Loading...
Loading...
Found 428 Skills
Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.
Summarize a customer interview transcript into a structured template with JTBD, satisfaction signals, and action items. Use when processing interview recordings or transcripts, synthesizing discovery interviews, or creating interview summaries.
Twitter/X data lookup — search tweets, user profiles, followers, replies. Use when the user asks about Twitter activity, social signals, or wants to look up accounts.
Bitcoin bottom-timing judgment model. By tracking 6 core indicators (RSI technical oversold, volume dry-up, MVRV ratio, social media fear index, miner shutdown price, long-term holder behavior), it comprehensively evaluates whether Bitcoin has entered a bottom-fishing zone and outputs a bottom-fishing rating and position-building recommendations. When users mention topics such as Bitcoin bottom-fishing, whether BTC has bottomed out, Bitcoin oversold, MVRV, miner shutdown price, long-term holder LTH, Bitcoin fear index, whether to buy Bitcoin, BTC position entry timing, crypto market bottom signals, Bitcoin cycle bottom, etc., be sure to use this skill. Even if the user simply asks "Can I buy the dip on Bitcoin now?" or "Has BTC finished dropping?", this skill should be triggered to provide a structured analysis framework.
Fetch the latest financial signals and transmission-chain analyses from DeepEar Lite. Use when the user needs immediate insights into financial market trends, stock performance factors, and reasoning from the DeepEar Lite dashboard.
Interpret buying signals and prioritize accounts for outreach. Use when analyzing intent data, prioritizing accounts, reading buying signals, tracking job changes, using intent topics, scoring leads, deciding who to contact first, or building signal-based outreach workflows. Do NOT use for building prospect lists (use /sales-prospect-list), enriching contacts (use /sales-enrich), or general Apollo platform help (use /sales-apollo).
ALWAYS use when working with Angular Signal Forms, reactive forms with signals, FormControl with signals, or new forms API in Angular.
Troubleshoot and resolve common issues with the ClickHouse Node.js client (@clickhouse/client). Use this skill whenever a user reports errors, unexpected behavior, or configuration questions involving the Node.js client specifically — including socket hang-up errors, Keep-Alive problems, stream handling issues, data type mismatches, read-only user restrictions, proxy/TLS setup problems, or long-running query timeouts. Trigger even when the user hasn't precisely named the issue; vague symptoms like "my inserts keep failing" or "connection drops randomly" in a Node.js context are strong signals to use this skill. Do NOT use for browser/Web client issues.
Audit and score blog posts on a 5-category 100-point scoring system covering content quality, SEO optimization, E-E-A-T signals, technical elements, and AI citation readiness. Includes AI content detection (burstiness, phrase flagging, vocabulary diversity). Supports export formats (markdown, JSON, table) and batch analysis with sorting. Generates prioritized recommendations (Critical/High/Medium/Low) with specific fixes. Works with any format (MDX, markdown, HTML, URL). Use when user says "analyze blog", "audit blog", "blog score", "check blog quality", "blog review", "rate this blog", "blog health check".
Horizontal session personality overlay — auto-detects conversation mode from density signals, defaults casual, upgrades to structured only on sustained signal. Includes CommitMono aesthetic preference and MoE/thinking-chain runtime awareness.
Generates YAML signal configs for agent simulation experiments. Use when the user wants to define what signals to track, how to extract them from run artifacts, and how to aggregate them into experiment-level metrics. Trigger when users say: "generate a signal config", "create signals for my experiment", "I want to track [metric]", "write a signal YAML", "set up extraction for [thing]", "how do I measure [behavior] across runs", "configure signals for [experiment]", "create a signal config", "create signal config file", or "build a signal config".
Guide AI agents through Godot 4.x GDScript coding best practices including scene organization, signals, resources, state machines, and performance optimization. This skill should be used when generating GDScript code, creating Godot scenes, designing game architecture, implementing state machines, object pooling, save/load systems, or when the user asks about Godot patterns, node structure, or GDScript standards. Keywords: godot, gdscript, game development, signals, resources, scenes, nodes, state machine, object pooling, save system, autoload, export, type hints.