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Async Python Patterns workflow skill. Use this skill when the user needs Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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A strict code reviewer, pair programmer, debugger, and mentor for Python, Bash, Google Apps Script, JavaScript, and Swift/Apple platforms. Use when writing, reviewing, debugging, planning, or securing code, or for senior-level rigor, a security review, or mentoring. Mode triggers — REVIEW: (critique + refactor), EXPLAIN: (teach), MVP:/PROTOTYPE: (lean-but-safe), DEBUG: (root-cause), AUDIT: (report-first); default is pair-programming. Drives a spec→plan→TDD→verify loop with a deterministic-first, verify-before-asserting (anti-hallucination) discipline. Enforces a security floor (secrets, injection, input validation, isolation, least privilege, authn) and a backup/continuity floor on a phase-aware rigor ladder (Prototype→MVP→Production) — cheap ≠ insecure. Covers testing & fuzzing, SAST/secret-scan/type-check/supply-chain gates, multi-tenant data protection, resilience & DR, scalability, CI/CD, cloud/containers/DBs, and accessible UI — deep references read on demand.
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Searches current documentation, release notes, API references and public repository issues for libraries, frameworks, SDKs, APIs and CLI tools with `firecrawl developer`. Use before answering when the user names a version, is upgrading, pastes an error from a library or tool, or asks how to use, configure or migrate a specific library or API. Model knowledge stops at a training cutoff and misses new releases, renamed APIs, changed defaults and recent fixes, so when a version, option, error or API is unfamiliar or may have changed, look it up instead of guessing. Also checks whether a bug was fixed and in which release. Not for general programming concepts, code that uses no specific library, or refactoring code the user supplied.
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Solving finite-horizon LQR via dynamic programming for MPC.
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Use this skill on every programming task — writing code, fixing bugs, refactoring, explaining code, running tools, or answering technical questions. Apply token-saving and quality-preserving practices throughout. Activate even when the user doesn't explicitly ask for efficiency — this skill is always relevant for software development work. Do not skip this skill for "simple" tasks; the rules apply at every scale.
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Review common AI slops of defensive programming patterns, avoid silent errors. TRIGGER when reviewing code for defensive anti-patterns, writing fail-fast code, or auditing error handling quality.
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Search an index of public repositories, GitHub issues, merged pull requests, repository READMEs, and curated documentation sites. Use when a programming question needs external documentation or upstream evidence.
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Expert Go programming skill authored by spf13 (former Go team lead, author of Cobra, Viper, Hugo, Afero). Covers idiomatic Go — package design, error handling, interfaces, concurrency, testing, and project layout, current through Go 1.27. Use whenever Go code is written, reviewed, debugged, or refactored — any .go file, go.mod, CLI tool, or web service, and whenever the user mentions Go or golang, even if they don't ask for "idiomatic" code.
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Implementing robust business logic, API integrations, data models, and reproducible AI image-generation code with type safety. Use for production implementation, Gemini image API pipelines, or interactive pair programming.
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Real-world problem formulation, mathematical abstraction, and applied mathematics for translating between practical problems and mathematical frameworks. Covers the modeling cycle (problem identification, assumptions, formulation, analysis, validation, interpretation), Polya's framework adapted for modeling, common model types (linear, exponential, logistic, periodic, power-law), dimensional analysis (Buckingham Pi theorem), optimization (linear programming, gradient descent, constraint satisfaction), probability models (Markov chains, queuing theory, Monte Carlo simulation), statistical modeling (regression, hypothesis testing, model selection), model criticism (overfitting, underfitting, sensitivity analysis), and real-world case studies. Use when formulating mathematical models, performing dimensional analysis, optimizing systems, running simulations, or evaluating model validity.
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Computational thinking as a problem-solving discipline independent of programming languages. Covers the four pillars (decomposition, pattern recognition, abstraction, algorithm design), computational problem-solving methodology (understand, decompose, generalize, formalize, verify), abstraction levels (from hardware through user interface), modeling and simulation, automata and formal languages (DFA, NFA, regular expressions, context-free grammars, Turing machines), computational complexity classes (P, NP, NP-complete, undecidable), and constructionist pedagogy (learning by building, Logo, Scratch, physical computing). Use when approaching unfamiliar problems, teaching problem-solving strategies, analyzing problem complexity, or bridging between domain knowledge and computational solutions.
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Algorithms and data structures from first principles through advanced analysis. Covers sorting (bubble, insertion, selection, merge, quick, heap, radix), searching (linear, binary, BFS, DFS, Dijkstra, A*), fundamental data structures (arrays, linked lists, stacks, queues, hash tables, trees, heaps, graphs, tries), complexity analysis (Big-O, Big-Omega, Big-Theta, amortized), recurrence relations, and algorithm design paradigms (divide-and-conquer, greedy, dynamic programming, backtracking). Use when analyzing, selecting, implementing, or comparing algorithms and data structures.
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Foundational skills for Zephyr RTOS development. Covers essential Embedded C patterns (BIT, CONTAINER_OF), real-time concurrency primitives (mutexes, semaphores, spinlocks), hardware literacy (datasheet-to-DTS mapping), and defensive programming. Trigger when writing core application logic, drivers, or troubleshooting foundational behavior.
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Detects timing side-channel vulnerabilities in cryptographic code. Use when implementing or reviewing crypto code, encountering division on secrets, secret-dependent branches, or constant-time programming questions in C, C++, Go, Rust, Swift, Java, Kotlin, C#, PHP, JavaScript, TypeScript, Python, or Ruby.
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Forth/Factor/Joy: stack-based concatenative programming where composition replaces application.
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Hedges' 4-kind lattice for bidirectional programming - covariant/contravariant/invariant/bivariant types with GF(3) correspondence
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Write modern, high-performance C# code using records, pattern matching, value objects, async/await, Span<T>/Memory<T>, and best-practice API design patterns. Emphasizes functional-style programming with C# 12+ features.
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Reference for advanced data structure patterns used in competitive programming and technical interviews. Covers heaps, monotonic stacks, tries, segment trees, Fenwick trees, stack-based parsing, and ordered sets with Python templates, recognition signals, and edge case guidance.
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Reference for dynamic programming patterns — recognition signals, constraint mapping, Python templates, edge cases, and common mistakes for 8 core DP techniques
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Develop a gas chromatography method from scratch: define analytical objectives, select column chemistry, optimize temperature programming, choose carrier gas and detector, and validate initial system performance for target analytes in a given matrix.
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Apply the fail-early (fail-fast) pattern to detect and report errors at the earliest possible point. Covers input validation with guard clauses, meaningful error messages, assertion functions, and anti-patterns that silently swallow failures. Primary examples in R with general/polyglot guidance. Use when writing functions that accept external input, adding input validation before CRAN submission, refactoring code that silently produces wrong results, reviewing PRs for error-handling quality, or hardening internal APIs against invalid arguments.
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Rust programming expert including ownership, borrowing, lifetimes, async Tokio patterns, error handling, trait system, performance optimization, testing, and production systems development
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Elixir and Phoenix expert including OTP, Ecto, and functional programming
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Go programming expert including APIs, gRPC, concurrency, and best practices
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