Smart Routing for 400+ Commands
SkillDev toolsUsar cuando se necesita descubrir o enrutar a un comando específico entre los 400+ disponibles.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Smart Routing for 400+ Commands skill
What this skill tells your AI
The instructions your AI receives, as published by gonzalezpazmonica/savia in .claude/skills/smart-routing/SKILL.md and read by ahel’s review.
Intelligent command discovery and routing for large tool catalogs. Maps user intent to relevant command categories, loads only necessary tools, maintains usage frequency for Top-20 prioritization.
Core Components
Intent Classification
Parse user request to identify primary and secondary intents:
User: "¿Cómo está el sprint?"
→ Primary: sprint status tracking
→ Category: PM Operations
→ Tools: [sprint-status, board-flow, daily-routine]
Implemented in Step 1 (input analysis):
- Extract keywords (sprint, status, dashboard, report, security, etc.)
- Map to category probabilities
- Select top 1-2 categories
Frequency Tracking
Maintain data/tool-usage.jsonl with:
{ "command": "sprint-status", "count": 47, "last_used": "2026-03-06T15:30:00Z", "category": "pm" }
Update after each command execution.
Top-20 Algorithm
Always available commands (never unloaded):
- Most-used 10 commands (cross-category)
- 10 most-used from active category
Loaded only when explicitly searched or category active:
- Remaining 90% of catalog
- Loaded via
/tool-searchor/tool-catalog
Routing Logic (5 Steps)
Step 1: Intent Analysis (input)
- Extract keywords from user request
- Assign category probabilities (PM, Dev, Infra, Reporting, Compliance, Discovery, Admin)
- Identify secondary categories if applicable
Step 2: Category Selection
- Primary category: highest probability
- Secondary: if probability >30%, include its top tools
- Load 20-30 tools from selected categories
Step 3: Usage Frequency Weighting
- Boost: most-used commands in category (+priority in suggestions)
- Order results by: relevance + frequency
Step 4: Suggestion Generation
- Top 3 candidate commands for primary category
- 1-2 commands from secondary category
- Brief description + confidence score (%)
Step 5: User Confirmation
- Show suggestions with confidence
- User selects or enters new search
- Execute selected command or refine search
Data Structure
categories:
pm: [pbi-*, sprint-*, capacity-*, project-*]
dev: [spec-*, dev-*, arch-*, code-*]
infra: [infra-*, pipeline-*, deploy-*, env-*]
reporting: [report-*, audit-*, track-*, metric-*]
communication: [scheduled-*, notify-*, chat-*]
compliance: [security-*, compliance-*, aepd-*, equality-*]
discovery: [discovery-*, jtbd-*, prd-*, rules-*]
admin: [plugin-*, agent-*, profile-*, config-*]
usage_tracking: data/tool-usage.jsonl
command_metadata: .opencode/commands/*.md
skill_metadata: .opencode/skills/*/SKILL.md
agent_metadata: .opencode/agents/*.md
Integration Points
/tool-search— Explicit search activation/tool-catalog— Browse categories- NL command resolution — Implicit routing
- Session init — Pre-load Top-20
Signals
- GitHub stars
- 50
- Forks
- 12
- Last commit
- Sep 2026
ahel recommends instead
Advanced
- Catalog kind
- skill
- Gateway key
smart-routing-2- Source
- github.com/gonzalezpazmonica/savia