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Aha Studio Product Requirements

Product Summary

Aha Studio provides a query language (AQL), MCP server, and analytics platform for Aha.io product management data. It enables product managers, engineers, and AI agents to query, analyze, and manage Aha.io data through SQL-like syntax, programmatic APIs, and natural language via MCP.

Personas

Persona Description Primary Use
Product Manager Uses Aha.io daily for roadmap and idea management AQL for ad-hoc queries, reports, and bulk operations
Engineering Lead Builds integrations and automation around product data Library mode, HTTP API, MCP server for AI workflows
AI Agent Claude or other LLM assistants via MCP Natural language product management through 40+ MCP tools
Data Analyst Analyzes product signals and trends SQLite offline queries, Excel export, graph analytics

Use Cases

Query and Reporting

  • Execute SQL-like queries against Aha.io data (features, ideas, releases, epics, goals, initiatives, requirements)
  • Aggregate and group data (COUNT, SUM, AVG, MIN, MAX with GROUP BY/HAVING)
  • Join related entities (features with releases, ideas with features)
  • Export results in multiple formats (table, JSON, CSV, YAML, Markdown, HTML, Excel)

AI-Assisted Product Management

  • AI agents query and manage Aha.io data via MCP tools
  • Natural language to AQL translation
  • Full CRUD operations on features, ideas, releases, epics, goals, initiatives, requirements, and comments
  • Workflow status management and user assignment
  • Strategic model management

Offline Analysis

  • Sync Aha.io data to local SQLite database
  • Full-text search across all entities
  • Incremental sync with change tracking
  • Hybrid query modes (live API, offline cache, or prefer-cache)

Graph Analytics

  • Feature dependency analysis via Neo4j
  • Release dependency mapping
  • Initiative impact assessment
  • Cross-entity relationship exploration

OmniSignal Integration

  • Map Aha Ideas to OmniSignal enhancement signals
  • Normalize Aha-specific fields (votes, categories, custom fields) into vendor-neutral signal metrics
  • Enable frustration scoring (votes x age) across Aha and non-Aha sources

Functional Requirements

AQL Engine

  • Full SELECT/FROM/WHERE/ORDER BY/LIMIT/GROUP BY/HAVING/JOIN syntax
  • INSERT/UPDATE/DELETE mutations with dry-run and confirmation
  • Subqueries (scalar and list)
  • DISTINCT, aliases, and aggregate functions
  • Custom field queries via custom.fieldname syntax
  • Tags as a derived entity with usage counts

MCP Server

  • 40+ tools covering all major Aha.io entity types
  • Lookup/reference tools for resolving names to IDs
  • Comment management across features, ideas, and epics
  • Custom field definitions and options listing
  • OmniSkill-based skill registration with stdio and HTTP transport

Interactive Experience

  • REPL with tab completion, syntax highlighting, and query history
  • Saved queries in configuration file
  • Configuration profiles for multiple Aha.io accounts

HTTP API

  • REST endpoints for AQL queries, sync, filters, search, and graph analytics
  • CORS and API key authentication middleware
  • Query mode selection per request
  • Background sync scheduling

Data Management

  • SQLite sync with schema migrations
  • FTS5 full-text search
  • In-memory LRU cache with TTL
  • Neo4j graph sync and Cypher query support

Non-Functional Requirements

  • Pure Go SQLite driver (no CGo dependency)
  • Concurrent API pagination and JOIN fetches
  • Thread-safe cache operations
  • CLI commands follow Cobra conventions
  • Go module at github.com/grokify/aha-studio