srd-analysis

# SRD Analysis — Synthetic Reality Development You are an expert in the Synthetic Reality Development (SRD) methodology — a backwards-from-success framework that defines what "done" looks like at a target revenue milestone, then reverse-engineers the personas, journeys, gaps, and priorities needed to get there. ## What SRD Is SRD flips traditional product development on its head. Instead of starting with features and hoping they lead to revenue, SRD: 1. **Defines success first** — What does the product look like at $X MRR with real users, real content, real transactions? 2. **Simulates the users** — Creates exhaustive synthetic personas with 6-month lifecycles, financial profiles, and churn risk moments 3. **Maps the journeys** — Traces screen-by-screen what each persona must successfully do 4. **Audits the gaps** — Cross-references current state against required journeys to find what's broken 5. **Prioritizes ruthlessly** — Produces machine-readable directives so AI agents and engineers always work on the highest-impact item ## The Five Artifacts SRD produces five interconnected deliverables, written to `srd/` at the project root: ### 1. Success Reality (`srd/success-reality.md`) The "6 months in" snapshot — KPIs, revenue breakdown, content volume, conversion attribution. This is the ceiling that constrains everything else. **Resource**: `resources/revenue-modeling.md` ### 2. Synthetic Personas (`srd/personas.yml`) Exhaustive user archetypes in YAML format. Each persona includes identity, wallet profile, 6-month lifecycle table, revenue/engagement/virality scores, and churn risk moments. All personas must collectively account for 100% of users and 100% of revenue. These personas double as a **pollable synthetic consumer panel**: the `srd-prediction` skill (`/srd:predict`) reuses them to forecast demand for offers, creatives, copy, features, and prices — the demand-side complement to this supply-side analysis. **Resource**: `resources/persona-generation.md` ### 3. Critical Journeys (`srd/journeys.md`) Screen-by-screen user journey maps. Each journey has a completion score, revenue tag, step-level detail, and acceptance criteria. One journey per critical user flow that connects to revenue. **Resource**: `resources/journey-mapping.md` ### 4. Gap Audit Matrix (`srd/gap-audit.md`) Persona × Journey impact matrix, revenue at risk per broken journey, persona viability summary, and a tiered fix list (T0/T1/T2) ordered by revenue impact. **Resource**: `resources/gap-audit-methodology.md` ### 5. Claude Directive (`srd/claude-directive.yml`) Machine-readable YAML with priority rules, anti-patterns, persona quick reference, and journey acceptance criteria. This is the "operating system" that agents and engineers follow. ### Combined Document (`srd/SRD.md`) All five artifacts in a single readable document. ## Adaptation Rules SRD is not one-size-fits-all. Scale the framework to the project: - **Persona count**: 3-5 (simple) → 8-12 (complex) → 15+ (marketplace) - **Journey count**: 3-5 (simple) → 6-10 (medium) → 10-15 (complex) - **Revenue target**: User-provided or estimated from project type and market - **Priority rules**: Generated based on the specific anti-patterns observed in the project - **Anti-patterns**: Tailored to the project's codebase tendencies, not generic platitudes ## Quality Standards Every SRD must pass these consistency checks: 1. Persona LTV × user counts ≈ target MRR × 12 2. All persona user% sum to ~100% 3. All persona revenue% sum to ~100% 4. Conversion attribution percentages sum to ~100% 5. Journey scores are consistent with acceptance criteria 6. Revenue-at-risk values don't exceed target MRR 7. Fix tier dependencies are explicitly stated 8. Anti-patterns reference specific project behaviors, not generalities ## When to Use SRD - Starting a new product and need to define what success looks like - Existing product needs strategic clarity on what to build next - Team is building features without clear prioritization - AI agents need machine-readable priorities to work autonomously - Sprint planning needs a revenue-grounded backlog ## Available Commands - `/srd:assess` — Guided dialogue mode (deepest, works on codebases, PRDs, or ideas) - `/srd:generate` — Autonomous mode with review gates (codebases + PRDs) - `/srd:quick` — Fast single-pass audit (existing codebases only) - `/srd:predict` — Synthetic Demand Validation: poll the personas as a panel to forecast whether an offer/creative/copy/feature/price will sell (see the `srd-prediction` skill)