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Found 514 Skills
Review and improve HelixDB query performance and query shape. Use when the task is to optimize a slow Helix query, improve anchor choice, tighten index usage, reduce traversal breadth, slim projections, fix BM25 or vector search scope, or decide between stored and dynamic routes.
Corporate event opportunity scanner for A-share companies via Longbridge — identifies and analyses events that may create pricing dislocations: M&A / restructuring (asset injection / reverse merger), major shareholder increases / buybacks (positive signal), equity incentive plans (management alignment), index inclusion / exclusion (forced passive flows), and lockup expiry (potential selling pressure). Provides historical statistical patterns and trading window recommendations per event type. Triggers: "捕捉机会", "事件机会", "并购重组机会", "增持机会", "回购信号", "指数调整机会", "解禁压力", "事件套利", "捕捉機會", "事件機會", "並購重組機會", "增持機會", "回購信號", "指數調整機會", "解禁壓力", "event opportunity", "corporate event", "M&A opportunity", "buyback signal", "index inclusion", "lockup expiry", "event catalyst", "special situation", "event-driven".
Event-driven investment strategy — identify and analyse corporate events (M&A, spinoffs, buybacks, index rebalancing, lockup expiry) that create pricing dislocations. Framework: event identification → sentiment scoring → historical price reaction → position sizing. Uses Longbridge news / filings / calendar data as signal inputs. Triggers: "事件驱动", "并购套利", "指数调整", "解禁套利", "事件策略", "公司事件策略", "事件投资", "套利机会", "事件驅動", "並購套利", "指數調整", "解禁套利", "事件策略", "公司事件策略", "event-driven", "event strategy", "merger arbitrage", "index rebalancing", "lockup expiry", "event investing", "corporate event trading", "special situation", "spinoff", "buyback catalyst".
UX critique — hierarchy, clarity, anti-slop. No code changes unless asked. Invoke when the user asks for critique on their UI, or mentions 'critique' alongside design / UI / frontend work.
Landscape evolution and surface process modelling in Python. Build 2D numerical models for erosion, hydrology, soil transport, and geomorphology. Use when Claude needs to: (1) Model landscape evolution over time, (2) Simulate river/stream erosion, (3) Route water flow across terrain, (4) Model hillslope diffusion processes, (5) Simulate weathering and soil production, (6) Analyze drainage networks, (7) Combine multiple geomorphic processes, (8) Load/save DEM data for modeling.
Automate Google Calendar events, scheduling, availability checks, and attendee management via Rube MCP (Composio). Create events, find free slots, manage attendees, and list calendars programmatically.
Optimize MATLAB code for better performance through vectorization, memory management, and profiling. Use when user requests optimization, mentions slow code, performance issues, speed improvements, or asks to make code faster or more efficient.
Use when loading all data upfront. Use when initial page load is slow. Use when fetching data that might not be needed.
Edit existing videos with AI using each::sense. Apply effects, color grading, speed changes, trimming, transitions, style transfer, and visual enhancements. Transform raw footage into polished content. Use for: color grading, speed ramping, style transfer, video enhancement, social media edits, content post-production. Triggers: edit video, video editing, color grade, speed change, video effects, trim video, video filter, slow motion, timelapse, video style, video enhance, post production
Guides CI/CD for agent skills repositories and skill packages—pipeline design (build, test, validate, package), GitHub Actions for PR checks and release promotion, environment gates, secrets hygiene (no secrets in repo), skill-creator integration (quick_validate.py, package_skill.py), .skill artifact strategy, rollback, and operational runbooks for skill releases. Use when the user mentions CI/CD, CI/CD engineer, pipeline design, GitHub Actions, skill validation CI, package skills, release pipeline, deploy skills, PR checks, continuous integration, or skill release workflow—not application-only CI without skill packaging (devops), pre-flight plan go/no-go (build-validator), IDP or golden paths (platform-engineer), org-wide SLO and error-budget programs without pipeline ownership (site-reliability-engineer), or portfolio catalog governance without pipeline YAML (ai-skill-manager).
Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding, incident handoff, customer-onboarding, claims adjudication) in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time. Pairs Lean / Six Sigma / Theory-of-Constraints canon with deterministic stdlib-only Python tools to produce a process map, a ranked bottleneck list (with severity + root-cause hypothesis), and a cycle-time analysis (P50, P90, value-add ratio, Little's-Law throughput). Distinct from sales-pipeline, system-reliability (SLO), and strategic-OKR work — this is tactical process documentation for internal operations.
Expert at diagnosing and fixing performance bottlenecks across the stack. Covers Core Web Vitals, database optimization, caching strategies, bundle optimization, and performance monitoring. Knows when to measure vs optimize. Use when "slow page load, performance optimization, core web vitals, bundle size, lighthouse score, database slow, memory leak, optimize performance, speed up, reduce load time, performance, optimization, core-web-vitals, caching, profiling, bundle-size, database" mentioned.