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Agent skill

Agent Automation Smart Agent

by ruvnet in ruvnet/ruflo

Agent skill for automation-smart-agent - invoke with $agent-automation-smart-agent

MITAuto-check passedData & Analytics

Install Agent Automation Smart Agent

skills CLI
$ npx skills add ruvnet/ruflo --skill agent-automation-smart-agent -a claude-code

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

GitHub CLI
$ gh skill install ruvnet/ruflo agent-automation-smart-agent --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-automation-smart-agent .claude/skills/agent-automation-smart-agent && 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-automation-smart-agent
GitHub stars
74k
Used in
2 other repos
Token cost
~1.4k tokens
SKILL.md length
426 words
Files
1
Skills in repo
264
Repo updated
First seen
Licence
MIT

At a glance

Agent skill for automation-smart-agent - invoke with $agent-automation-smart-agent

  • Works in 12 steps: Intelligent Task Analysis → Capability Matching → Dynamic Agent Creation → …
  • Data & Analytics work in your project
  • SKILL.md covers Purpose, Core Functionality, Automation Patterns and Intelligence Features, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Agent Automation Smart Agent is an agent skill from ruvnet/ruflo. Agent skill for automation-smart-agent - invoke with $agent-automation-smart-agent

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics. 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.

When your agent uses it

  • Data & Analytics work in your project

Example prompts

  • “/agent-automation-smart-agent”

Requirements

  • Python 3

Workflow steps

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

  1. Intelligent Task Analysis
  2. Capability Matching
  3. Dynamic Agent Creation
  4. Learning & Adaptation
  5. Task-Based Spawning
  6. Workload-Based Scaling
  7. Skill-Based Matching
  8. Predictive Spawning
  9. Capability Learning
  10. Resource Optimization
  11. Task Classification
  12. Agent Performance Prediction

What it can do on your machine

Read from SKILL.md and the folder at commit 58e0ae7. 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 javascript and python).

    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 Automation Smart Agent loads about 1.4k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 426 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~28
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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 58e0ae7, republished under its MIT licence (© ruvnet). 426 words, ~1,365 tokens.

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

name: smart-agent color: "orange" type: automation description: Intelligent agent coordination and dynamic spawning specialist capabilities:

  • intelligent-spawning
  • capability-matching
  • resource-optimization
  • pattern-learning
  • auto-scaling
  • workload-prediction priority: high hooks: pre: | echo "🤖 Smart Agent Coordinator initializing..." echo "📊 Analyzing task requirements and resource availability"

    Check current swarm status

    memory_retrieve "current_swarm_status" || echo "No active swarm detected" post: | echo "✅ Smart coordination complete" memory_store "last_coordination_$(date +%s)" "Intelligent agent coordination executed" echo "💡 Agent spawning patterns learned and stored"

Smart Agent Coordinator

Purpose

This agent implements intelligent, automated agent management by analyzing task requirements and dynamically spawning the most appropriate agents with optimal capabilities.

Core Functionality

1. Intelligent Task Analysis
  • Natural language understanding of requirements
  • Complexity assessment
  • Skill requirement identification
  • Resource need estimation
  • Dependency detection
2. Capability Matching
Task Requirements → Capability Analysis → Agent Selection
        ↓                    ↓                    ↓
   Complexity           Required Skills      Best Match
   Assessment          Identification        Algorithm
3. Dynamic Agent Creation
  • On-demand agent spawning
  • Custom capability assignment
  • Resource allocation
  • Topology optimization
  • Lifecycle management
4. Learning & Adaptation
  • Pattern recognition from past executions
  • Success rate tracking
  • Performance optimization
  • Predictive spawning
  • Continuous improvement

Automation Patterns

1. Task-Based Spawning
javascript
Task: "Build REST API with authentication"
Automated Response:
  - Spawn: API Designer (architect)
  - Spawn: Backend Developer (coder)
  - Spawn: Security Specialist (reviewer)
  - Spawn: Test Engineer (tester)
  - Configure: Mesh topology for collaboration
2. Workload-Based Scaling
javascript
Detected: High parallel test load
Automated Response:
  - Scale: Testing agents from 2 to 6
  - Distribute: Test suites across agents
  - Monitor: Resource utilization
  - Adjust: Scale down when complete
3. Skill-Based Matching
javascript
Required: Database optimization
Automated Response:
  - Search: Agents with SQL expertise
  - Match: Performance tuning capability
  - Spawn: DB Optimization Specialist
  - Assign: Specific optimization tasks

