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Found 1,440 Skills
TAM/SAM/SOM calculator with deep market research. Produces comprehensive market-sizing.md with top-down and bottom-up estimates, methodology, data sources, assumptions, sensitivity ranges, growth projections, competitive landscape, and Mermaid visualizations. Use when user needs market size estimates, addressable market analysis, go-to-market sizing, investor-ready market analysis, or business plan market validation.
Standards and best practices for writing LookML tests to ensure data integrity, accuracy, and logic validation.
Plan and run pre-release OpenClaw plugin validation across bundled plugins, package artifacts, lifecycle commands, doctor/fix, config round-trip, gateway startup, SDK compatibility, Docker E2E, Package Acceptance, and Testbox proof.
Author, validate, and troubleshoot AWS CloudFormation templates. Covers template authoring with secure defaults, pre-deployment validation (cfn-lint, cfn-guard, change sets), and root-cause diagnosis of failed stacks using CloudFormation events and CloudTrail correlation.
Use when preparing your agent for production — IAM scoping, inbound auth (JWT, SigV4), secrets management, cold start optimization, session lifecycle, rate limiting, input validation, and quota guidance. Triggers on: "production checklist", "harden agent", "production ready", "secure agent", "inbound auth", "going live", "cold start optimization", "session lifecycle", "StopRuntimeSession", "quota", "throttling", "maxVms", "rate limit", "security audit of outbound API calls", "gateway target audit for production", "restrict who can call", "lock down endpoint", "only our app can call". Not for Cedar tool-restriction policies — use agents-connect. Not for quality measurement — use agents-optimize. Not for outbound credential storage or API key wiring — use agents-connect. Not for A2A agent-to-agent auth — use agents-build. Cold start observation and diagnosis (not optimization) routes to agents-debug.
A comprehensive guide to implementing Syncfusion Angular Input components, including Uploader, NumericTextBox, TextBox, Signature, CheckBox, OTP Input, RangeSlider, and TextArea. This guide is intended for building Angular applications with file upload UIs supporting async and chunked uploads, drag‑and‑drop functionality, numeric inputs with validation and formatting, text inputs with floating labels and custom adornments, digital signature capture with undo, redo, and export capabilities, checkbox multi‑select and indeterminate states, seamless form integration, accessibility compliance, one‑time password (OTP) inputs, programmatic row adjustments, and slider tick customization and styling.
Autonomous rule adherence checker. Scans the codebase for rule violations, fixes the highest-impact ones in an isolated worktree, runs full validation, creates a PR. Uses memory to track progress across runs.
Handles commit flows by detecting changes, optionally running validator validation, and completing commits for requests such as "commit with validator", "run checks before commit", "run validator then commit", or "skip validator and commit".
Quantitative strategy generation and optimisation framework via Longbridge — create, modify, and backtest quant strategies: parameter grid search, walk-forward validation, overfitting detection (in-sample vs. out-of-sample), strategy combination (multi-strategy correlation diversification), Sharpe / Calmar ratio optimisation. Generates Python code frameworks for local execution. Triggers: "策略优化", "策略生成", "参数优化", "网格搜索", "回测优化", "过拟合", "walk-forward", "策略回测优化", "策略組合", "策略優化", "策略生成", "參數優化", "網格搜索", "回測優化", "strategy optimization", "strategy generation", "parameter optimization", "grid search", "overfitting", "walk-forward validation", "strategy backtest", "Sharpe ratio", "Calmar ratio".
Assess construction data quality using completeness, accuracy, consistency, timeliness, and validity metrics. Automated validation with regex patterns, thresholds, and reporting.
Day 2 end capstone move of a Foundation Sprint. Compresses the sprint's full strategic frame into a single canonical sentence (the Founding Hypothesis) plus an assumption scorecard, why-we-believe, what-could-prove-us-wrong, and recommended next validation step. Use after Magic Lenses is signed. Strict canonical template; paraphrase is not accepted in v0.1.0. The Founding Hypothesis is the spine artifact the sprint exists to produce.
Design and operate data quality programs for financial data — golden source architecture, validation rules, data lineage, exception management, profiling, and governance. Use when building validation rules for pricing or client data pipelines, designing a data quality monitoring framework, establishing golden source designations across systems, implementing data lineage for BCBS 239 or MiFID II, investigating reconciliation breaks or billing errors traced to bad data, preparing for regulatory exams on data accuracy, building data quality scorecards, or defining data stewardship roles. Trigger on: data quality, golden source, data lineage, data validation, data profiling, exception management, data governance, BCBS 239, data completeness, data accuracy, validation rules, data anomaly, data stewardship, data quality scorecard.