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Use this skill to validate the "why" before building, run product diagnostics, and convert vague ideas into specs.
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Basado en la clasificación ocupacional SOC
Head-to-head comparison of coding agents (Gemini Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics
Add x402 payment execution to AI agents — per-task budgets, spending controls, and non-custodial wallets via MCP tools. Use when agents need to pay for APIs, services, or other agents.
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
Capture architectural decisions made during Gemini Code sessions as structured ADRs. Auto-detects decision moments, records context, alternatives considered, and rationale. Maintains an ADR log so future developers understand why the codebase is shaped the way it is.
Patterns and architectures for autonomous Gemini Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Turn a one-line objective into a step-by-step construction plan for multi-session, multi-agent engineering projects. Each step has a self-contained context brief so a fresh agent can execute it cold. Includes adversarial review gate, dependency graph, parallel step detection, anti-pattern catalog, and plan mutation protocol. TRIGGER when: user requests a plan, blueprint, or roadmap for a complex multi-PR task, or describes work that needs multiple sessions. DO NOT TRIGGER when: task is completable in a single PR or fewer than 3 tool calls, or user says "just do it".
| name | product-lens |
| description | Use this skill to validate the "why" before building, run product diagnostics, and convert vague ideas into specs. |
| origin | ECC |
Like YC office hours but automated. Asks the hard questions:
1. Who is this for? (specific person, not "developers")
2. What's the pain? (quantify: how often, how bad, what do they do today?)
3. Why now? (what changed that makes this possible/necessary?)
4. What's the 10-star version? (if money/time were unlimited)
5. What's the MVP? (smallest thing that proves the thesis)
6. What's the anti-goal? (what are you explicitly NOT building?)
7. How do you know it's working? (metric, not vibes)
Output: a PRODUCT-BRIEF.md with answers, risks, and a go/no-go recommendation.
Reviews your current project through a founder lens:
1. Read README, GEMINI.md, package.json, recent commits
2. Infer: what is this trying to be?
3. Score: product-market fit signals (0-10)
- Usage growth trajectory
- Retention indicators (repeat contributors, return users)
- Revenue signals (pricing page, billing code, Stripe integration)
- Competitive moat (what's hard to copy?)
4. Identify: the one thing that would 10x this
5. Flag: things you're building that don't matter
Maps the actual user experience:
1. Clone/install the product as a new user
2. Document every friction point (confusing steps, errors, missing docs)
3. Time each step
4. Compare to competitor onboarding
5. Score: time-to-value (how long until the user gets their first win?)
6. Recommend: top 3 fixes for onboarding
When you have 10 ideas and need to pick 2:
1. List all candidate features
2. Score each on: impact (1-5) × confidence (1-5) ÷ effort (1-5)
3. Rank by ICE score
4. Apply constraints: runway, team size, dependencies
5. Output: prioritized roadmap with rationale
All modes output actionable docs, not essays. Every recommendation has a specific next step.
Pair with:
/browser-qa to verify the user journey audit findings/design-system audit for visual polish assessment/canary-watch for post-launch monitoring