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Found 551 Skills
Top Rank Tokens Sniper v1.0 — OKX Ranking Sniper (Real Trading). Monitors the OKX leaderboard for newly listed tokens, filters through 13 Slot Guard pre-checks + 9 Advanced Safety checks + 3 Holder Risk checks + Momentum scoring, then automatically snipes entries. 6-layer exit system manages take profit and stop loss. Triggered when the user mentions top rank tokens sniper, ranking strategy, leaderboard sniper, top N sniper, 榜单狙击手, or start ranking sniper. Run file: ranking_sniper.py (includes Web Dashboard http://localhost:3244)
Use when configuring tsconfig, resolving TypeScript compiler errors, debugging slow type-checking or builds, fixing module resolution and ESM/CJS issues, auditing or hardening type strictness in an existing codebase, migrating JavaScript to TypeScript, migrating compiler major versions such as TypeScript 7, or setting up type-checking in monorepos. Not for general feature work that merely happens in a TypeScript codebase.
Diagnose slow React components and suggest targeted performance fixes.
Laserfocus platform help — Salesforce overlay with Stacks, table views, bulk editing, precache technology, and task management. Use when reps find native Salesforce UI too complex for daily pipeline work, Salesforce data entry is slow and reps skip updates, evaluating Laserfocus vs Scratchpad vs Weflow vs Dooly for Salesforce overlay, need a lightweight Salesforce alternative without replacing the CRM, or Laserfocus Stacks or Field Groups not working as expected. Do NOT use for general CRM selection (use /sales-crm-selection) or conversation intelligence / call recording (use /sales-note-taker).
Activate when developers have latent caching needs: slow API responses, database read bottlenecks, DynamoDB throttling or cost, RDS/Aurora scaling pressure, Bedrock latency or cost, or adding a cache; activate when working with Redis, Valkey, Memcached, or any in-memory data store, cache-aside patterns, session stores, rate limiting, leaderboards, counters, streams, queues, pub/sub, distributed locks, feature flags, shopping carts, or other caching strategies. Activate for GenAI and ML retrieval: vector similarity search for low-latency retrieval, semantic caching, RAG, LLM response caching, embedding stores, AI agent memory, recommendation, personalization. Activate for ElastiCache lifecycle: provisioning (serverless or node-based), engine selection, CloudFormation/CDK/Terraform IaC, VPC connectivity, TLS, RBAC, IAM auth, Global Datastore, monitoring, troubleshooting, cost optimization, and migration from self-managed Redis. Do not trigger for browser caches, CDN/CloudFront, HTTP Cache-Control, CPU caches.
After navigating and interacting in Cursor's built-in browser, use browser_network_requests to audit every fetch/XHR for failures, slowness, duplicate calls, and suspicious payloads. Use for API-heavy pages and after backend or client networking changes.
Query Google Calendar free/busy status for multiple users to find a meeting slot.
Manages Amazon DocumentDB end-to-end — serverless-on-8.0 cluster setup, TLS/VPC/driver config, flexible-schema and vector-search data modeling, MongoDB compatibility assessment, DMS-based migration, slow-query diagnosis, major version upgrades (4.0→5.0→8.0), Well-Architected reviews (41-check wa_review.py), cost estimation, and security hardening. Retrieve for every DocumentDB question and when the user asks to set up or migrate MongoDB to AWS — DocumentDB is AWS's MongoDB-compatible managed database. Triggers: JSON document store, document database, MongoDB on AWS, Nested fields, Lambda cannot connect, TLS handshake, VPC port 27017, IAM auth, Secrets Manager, encryption at rest, $graphLookup, flexible schema, COLLSCAN, compound index, DMS migration, CDC cutover, $vectorSearch, RAG, Global Clusters, DR replication, cost sizing, audit, health check, production-readiness.
SERP-informed outline generation with H2/H3 heading hierarchy, competitive content gap analysis, section-by-section word count targets, chart and image placement markers, FAQ question planning, and internal linking zones. Skeleton only: structure, H2/H3 hierarchy, word counts, FAQ slots. Use blog-brief instead if you need full competitive analysis, statistics research, and image suggestions. Lighter than a full content brief, generates article skeleton and structure only, ready for /blog write to consume. Use when user says "outline", "blog outline", "content outline", "structure blog", "plan sections", "article skeleton", "heading structure", "SERP analysis", "competitive outline", "plan article".
Optimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Reviewing SQL for performance anti-patterns (function on filter column, implicit joins, etc.) (4) User asks why a query is slow or how to speed it up
Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.
Remove AI-writing patterns from French text and inject voice, personality, and soul. Use when editing, reviewing, rewriting, or cleaning up French content that reads like ChatGPT/Claude output. Humanize, humanise, déslopifier. Detects and fixes 27 patterns: AI vocabulary overuse (crucial, essentiel, notamment, par ailleurs, dans le paysage), anglicisms from English-first models (faire du sens, adresser un problème), copula avoidance, formulaic openings (À l'ère de, Dans le paysage actuel), superficial participle analyses (-ant), em dash overuse, redundant adjective doublets, rule of three, sycophantic tone, typographic tells (curly quotes instead of guillemets). Trigger on: humaniser, déslopifier, rendre plus humain, nettoyer le texte IA, enlever le slop, réécrire pour que ça sonne humain, make it sound human.