OpenGlad

The primary friction tool. Use this FIRST when a user shares a new startup idea or business concept. Executes the full pipeline: Pattern Scan + Loss Simulation + Revenue Gate + Micro-Correction. Fetches real-time market intelligence from Reddit, HackerNews, GitHub, and Polymarket for multi-source grounding. Returns a comprehensive reality check — present the full output to the user without summarizing.

Detects behavioral antipatterns: overbuilding drift, monetization avoidance, prestige bias, idea hopping. Use this when the user is talking ABOUT their approach, mindset, or decision-making — not presenting a new idea. Does NOT search external sources. For new ideas, use run_the_bet instead.

Simulates 3 failure scenarios (Best/Likely/Worst) for an idea with quantified expected loss in hours and money. Fetches multi-source market data (Reddit, HN, GitHub, Polymarket) to ground predictions in real signals. Use this when the user wants to understand the RISK of an idea without the full run_the_bet pipeline.

Locks the build phase and produces 2-3 specific monetization unlock tasks the user must complete before writing code. Use this when the user is eager to start building but hasn't validated willingness-to-pay. Does NOT search external sources — purely behavioral.

Friction-focused market analysis: detects overcrowding, tarpit ideas, late entry risk, and failure rate signals. Sources: Reddit, HackerNews, GitHub (competitor repos), and Polymarket prediction markets. Use this when the user asks about market timing, competition, or whether their space is saturated.

Broad multi-source trend scanner for any topic. Returns sentiment, red flags, cautionary tales, and a 6-12 month prediction using data from Reddit, HackerNews, GitHub, and Polymarket. Use this for general market research when the user asks "what's happening with X" or wants to explore a space before committing.

Comparative friction analysis for 2-3 startup ideas side-by-side. Fetches multi-source market intelligence for each idea in parallel (Reddit, HackerNews, GitHub, Polymarket), then produces a ranked comparison with gate statuses and a single verdict on which idea (if any) is worth pursuing. Use this when the user is deciding between multiple directions.

Smart triage router — the best starting point when unsure which tool to use. Pass the user's raw input and it auto-detects: ideas get routed to run_the_bet (with Reddit data), metrics/JSON get routed to the appropriate diagnostic. Set type to override auto-detection.

Analyzes engineering metrics (commit frequency, deploy failure rate, tech debt) and produces an Execution Stability Score (1-100). Use when the user provides development/repo activity data as JSON.

Analyzes financial metrics (MRR/ARR, churn, CAC/LTV, burn rate) and produces a Revenue Health Score (1-100). Use when the user provides financial data as JSON.

Analyzes team activity signals (work hours, context-switching, recovery) and produces a Burnout Risk Score (1-100). Use when the user provides team workload data as JSON.

Analyzes marketing/growth metrics (channel health, funnel, organic vs paid) and produces a Distribution Discipline Score (1-100). Use when the user provides marketing data as JSON.

Comprehensive system scan across all dimensions: Execution, Revenue, Burnout, and Distribution. Produces an Overall Health Score (1-100) with failure scenario predictions. Use this when the user provides complete startup telemetry covering multiple areas, or when they want a holistic view.