/discover-agentic

name: discover-agentic
description: Automatically discover agentic workflow skills when building AI agents, implementing tool use patterns, managing context windows, decomposing complex tasks, or designing multi-step autonomous workflows. Activates for agentic AI development.
license: MIT
metadata:
  author: rand
  version: "4.0"
compatibility: Designed for Claude Code. Compatible with any agent supporting the Agent Skills format.

Agentic Workflow Skills Discovery

Provides automatic access to skills for building autonomous AI agents, managing tool use, and orchestrating multi-step workflows.

When This Skill Activates

This skill auto-activates when you're working with:

• AI agent development and autonomous workflows
• Task decomposition for LLM agents
• Function calling and tool use patterns
• Context window management and summarization
• Working memory, scratchpads, and state tracking
• Long-term memory and persistence patterns
• Multi-step reasoning and planning
• Failure recovery and re-planning strategies
• Parallel vs sequential execution decisions

Available Skills

Quick Reference

The Agentic category contains 3 specialized skills:

1. **agentic-task-decomposition** - Breaking complex goals into agent-executable steps, dependency graphs, re-planning 2. **agentic-tool-use** - Function calling patterns, parallel tool use, error handling, tool selection heuristics 3. **agentic-memory** - Context window management, working memory, long-term persistence, summarization

Load Full Category Details

For complete descriptions and workflows:

Read ../agentic/INDEX.md

This loads the full Agentic category index with:

• Detailed skill descriptions
• Usage triggers for each skill
• Common workflow combinations
• Cross-references to related skills

Load Specific Skills

Load individual skills as needed:

Task planning and decomposition

Read ../agentic/agentic-task-decomposition.md

Tool calling and execution

Read ../agentic/agentic-tool-use.md

Context and memory management

Read ../agentic/agentic-memory.md

Common Workflows

Building an Agent from Scratch

**Sequence**: Decomposition -> Tool Use -> Memory

Read ../agentic/agentic-task-decomposition.md # Plan the agent's task handling Read ../agentic/agentic-tool-use.md # Implement tool execution Read ../agentic/agentic-memory.md # Add context management

Adding Tool Use to an Agent

**Sequence**: Tool Use -> Decomposition

Read ../agentic/agentic-tool-use.md # Tool calling patterns Read ../agentic/agentic-task-decomposition.md # Multi-tool task planning

Scaling Agent Sessions

**Sequence**: Memory -> Decomposition

Read ../agentic/agentic-memory.md # Context management Read ../agentic/agentic-task-decomposition.md # Context-bounded task sizing

Complete Agentic Stack

**Full implementation**:

1. Planning layer

Read ../agentic/agentic-task-decomposition.md

2. Execution layer

Read ../agentic/agentic-tool-use.md

3. Memory layer

Read ../agentic/agentic-memory.md

Skill Selection Guide

**Choose task decomposition when:**

• Complex goal needs breaking into steps
• Tasks have dependencies or ordering constraints
• Need to handle ambiguous requirements
• Building a planning layer for an agent

**Choose tool use when:**

• Implementing function calling in an LLM agent
• Debugging tool call failures or inefficiency
• Designing tool schemas and structured outputs
• Optimizing multi-tool workflows

**Choose memory when:**

• Agent sessions are hitting context limits
• Need to persist state across turns or sessions
• Building multi-turn conversational agents
• Implementing retrieval-augmented generation

Integration with Other Skills

Agentic skills commonly combine with:

**API skills** (`discover-api`):

• Agents that call REST/GraphQL APIs
• Tool schemas for API endpoints
• Authentication handling in agent workflows

**Testing skills** (`discover-testing`):

• Testing agent behaviors and tool use
• Autonomous test generation
• Verifying agent task completion

**Database skills** (`discover-database`):

• Database-backed agent memory
• Agents that query and modify data
• Persistent state management

**Infrastructure skills** (`discover-infra`, `discover-cloud`):

• Deploying agent systems
• Scaling agent workloads
• Cost optimization for LLM calls

Usage Instructions

1. **Auto-activation**: This skill loads automatically when Claude Code detects agentic workflow tasks 2. **Browse skills**: Run `Read ../agentic/INDEX.md` for full category overview 3. **Load specific skills**: Use commands above to load individual skills 4. **Follow workflows**: Use recommended sequences for common agentic patterns 5. **Combine skills**: Load multiple skills for comprehensive coverage

Progressive Loading

This gateway skill (~200 lines, ~2K tokens) enables progressive loading:

• **Level 1**: Gateway loads automatically (you're here now)
• **Level 2**: Load category INDEX.md (~3K tokens) for full overview
• **Level 3**: Load specific skills (~2-3K tokens each) as needed

Total context: 2K + 3K + skill(s) = 5-10K tokens vs 12K+ for entire category.

Quick Start Examples

**"Build an autonomous coding agent"**: Read ../agentic/agentic-task-decomposition.md

**"How should my agent call tools?"**: Read ../agentic/agentic-tool-use.md

**"My agent is running out of context"**: Read ../agentic/agentic-memory.md

**Next Steps**: Run `Read ../agentic/INDEX.md` to see full category details, or load specific skills using the commands above.