Skill UI

This profile establishes 'Quinn,' a collaborative AI persona designed to act as a hands-on, energetic teammate. Quinn focuses on strong technical execution, fast iteration, and generating practical, verifiable outputs. She guides the user through concrete steps, maintaining momentum, and ensuring that learning translates into actionable work.

This profile acts as a narrative and synthesis partner, focusing on articulating the 'why' behind decisions rather than just the 'what.' It specializes in creating clear, structured written artifacts, refining design notes, and synthesizing complex tradeoffs. Wiggins helps ensure that the intent aligns with the execution, adjusting the explanation level and framing to suit any mixed audience, from engineers needing mechanisms to leaders needing implications.

Master the design, debugging, and hardening of production-grade GitHub Actions CI/CD pipelines. This skill covers advanced topics including reusable workflows, matrix builds, self-hosted runners, OIDC authentication, secrets management, environment protection, and complex trigger patterns (e.g., workflow_call, schedule, release). Use this to automate complex build, test, and deployment processes.

This orchestrator dynamically manages and loads multiple specialized Go skills based on the current task context. Whether you are designing an API, debugging a panic, auditing security, or optimizing performance, it automatically combines the most relevant skills (e.g., gRPC loads testing, error handling, and core Go skills). It acts as a comprehensive guide to Go best practices and modern development patterns.

Invariant-Guard enforces a correctness-first approach to algorithm design. Instead of writing code and hoping it works, this skill mandates defining the function contract, loop invariants, termination arguments, and all potential edge cases *before* implementation. It is essential for complex algorithms where subtle bugs (like off-by-one errors or missed post-conditions) are common, ensuring mathematically rigorous and verifiable code.

This skill enforces an algorithm-first discipline, requiring the user to state the time and space complexity (Big-O), the intended data structure, and the core algorithm family before writing any complex code (loops, queries, recursion). It serves as a critical gatekeeper to prevent common performance pitfalls like O(n²) complexity, N+1 database queries, and brute-force implementation errors, significantly improving code robustness and efficiency.

LiteParse is a fast, open-source tool for local, layout-aware text extraction from PDFs, Office files, and images. It provides structured JSON output with precise bounding boxes and supports OCR, making it ideal for building robust RAG systems, citation grounding, and multimodal agents. All processing is done locally without needing cloud APIs.

This orchestrator converts complex Markdown content—such as long-form specs, code reviews, or slide decks—into a single-file, lightly-interactive HTML document. It deterministically classifies the input type (Document, Review, or Slides) and routes the content to the appropriate specialized converter sub-skill, ensuring the output retains density and structure far beyond what raw markdown can achieve.

Generates an exhaustive, executable 12-month marketing plan structured by the AARRR framework (Acquisition, Activation, Retention, Referral, Revenue). Acting as a fractional CMO, this tool tailors strategies to the client's specific budget, team capabilities, and business stage. It creates a single, actionable roadmap, complete with current-state audits and strategic recommendations, ideal for investor updates or internal team alignment.

A specialized skill for achieving asymptotic performance gains when classical algorithms are already near optimal. It leverages advanced mathematical techniques and probabilistic data structures (e.g., Bloom Filters, HyperLogLog, FFT, MinHash/LSH) to handle massive datasets (n ≥ 10⁶) by accepting bounded approximations or exploiting deep structural properties. Requires strict adherence to error parameter and complexity justification protocols.

Meta-Apply serves as the mandatory, privileged landing gate for all self-modification patches within the skill corpus. It strictly separates the 'proposal' (read-only staging) from the 'landing' (mutation). This skill requires explicit human invocation and runs a fresh, cross-model jury audit at the time of application, ensuring that no staged patch can be applied without passing stringent, real-time security and functional checks. It acts as the final, audited authority for updating the core system skills.

This skill analyzes how artificial intelligence (AI) is disrupting an industry or specific business unit. It assesses competitive exposure across 10 critical vectors (e.g., labor substitution, data moat, customer interface) and generates a detailed 90-day defensive counterstrike plan. Ideal for due diligence, strategic planning, and anticipating market shifts in AI-driven ecosystems.