Ai skills

This skill connects to any MCP server on demand, loading tool schemas only when needed to keep context lean.

This skill performs comprehensive technical SEO audits and optimizations to boost Core Web Vitals, on-page SEO, and GEO visibility for AI search engines.

This skill helps bootstrap SaaS founders set up clean books, stay tax-ready, and automate finances with simple, practical steps.

This skill helps bootstrapped SaaS founders add AI-powered features by choosing simple, cost-effective APIs and practical prompts.

This skill helps bootstrapped SaaS founders reduce churn and maximize lifetime value through onboarding, value delivery, and win back strategies.

This skill helps you build features with AI coding tools, guiding tool selection, prompting strategies, and iterative development workflows.

This skill helps solo founders build a clear SaaS financial model by calculating unit economics, churn, CAC, LTV and runway on a single editable spreadsheet.

This skill helps you uncover customer needs and build actionable JTBD driven personas to inform product decisions and prioritization.

This skill evaluates ML research papers following ICML guidelines, providing comprehensive, literature-grounded feedback across claims, methods, experiments,

This skill guides you through tree-based research cycles as an AI co-scientist, ensuring hypothesis-driven, reproducible experiments across domains.

This skill creates context checkpoints to preserve conversation state before breaks or risky changes, enabling seamless restoration later.

This skill clears conversation context while preserving knowledge via a context marker, enabling seamless task switching without losing progress.

This skill helps you estimate Tinker fine-tuning costs by tokenizing datasets with the correct tokenizer and applying model-specific pricing.

This skill creates reusable Standard Operating Procedures from solving novel issues, guiding pattern establishment, and documenting workflows for future reuse.

This skill displays and toggles Navigator features, helping you tailor your setup and optimize your workflow.

This skill critiques ML conference papers in reviewer style, helping you anticipate concerns, identify weaknesses, and fill claim-evidence gaps.

This skill creates and manages Navigator task documentation, generating implementation plans and archiving completed work to keep project records up to date.

This skill guides ideation and implementation of neuro-symbolic reasoning, combining LLMs with symbolic solvers to design experiments or integrate solvers.

This skill conducts a literature review and crafts a CS research proposal by identifying assumptions, proposing alternatives, and outlining testable validation.

This skill simplifies recently modified Python code to improve clarity and maintainability without changing behavior.

This skill automates design review, token extraction, and implementation planning from Figma, slashing handoff time by hours and boosting accuracy.