Agent skill
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.
Install this agent skill to your Project
npx add-skill https://github.com/rand/cc-polymath/tree/main/skills/discover-agentic
Metadata
Additional technical details for this skill
- author
- rand
- version
- 4.0
SKILL.md
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:
- agentic-task-decomposition - Breaking complex goals into agent-executable steps, dependency graphs, re-planning
- agentic-tool-use - Function calling patterns, parallel tool use, error handling, tool selection heuristics
- 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
- Auto-activation: This skill loads automatically when Claude Code detects agentic workflow tasks
- Browse skills: Run
Read ../agentic/INDEX.mdfor full category overview - Load specific skills: Use commands above to load individual skills
- Follow workflows: Use recommended sequences for common agentic patterns
- 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.
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