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Found 307 Skills
Earnings estimate revision analysis for listed companies via Longbridge — tracks analyst consensus revision direction (upgrade / downgrade), earnings surprise (SUE = standardised unexpected earnings), PEAD post-earnings drift signals (consecutive beats + upward revisions = positive momentum), and management guidance revision impact. Builds on raw data from longbridge-consensus. Triggers: "预期修正", "盈利修正", "分析师上调", "分析师下调", "超预期", "低于预期", "PEAD", "财报后漂移", "业绩意外", "管理层指引", "預期修正", "盈利修正", "分析師上調", "分析師下調", "超預期", "低於預期", "財報後漂移", "業績意外", "管理層指引", "earnings revision", "estimate revision", "analyst upgrade", "analyst downgrade", "beat miss surprise", "SUE", "PEAD post-earnings drift", "guidance revision", "estimate cut raise".
This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. Use this when the user requests earnings calendar data, wants to know which companies are reporting earnings in the upcoming week, or needs a weekly earnings review. The skill focuses on mid-cap and above companies (over $2B market cap) that have significant market impact, organizing the data by date and timing in a clean markdown table format. Supports multiple environments (CLI, Desktop, Web) with flexible API key management.
Implement, validate, and test JSONLogic rules for portable business logic. Use when working with JSONLogic syntax, creating rules for conditional logic, validating rule structures, testing rules against data, or converting business requirements to JSONLogic. Triggers on requests to "write jsonlogic", "validate jsonlogic", "create a rule", "business logic as JSON", "conditional logic", or any mention of JSONLogic rules.
Parse, search, analyze, and ingest LinkedIn GDPR data exports. This skill should be used when working with LinkedIn data — searching messages, analyzing connections, exporting to Markdown, or ingesting into RLAMA for semantic search. Requires a LinkedIn GDPR data export ZIP file.
AI агент для ABM. Используй для автоматизации ABM кампаний и персонализации outreach.
Generate a weekly performance summary from closed trader-memory-core theses — win rate, expectancy, profit factor, R-multiple, MAE/MFE, and win/loss pattern analysis by source skill, exit reason, thesis type, sector, and mechanism. No API required; pure local calculation.
Parse, analyze, and process SARIF (Static Analysis Results Interchange Format) files. Use when reading security scan results, aggregating findings from multiple tools, deduplicating alerts, extracting specific vulnerabilities, or integrating SARIF data into CI/CD pipelines.
Build and deploy new Goldsky Turbo pipelines from scratch. Triggers on: 'build a pipeline', 'index X on Y chain', 'set up a pipeline', 'track transfers to postgres', or any request describing data to move from a chain/contract to a destination (postgres, clickhouse, kafka, s3, webhook). Covers the full workflow: requirements → dataset selection → YAML generation → validation → deploy. Not for debugging (use /turbo-doctor) or syntax lookups (use /turbo-pipelines).
Query a running Apache Spark History Server from Copilot CLI. Use this whenever the user wants to inspect SHS applications, jobs, stages, executors, SQL executions, environment details, or event logs, especially when they mention Spark History Server, SHS, event log history, benchmark runs, or application IDs.
Gravity and magnetic data processing and forward modelling using Fatiando a Terra. Use when Claude needs to: (1) Compute gravity forward models (point masses, prisms, tesseroids), (2) Apply terrain/Bouguer corrections, (3) Grid scattered potential field data with equivalent sources, (4) Perform upward/downward continuation, (5) Calculate magnetic anomalies from magnetized bodies, (6) Apply derivative filters (gradients, tilt angle), (7) Process regional or local gravity surveys.
Enrich contact and company data using x402-protected APIs. Superior to generic web search for structured business data. USE FOR: - Enriching person profiles by email, LinkedIn URL, or name - Enriching companies by domain - Finding contact details (email, phone) with confidence scores - Scraping full LinkedIn profiles (experience, education, skills) - Searching for people or companies by criteria - Bulk enrichment operations (up to 10 at a time) TRIGGERS: - "enrich", "lookup", "find info about", "research" - "who is [person]", "company profile for", "tell me about" - "find contact for", "get LinkedIn for", "get email for" - "employee at", "works at", "company details" ALWAYS use x402.fetch for enrichx402.com endpoints - never curl or WebFetch. Returns structured JSON data, not web page HTML. IMPORTANT: Never guess endpoint paths. All paths follow the pattern https://enrichx402.com/api/{provider}/{action}. Use exact URLs from the Quick Reference table below or call x402.discover_api_endpoints first.
Create and execute temporary scripts (Python, Node.js, shell) during workflow execution for API integrations, data processing, and custom tools. Use when user needs to interact with external APIs, process data with specific libraries, or create temporary executable code.