ai-prompt-manager

name	ai-prompt-manager
description	Expert assistant for managing AI prompts, features, and configuration in the KR92 Bible Voice AI system. Use when creating AI prompts, configuring AI features, managing prompt versions, setting up AI bindings, or working with AI pricing and models. Supports multiple vendors and models for feature flexibility.

AI Prompt Manager

Quick Start

Core Workflow

1. Create feature → Define what AI capability is needed
2. Create prompt template → Write system/user prompts with {{variables}}
3. Create prompt version → Implement the template (allows versioning)
4. Bind to environment → Connect prompt to dev/stage/prod
5. Configure provider → Choose vendor and model
6. Test via Admin panel → Validate response and cost

For SQL patterns, see sql-patterns.md.

Database Schema (Essentials)

Table	Purpose
ai_features	Feature registry (key, description)
ai_prompt_templates	Prompt structure (task, name)
ai_prompt_versions	Prompt variants with {{variables}}
ai_prompt_bindings	Link prompt version to environment
ai_feature_bindings	Link feature to vendor/model/env
ai_pricing	Cost per vendor/model
ai_usage_logs	Track calls, tokens, cost per user

Full schema: See Docs/context/db-schema-short.md.

Prompt Design

Variable Substitution

Use {{variable}} syntax for dynamic content:

system_prompt: "You are a {{role}} assistant for Bible study."
user_prompt_template: "Analyze: {{verse_reference}}"

// At call time
await getPrompt('my_feature', {
  role: 'theological scholar',
  verse_reference: 'John 3:16'
}, 'prod');

Output Schema

Define expected output structure to validate responses:

{
  "type": "object",
  "properties": {
    "summary": {"type": "string"},
    "insights": {
      "type": "array",
      "items": {"type": "string"}
    },
    "references": {
      "type": "array",
      "items": {"type": "string"}
    }
  }
}

Temperature & Tokens

• Temperature: 0.0–0.3 (factual), 0.4–0.7 (balanced), 0.8–1.0 (creative)
• max_tokens: Set based on expected output length
  • Verse lookup: ~50 tokens
  • Short analysis: ~200 tokens
  • Full commentary: ~1000+ tokens

See providers.md for full guidance.

Vendor & Model Configuration

Vendors: lovable, openai, anthropic, openrouter

Models are vendor-specific and change over time. Always:

1. Check current availability in the API docs
2. Test in dev environment first
3. Configure pricing in ai_pricing before promoting to prod

See providers.md for selection strategy.

Environment Strategy

1. dev – Test new prompts, experiment with vendors
2. stage – Validate cost estimates, pre-production testing
3. prod – Stable, cost-optimized features

Always follow: dev → stage → prod progression.

Testing AI Features

1. Go to Admin panel → AI section → Testaus tab
2. Select feature
3. Input test variables
4. Review response, tokens, cost estimate
5. Iterate on prompt if needed

Monorepo Integration

AI features work across workspace apps:

• raamattu-nyt (main Bible app) – Uses most AI features
• widgetizer (embed service) – Limited AI features
• Edge Functions – Orchestrate calls in ai-orchestrator/

All share same bible_schema database and configuration.

Skills Handoff

• Quota/plan limits → See subscription-system skill
• Cost optimization → See performance-auditor skill
• Edge Functions → See edge-function-generator skill

References

• sql-patterns.md – Common SQL workflows
• providers.md – Vendor/model selection and parameters
• Docs/06-AI-ARCHITECTURE.md – Full system design
• Docs/context/db-schema-short.md – Database schema details
• Docs/context/supabase-map.md – Edge Functions & access matrix