rollout with fallbacks
5. Backwards Compatibility
  • Keep command files during transition
  • Map command invocations to agent activations
  • Provide migration warnings for deprecated commands

Monitoring Migration Success

Key Metrics
  • Agent activation accuracy
  • Task completion rates
  • Inter-agent coordination efficiency
  • User satisfaction scores
  • Performance improvements
Validation Criteria
  • All commands have equivalent agents
  • No functionality loss during migration
  • Improved natural language understanding
  • Better task decomposition and parallelization
  • Enhanced error handling and recovery

© ruvnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/agent-migration-plan of ruvnet/ruflo.

Open the folder on GitHubat commit 6051f67

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in ruvnet/ruflo, which our catalogue first saw on October 7, 2026.

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Works with

Questions about Agent Migration Plan

What does Agent Migration Plan do?

Agent skill for migration-plan - invoke with $agent-migration-plan. Agent Migration Plan is an agent skill from ruvnet/ruflo.

How do I install Agent Migration Plan in Claude Code?

Run `npx skills add ruvnet/ruflo --skill agent-migration-plan -a claude-code`. Or copy the skill folder (.agents/skills/agent-migration-plan in ruvnet/ruflo) into .claude/skills/agent-migration-plan in your project. Claude Code loads it when a task matches its description.

How do I install Agent Migration Plan in Codex?

Run `npx skills add ruvnet/ruflo --skill agent-migration-plan -a codex`. Or copy the skill folder (.agents/skills/agent-migration-plan in ruvnet/ruflo) into .agents/skills/agent-migration-plan in your project. Codex loads it when a task matches its description.

Can I use Agent Migration Plan in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/ruflo --skill agent-migration-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-migration-plan, .gemini/skills/agent-migration-plan, .github/skills/agent-migration-plan and .opencode/skills/agent-migration-plan in your project.

What does Agent Migration Plan need to run?

SKILL.md names no scripts, command-line tools or credentials: Agent Migration Plan is instructions for the agent only.

Does Agent Migration Plan access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Agent Migration Plan safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agent Migration Plan use?

Agent Migration Plan is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Migration Plan use?

About 4.6k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Agent Migration Plan?

Skills that share tags, products or a category with Agent Migration Plan: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Diagnosing Superpowers Sessions (obra/superpowers, 296k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars) and Greploop (onyx-dot-app/onyx, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Migration Plan?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,089 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 8, 2026.

Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.