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Found 92 Skills
Use when designing software architecture for bioinformatics pipelines, defining data structures, planning scalability, or making technical design decisions for complex systems.
Create critical process briefs through challenging dialogue that exposes operational blind spots and stress-tests workflows. Use when user wants to map out business processes, operations, or workflows. Proactively finds gaps, exposes hidden complexity, identifies fragile points, and tests scalability. Creates structured process briefs in .ideas/[name]/process.md. Triggers include "how would this work operationally", "what's the process", "how do we deliver", or operational details questions.
Use when planning system architecture to ensure nothing is missed. Provides structured questions covering scalability, security, data, and operational dimensions before implementation.
Implement database sharding for horizontal scalability. Use when scaling large databases, distributing data across multiple servers, or designing sharded architectures.
Analyzes technical systems and problems through engineering lens using first principles, systems thinking, design methodologies, and optimization frameworks. Provides insights on feasibility, performance, reliability, scalability, and trade-offs. Use when: System design, technical feasibility, optimization, failure analysis, performance issues. Evaluates: Requirements, constraints, trade-offs, efficiency, robustness, maintainability.
Build and operate Turborepo monorepos with deterministic task graphs, cache correctness, and CI scalability. Use for `turbo.json` design, task dependency modeling, outputs/inputs hashing, environment variable handling, remote cache rollout, and pipeline troubleshooting.
Analyzes events through computer science lens using computational complexity, algorithms, data structures, systems architecture, information theory, and software engineering principles to evaluate feasibility, scalability, security. Provides insights on algorithmic efficiency, system design, computational limits, data management, and technical trade-offs. Use when: Technology evaluation, system architecture, algorithm design, scalability analysis, security assessment. Evaluates: Computational complexity, algorithmic efficiency, system architecture, scalability, data integrity, security.
Analyze unit economics to evaluate per-unit profitability and business model scalability. Use this skill when the user needs to assess whether each transaction, customer, or product unit is profitable, evaluate startup viability, or optimize contribution margins — even if they say 'does our business model work', 'what's our margin per order', or 'can we scale profitably'.
Use when the user needs system design, architecture decision records, scalability analysis, trade-off evaluation, or non-functional requirements planning. Triggers: new system design, technology selection, scaling strategy, ADR creation, infrastructure topology, service boundary definition.
Produce a Platform & Infrastructure Improvement Pack (shared capabilities plan, reliability/performance/privacy targets, scaling triggers, analytics + discoverability decisions, execution roadmap). Use for platform engineering, infrastructure planning, scalability, reliability, and architecture foundations.
Analyze candidate algorithms for time/space complexity, scalability limits, and resource-budget fit (CPU, memory, I/O, concurrency). Use when feasibility depends on input growth or latency/memory constraints and quantitative bounds are required before implementation; do not use for persistence schema or deployment topology decisions.
Optimize application performance for speed, efficiency, and scalability. Use when improving page load times, reducing bundle size, optimizing database queries, or fixing performance bottlenecks. Handles React optimization, lazy loading, caching, code splitting, and profiling.