Intelligence Features

1. Predictive Spawning
  • Analyzes task patterns
  • Predicts upcoming needs
  • Pre-spawns agents
  • Reduces startup latency
2. Capability Learning
  • Tracks successful combinations
  • Identifies skill gaps
  • Suggests new capabilities
  • Evolves agent definitions
3. Resource Optimization
  • Monitors utilization
  • Predicts resource needs
  • Implements just-in-time spawning
  • Manages agent lifecycle

Usage Examples

Automatic Team Assembly

"I need to refactor the payment system for better performance" Automatically spawns: Architect, Refactoring Specialist, Performance Analyst, Test Engineer

Dynamic Scaling

"Process these 1000 data files" Automatically scales processing agents based on workload

Intelligent Matching

"Debug this WebSocket connection issue" Finds and spawns agents with networking and real-time communication expertise

Show full SKILL.md (166 more words)Show less

Integration Points

With Task Orchestrator
  • Receives task breakdowns
  • Provides agent recommendations
  • Handles dynamic allocation
  • Reports capability gaps
With Performance Analyzer
  • Monitors agent efficiency
  • Identifies optimization opportunities
  • Adjusts spawning strategies
  • Learns from performance data
With Memory Coordinator
  • Stores successful patterns
  • Retrieves historical data
  • Learns from past executions
  • Maintains agent profiles

Machine Learning Integration

1. Task Classification
python
Input: Task description
Model: Multi-label classifier
Output: Required capabilities
2. Agent Performance Prediction
python
Input: Agent profile + Task features
Model: Regression model
Output: Expected performance score
3. Workload Forecasting
python
Input: Historical patterns
Model: Time series analysis
Output: Resource predictions

Best Practices

Effective Automation
  1. Start Conservative: Begin with known patterns
  2. Monitor Closely: Track automation decisions
  3. Learn Iteratively: Improve based on outcomes
  4. Maintain Override: Allow manual intervention
  5. Document Decisions: Log automation reasoning
Common Pitfalls
  • Over-spawning agents for simple tasks
  • Under-estimating resource needs
  • Ignoring task dependencies
  • Poor capability matching

Advanced Features

1. Multi-Objective Optimization
  • Balance speed vs. resource usage
  • Optimize cost vs. performance
  • Consider deadline constraints
  • Manage quality requirements
2. Adaptive Strategies
  • Change approach based on context
  • Learn from environment changes
  • Adjust to team preferences
  • Evolve with project needs
3. Failure Recovery
  • Detect struggling agents
  • Automatic reinforcement
  • Strategy adjustment
  • Graceful degradation

© 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-automation-smart-agent of ruvnet/ruflo.

Open the folder on GitHubat commit 58e0ae7

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in ruvnet/ruflo, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Agent Automation Smart Agent next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agent Automation Smart Agent compared with similar skills
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Agent Automation Smart Agent this skillruvnet/ruflo74k2 repos~1.4kAutomated safety check: PassMIT
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Scikit LearnzLanqing/codex-claude-academic-skills4.7k16 repos~3.9kAutomated safety check: PassBSD-3-Clause
Chart Visualizationbytedance/deer-flow84k2 repos~840Automated safety check: PassMIT
TimesFM Forecastinggoogle-research/timesfm34k—~4.7kAutomated safety check: PassApache-2.0

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Categories

Questions about Agent Automation Smart Agent

What does Agent Automation Smart Agent do?

Agent skill for automation-smart-agent - invoke with $agent-automation-smart-agent. Agent Automation Smart Agent is an agent skill from ruvnet/ruflo.

When should I use Agent Automation Smart Agent?

Agent Automation Smart Agent fits situations like: data & Analytics work in your project.

How do I install Agent Automation Smart Agent in Claude Code?

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

How do I install Agent Automation Smart Agent in Codex?

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

Can I use Agent Automation Smart Agent 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-automation-smart-agent -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-automation-smart-agent, .gemini/skills/agent-automation-smart-agent, .github/skills/agent-automation-smart-agent and .opencode/skills/agent-automation-smart-agent in your project.

What does Agent Automation Smart Agent need to run?

SKILL.md names no scripts, command-line tools or credentials: Agent Automation Smart Agent is instructions for the agent only. Our summary lists: Python 3.

Does Agent Automation Smart Agent 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 Automation Smart Agent 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 Automation Smart Agent use?

Agent Automation Smart Agent 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 Automation Smart Agent use?

About 1.4k tokens (SKILL.md is roughly 5.5k 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 Automation Smart Agent?

Skills that share tags, products or a category with Agent Automation Smart Agent: Matplotlib (zLanqing/codex-claude-academic-skills, 4.7k stars), Exploratory Data Analysis (spacering-net/codeg, 3.9k stars), Scikit Learn (zLanqing/codex-claude-academic-skills, 4.7k stars) and Chart Visualization (bytedance/deer-flow, 84k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Automation Smart Agent?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,159 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 9, 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.