goal-to-prototype

Step 0 — Context Loading

Load user personas and company profile

Read and load the following context files:

• Load references/personas.md
• Load references/company-profile.md

Load market landscape and competitive intel

Read and load the following context files:

• Load references/market-landscape.md

Also fetch data from:

• Fetch https://api.example.com/market-data

Parse the user's goal statement into structured requirements: target audience, problem space, desired outcome, success metrics, and constraints

Parse the user's goal statement into structured requirements: target audience, problem space, desired outcome, success metrics, and constraints

Step 1 — Data Acquisition

Launch parallel research agents to gather data simultaneously (parallel)

Run the following tasks simultaneously in parallel:

Web Research Agent

Search the web for recent articles, papers, and discussions related to the problem space. Fetch at least 10 high-quality sources. Use WebSearch and WebFetch tools.

Competitor Analysis Agent

Identify top 5-10 competitors in the space. For each, analyze: product offering, pricing, strengths, weaknesses, market share. Use WebSearch to find competitor data.

User Research Agent

Cross-reference the loaded personas against the problem space. Identify pain points, unmet needs, willingness to pay, and adoption barriers. Load references/personas.md for context.

Market Trend Agent

Analyze market trends, growth trajectories, regulatory changes, and technology shifts that could impact the opportunity. Use WebSearch for current data.

Step 2 — Signal Evaluation

Synthesize all research outputs into a unified intelligence brief

Read all outputs and synthesize them with weighted importance.

Compute signal quality metrics from the merged research:

• market_signal: strength of market opportunity (0-1)
• competitive_gap: size of unserved niche (0-1)
• user_demand: evidence of user pull (0-1)
• feasibility: technical buildability (0-1)
• confidence: data quality and coverage (0-1)

Compute signal quality metrics from the merged research:

• market_signal: strength of market opportunity (0-1)
• competitive_gap: size of unserved niche (0-1)
• user_demand: evidence of user pull (0-1)
• feasibility: technical buildability (0-1)
• confidence: data quality and coverage (0-1)

Verify signal strength before investing in deep analysis

Check whether the following criteria are met before proceeding:

• confidence: >= 0.6
• market_signal: >= 0.5
• user_demand: >= 0.4

If any criterion fails, retry up to 3 times. On each retry, analyze what went wrong and adjust the approach.

Step 3 — Multi-Angle Analysis

Analyze the opportunity from multiple angles in parallel (parallel)

Run the following tasks simultaneously in parallel:

Technical Feasibility Assessment

Evaluate: tech stack options, build complexity, infrastructure needs, MVP scope, time-to-prototype. Score feasibility 0-1.

Market Viability Assessment

Evaluate: TAM/SAM/SOM, go-to-market strategy, pricing model, distribution channels, competitive moat. Score viability 0-1.

User Desirability Assessment

Evaluate: user journey, pain-point alignment, switching cost, value proposition clarity, retention hooks. Score desirability 0-1.

Step 4 — Synthesis

Converge all perspective assessments into a unified opportunity score

Read all outputs and synthesize them with weighted importance.

Gate on overall opportunity quality before prototyping

Check whether the following criteria are met before proceeding:

• opportunity_score: >= 0.7
• feasibility: >= 0.6

If criteria pass → proceed to next step. If criteria fail → "deep-research-loop" → route to remediation.

Generate a structured product brief with: problem statement, target user, value proposition, key features, success metrics, risks, and mitigations

Generate a structured product brief with: problem statement, target user, value proposition, key features, success metrics, risks, and mitigations

Apply RALPH methodology to strengthen weak signals

Apply the RALPH methodology (up to 5 iterations):

1. Reflect on which signals are weak and why
2. Analyze gaps in the research — what data is missing?
3. Learn from competitor approaches — what are they doing right?
4. Plan targeted research to fill specific gaps
5. Hypothesize an improved positioning and re-score

Exit when all criteria are met:

• opportunity_score: >= 0.7
• confidence: >= 0.8

Validate the output against criteria after each iteration. Fix failures before proceeding.

Step 5 — Prototype Generation

Generate the Product Requirements Document

Save to the following output files:

• Write to output/prd.md

Generate low-fidelity wireframes for the core user flows

Launch a general-purpose sub-agent to run in parallel with the following task:

> Generate low-fidelity wireframes for the core user flows

Tools available: Write

Load the following context before starting:

• Read output/prd.md

Generate the implementation plan with architecture, tech stack, milestones, and sprint breakdown

Launch a general-purpose sub-agent to run in parallel with the following task:

> Generate the implementation plan with architecture, tech stack, milestones, and sprint breakdown

Tools available: Write, Read

Load the following context before starting:

• Read output/prd.md

Step 6 — Final Review

Iteratively improve prototype quality

Apply the RALPH methodology (up to 3 iterations):

1. Reflect on prototype completeness — are all requirements covered?
2. Analyze coherence — do PRD, wireframes, and plan align?
3. Learn from quality gaps — what's missing or contradictory?
4. Plan specific fixes for each gap
5. Hypothesize the improved version and verify

Exit when all criteria are met:

• completeness: >= 0.9
• coherence: >= 0.9

Validate the output against criteria after each iteration. Fix failures before proceeding.

Present the complete prototype package to the user for review and approval

Ask the user to confirm before proceeding:

> Present the complete prototype package to the user for review and approval

Save the final deliverables

Save to the following output files:

• Write to output/prd.md
• Write to output/wireframes.md
• Write to output/implementation-plan.md
• Write to output/research-brief.md

Troubleshooting

If something goes wrong during execution, check these common issues:

Tool access issues: Ensure the following tools are available: Read, Write

Missing files: Ensure these files exist before running:

• output/implementation-plan.md
• output/prd.md
• output/research-brief.md
• output/wireframes.md
• references/company-profile.md
• references/market-landscape.md
• references/personas.md

References

• output/implementation-plan.md
• output/prd.md
• output/research-brief.md
• output/wireframes.md
• references/company-profile.md
• references/market-landscape.md
• references/personas.md