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Found 2,821 Skills
Compute market-data and trading analytics with the `fintech-algorithms` npm package — 324 zero-dependency TypeScript algorithms covering technical indicators (RSI, MACD, moving averages, Bollinger Bands, ATR, OBV, Stochastic), candlestick and chart patterns, market breadth, bar construction from tick data, OHLC validation and cleaning, corporate actions, index and benchmark construction, market microstructure, matching engines, execution and TCA, statistical time series, on-chain metrics and EPS analytics. Use when asked to analyse a price series, compute or explain an indicator, detect a candlestick or chart pattern, build bars from ticks, validate or clean market data, wire up a market-data provider, or when writing code that needs any of these calculations to be correct rather than approximated.
MANDATORY for static requests to find, identify, or list untested source files or modules, sources without tests, source-to-test pairing, test-gap worklists, or suggested test locations. Invoke even for a tiny package; do not substitute manual globbing. Uses Roslyn for C#/.NET and tree-sitter for Python, TS/JS, Go, Java, Rust, and Ruby. DO NOT USE FOR: line/branch coverage, CRAP risk, or grading existing tests.
Answer a merchant's **analytics and reporting** questions with **ShopifyQL** — Shopify's query language for aggregated store metrics that the Admin GraphQL API cannot compute. Choose this (not `admin`) whenever the ask is for **numbers, totals, trends, or breakdowns** rather than fetching or mutating individual records: including but not limited to total/gross/net sales and revenue, order counts, average order value, refunds, quantity sold, sessions, conversion rate, and traffic — sliced by product, channel, region, or customer, trended over time, or compared period-over-period. Examples: "total sales last 7 days", "orders by sales channel this month", "top products by revenue", "conversion rate this week", "sales this year vs last year". This topic covers writing the ShopifyQL query; if the merchant wants to run it against their store, execution is handed off to `use-shopify-cli`. Not for general Admin GraphQL record operations — fetching or mutating individual resources (use `admin`).
Grades a specified set of test methods individually and produces a concise table mapping each test (fully-qualified name) to a letter grade (A–F), a score band, and a one-line note — designed to be posted as a PR comment. Use when the caller wants per-test feedback on a curated list of methods (for example, the new or modified tests in a pull request), not a suite-wide audit. Polyglot: .NET, Python, TS/JS, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, C++. Input is a list of test methods (or method bodies / file+line spans); output is a compact markdown table plus a short summary. DO NOT USE FOR: full suite audits (use test-quality-auditor agent or test-anti-patterns), writing new tests (use code-testing-generator agent or writing-mstest-tests), fixing failures, or measuring code coverage.
Multi-dimensional health assessment for .NET projects with letter grades (A-F) using Roslyn MCP tools. Evaluates 8 dimensions: build health, code quality, architecture, test coverage, dead code, API surface, security posture, and documentation. Produces a structured report card with actionable recommendations. Load this skill when: "health check", "how healthy is this", "project health", "code quality report", "grade this project", "assess codebase", "quality audit", "technical assessment", "codebase review", "report card".
Bun runtime API reference for TypeScript scripts. Covers Bun.file(), Bun.write(), Bun.$() shell, Bun.spawn(), Bun.Glob, Bun.env, bun:sqlite, Bun.sql() for PostgreSQL/MySQL via DATABASE_URL, Bun.s3 for S3-compatible storage, Bun.redis for Redis/Valkey, Bun.Archive for tarballs, Bun.Image image processing, Bun.WebView headless browser automation, Bun.cron in-process scheduler, JSONC/JSON5/JSONL/markdown (named imports), Bun.hash, Bun.password, compression, and scripting utilities. Use when writing scripts, automating tasks, querying databases, working with S3 storage, Redis caching, processing images, automating a headless browser, parsing markdown/JSON variants, or doing file processing in a Bun project. Signals: bun.lock, bunfig.toml, DATABASE_URL, REDIS_URL, AWS_ACCESS_KEY_ID, Bun.$ usage Not for bun CLI commands (bun-cli skill), non-Bun runtimes, or ORM CLI tooling
Index of ImageKit SDKs, plugins, and integrations — front-end, back-end, mobile, CMS, external storage, video player, media library & upload widgets, AI/automation, and URL generation. Use to find the right integration for a technology and what it covers, then query search_docs for implementation details.
AWS-curated copy-paste prompts for AI coding agents (MVP scaffolding, RAG chatbot with Claude on Bedrock, security baseline evaluation, cost anomaly detection, GPU quota requests, EKS deployment, Well-Architected review, etc.) plus downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account / cost monitoring / quota management / Bedrock model availability / database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, OpenAI/Gemini to Bedrock), route to the migration-to-aws skill. Do not use for: factual AWS Activate / programs / credits questions, learn articles, sample architectures, or for prompts that are not in the bundled `references/prompt-library/` tree.
Use when auditing domain authority, trust, or citation credibility; runs a peer-relative 40-item CITE profile with evidence coverage and verified manipulation/penalty veto checks. Not for page-level content quality — use content-quality-auditor; not for backlink profiling alone — use offsite-signal-analyzer. 域名权威/网站可信度
Code-level quality analysis. Use when asked to review code for smells, security issues, implementation quality, or test coverage.
Audit and reduce AI agent runtime spend in dollars. Use for AI costs, agent spend, token waste, runtime attribution, detector coverage, and FinOps. Works with OpenClaw, Hermes, QM, Claude Code, Cursor, and generic event ingest.
Factorial Code platform architecture and core concepts — processes, modules, execution context, team variables and their inheritance from parent workspaces, datastore, file storage, workspace structure, and naming conventions. Use when building, editing, or reasoning about any Factorial Code (fcode) process, module, or workspace; start here before writing process or module code.