discover-agentic

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.

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Install skill "discover-agentic" with this command: npx skills add rand/cc-polymath/rand-cc-polymath-discover-agentic

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.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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