skill:divine - Divine Toolkit Entry Point

Version: 1.0.0

Purpose

The divine skill is the master entry point for The Forge's entire toolkit. It discovers and catalogs all available skills, agents, and commands, then recommends the optimal tool or workflow for a given task. Use this skill when users need guidance on which Forge capabilities to employ, when exploring what's available, or when orchestrating multi-skill workflows.

File Structure

skills/divine/
├── SKILL.md (this file)
└── examples.md

Interface References

• Context: Loaded via ContextProvider Interface
• Memory: Accessed via MemoryStore Interface
• Schemas: Validated against context_metadata.schema.json and memory_entry.schema.json

Mandatory Workflow

IMPORTANT: Execute ALL steps in order. Do not skip any step.

Step 1: Initial Analysis

• Gather user intent (what task or problem they want to solve)
• Determine the scope: skill discovery, agent recommendation, command lookup, or full workflow orchestration
• Identify whether the user needs a single tool or a multi-tool workflow

Step 2: Load Memory

• Use memoryStore.getSkillMemory("divine", "{project-name}") to load existing project memory. See MemoryStore Interface.
• Load previously recommended workflows and their outcomes
• Retrieve user preference patterns for tool selection

Step 3: Load Context

• Load engineering domain context via contextProvider.getIndex("engineering"). See ContextProvider Interface.
• Load the skill registry (all available SKILL.md files)
• Load the agent registry (all agent .config.json files)
• Load the command registry (all command .md files)

Step 4: Discover Available Tools

• Enumerate all skills, agents, and commands in The Forge
• Classify each by category, domain, and capability
• Build an indexed catalog with triggers, descriptions, and prerequisites

Step 5: Match Task to Tools

• Analyze the user's task against the catalog
• Score each tool for relevance based on:
  • Domain alignment (language, framework, infrastructure)
  • Task type match (review, generate, plan, analyze, deploy)
  • Trigger keyword matches
  • Historical success from memory
• Rank recommendations by confidence

Step 6: Compose Workflow

• For simple tasks: recommend a single skill, agent, or command
• For complex tasks: compose a multi-step workflow with:
  • Ordered skill invocations via skillInvoker
  • Agent delegation assignments
  • Command sequences
  • Data flow between steps
• Include estimated effort and prerequisites for each step

Step 7: Generate Output

• Save output to /claudedocs/divine_{project}_{YYYY-MM-DD}.md
• Follow naming conventions in ../OUTPUT_CONVENTIONS.md
• Present recommendations with rationale and confidence scores

Step 8: Update Memory

• Use memoryStore.update(layer="skill-specific", skill="divine", project="{project-name}", ...) to store insights. See MemoryStore Interface.
• Record which tools were recommended and for what tasks
• Track user feedback on recommendation quality
• Update preference patterns for future recommendations

Compliance Checklist

Before completing, verify:

• All mandatory workflow steps executed in order
• Memory loaded via memoryStore.getSkillMemory() (Step 2)
• Context loaded via contextProvider.getIndex() (Step 3)
• Tool discovery completed with full catalog (Step 4)
• Task-to-tool matching performed with scoring (Step 5)
• Output saved with standard naming convention
• Memory updated via memoryStore.update() (Step 8)

Version History

Version	Date	Changes
1.0.0	2026-02-12	Initial release — toolkit discovery, task matching, workflow composition