Adaptive Pricing Discovery Skill

Adaptive Pricing Discovery

Resumable AI pipeline: idea context → analyze strength → generate/approve hypotheses → compile schema → produce tiered pricing.

State Machine

Strong Route (context score = strong):
S0_NORMALIZE → S1_ANALYZE → S2A_SYNTHESIZE → S3_COMPILE → S4_IDEATION → COMPLETED

Weak/Medium Route (hypothesis-driven with user feedback):
S0 → S1 → S2B1_VALUE → U1 [user picks] → S2B2_BUYER → U2 [user picks] → S2B3_MARKET → U3 [user picks] → S3 → S4 → COMPLETED

Rejection fallback (at U1/U2):
→ ASK_MINIMUM [user provides text] → S3 → S4 → COMPLETED

Statuses: running | awaiting_user | completed | failed

Pause points: U1 (value hypotheses), U2 (buyer hypotheses), U3 (market anchors), ASK_MINIMUM

Key Files

Edge Function

| File | Purpose | |------|---------| | supabase/functions/pricing-discovery/index.ts | State machine, orchestrator calls, DB state, resumption |

Types

| File | Purpose | |------|---------| | apps/idea-machina/src/types/pricing.ts | PricingInputSchemaV1, PricingResult, PricingRun, step types |

Components

| Component | File | Purpose | |-----------|------|---------| | PricingDiscoveryDialog | components/PricingDiscoveryDialog.tsx | Main dialog: states (idle/loading/u_step/ask_minimum/completed/failed) | | PricingOptionCard | components/pricing/PricingOptionCard.tsx | Choice card with checkbox/radio + confidence badge | | PricingResultView | components/pricing/PricingResultView.tsx | Final result: tiers, sanity, stress test, warnings |

Service Layer

| File | Functions | |------|-----------| | lib/ideas.ts | startPricingDiscovery(ideaId), resumePricingDiscovery(runId, action, selections) | | lib/aiContext.ts | pricing_discovery as AiPhaseType | | lib/pipelineStatus.ts | "pricing" chip in status bar |

Database

| Migration | Purpose | |-----------|---------| | 20260211000000_pricing_discovery_run_table.sql | ai_prompt.pm_pricing_discovery_runs table + RLS | | 20260211000100_pricing_discovery_features.sql | 8 AI features + quotas + operations | | 20260211000200_pricing_discovery_prompts.sql | All prompt templates (S0-S4, U1-U3) |

DB Table: `ai_prompt.pm_pricing_discovery_runs`

| Column | Type | Notes | |--------|------|-------| | id | uuid | PK | | idea_id | uuid | FK pm_ideas | | current_step | text | S0→S4, U1-U3, ASK_MINIMUM, COMPLETED | | status | text | running, awaiting_user, completed, failed | | step_results | jsonb | Intermediate outputs per step | | approvals | jsonb | User decisions at approval points | | pricing_schema | jsonb | PricingInputSchemaV1 (from S3) | | pricing_result | jsonb | Final output (from S4) | | route | text | strong or medium_weak | | total_tokens_used | int | | | total_cost_usd | numeric | | | error_message | text | If failed | | created_by | uuid | User |

AI Features (8 steps)

| Feature Key | Step | Model | |-------------|------|-------| | pricing_s0_normalize | Ingest & normalize | Sonnet 4.5 | | pricing_s1_analyze | Context strength | Sonnet 4.5 | | pricing_s2a_synthesize | Full-context (strong) | Sonnet 4.5 | | pricing_s2b1_value | Value hypotheses | Sonnet 4.5 | | pricing_s2b2_buyer | Buyer hypotheses | Sonnet 4.5 | | pricing_s2b3_market | Market anchors | Sonnet 4.5 | | pricing_s3_compile | Schema compilation | Sonnet 4.5 | | pricing_s4_ideation | Final pricing | Sonnet 4.5 |

Edge Function API

Start: { mode: "start", idea_id } → runs S0→S1→(route)→pause or complete

Resume: { mode: "resume", run_id, action, selections? } where action = approve|reject|skip|minimum_answers

Response: { success, run_id, status, current_step, options?, result?, pricing_schema?, usage }

PricingInputSchemaV1 (key fields)

value_definition: { core_value_proposition, value_type, value_levers, perceived_uniqueness }
tier_intents: [{ tier_name, target_segment, positioning, key_features }]
buyer_context: { buyer_type, payer_types, budget_sensitivity, purchase_type }
market_anchors: { reference_products[], psychological_alternatives[] }
stress_test_inputs: { churn_scenario, price_elasticity_guess, volume_assumption }

Common Patterns

Add new step to pipeline

Add step constant to edge function step enum
Add prompt template migration with ai_prompt.prompts + ai_prompt.prompt_versions
Register AI feature + quota in bible_schema.ai_features + ai_plan_quotas
Add step logic in edge function state machine (after which step, pause or auto-continue)
Update progress percentage mapping in PricingDiscoveryDialog
Add types for step output in types/pricing.ts

Modify prompt template

Find prompt by feature_key in ai_prompt.prompts
Create new prompt_versions row (keep old version for rollback)
Update ai_prompt.ai_feature_bindings if changing model/vendor
Test via edge function (start a new pricing run)

Modify dialog UI at a U-step

PricingDiscoveryDialog.tsx — handles step rendering logic
PricingOptionCard.tsx — individual choice card
Step data comes from edge function options field in response
User selection sent back via resumePricingDiscovery(runId, action, selections)

Debug a stuck/failed run

Query: SELECT * FROM ai_prompt.pm_pricing_discovery_runs WHERE id = '<run_id>'
Check status, current_step, error_message
Check step_results jsonb for partial outputs
Edge function logs: check pricing-discovery in Supabase logs

References

Full schema details: See references/schema.md (pricing runs table, AI features, prompts)
Parent skill: idea-machina for general Idea Machina development

Agent Skills: Adaptive Pricing Discovery

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