pantheon-ai/implementation-planner

Converts a PRD or requirements document into a structured, phased implementation plan with individual phase files and granular per-task files written to .context/plans/. Also restructures existing monolithic planning documents into digestible, hierarchical directory structures. Creates a root plan index summarising all phases, a numbered phase file per phase, and a numbered task file per task inside each phase directory.

3.25x

Quality

93%

Does it follow best practices?

Impact

91%

3.25x

Average score across 5 eval scenarios

Securityby

Passed

No known issues

Task: Create an implementation plan for a large-scale SaaS platform

Name: pantheon-ai/implementation-planner
Rating: 0.922 (1 reviews)
Author: pantheon-ai

Create a complete implementation plan for the following system.

Project: Multi-Tenant SaaS Analytics Platform

Build a production-grade multi-tenant analytics platform with the following capabilities:

Authentication & Authorisation

OAuth 2.0 / OpenID Connect with Google and GitHub providers
Role-based access control (owner, admin, analyst, viewer)
API key management for service accounts

Data Ingestion

HTTP event ingestion endpoint (100k events/sec throughput)
Kafka consumer for batch ingestion
CSV and JSON bulk import via S3
Webhook delivery system for downstream integrations

Data Pipeline

Real-time processing with Apache Flink
Hourly and daily aggregation jobs
Data quality validation layer
Schema registry integration

Storage

PostgreSQL for tenant metadata and config
ClickHouse for analytical queries
S3 for raw event archive
Redis for caching and session storage

Query Engine

SQL-over-HTTP query API
Saved queries with parameterisation
Query result caching with TTL
Export to CSV/Parquet/JSON

Visualisation

Dashboard builder with drag-and-drop layout
Chart library (line, bar, pie, funnel, cohort)
Scheduled report delivery by email
Embeddable dashboard iframes with token auth

Multi-Tenancy

Tenant provisioning and onboarding flow
Per-tenant resource limits and quota enforcement
Tenant data isolation at storage layer
Billing integration with Stripe

Operations

Kubernetes deployment with Helm charts
Observability stack (Prometheus, Grafana, Loki)
Automated database migrations
Zero-downtime deployments

Developer Experience

TypeScript SDK with full type coverage
OpenAPI specification and docs site
Sandbox environment with sample data
CLI tool for data management

Constraints

Each of the 9 sections above (Authentication, Data Ingestion, Data Pipeline, Storage, Query Engine, Visualisation, Multi-Tenancy, Operations, Developer Experience) represents a distinct delivery milestone and must be treated as a separate phase. Do not merge sections.
The stakeholder has confirmed the scope is fixed — no reduction is possible.

What to produce

Create a complete implementation plan under .context/plans/ for this project.