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Found 1,954 Skills
Use when receiving code review feedback, processing PR comments, or needing to evaluate suggestions before implementing - requires technical verification not blind agreement
Generate or update tests for changed files in the current git branch, using statement coverage as the evaluation metric (target: 80%+). Use when: (1) the user asks to "write tests for my changes", "add tests for the current branch", or "improve coverage", (2) after implementing a feature to ensure adequate test coverage, (3) before a PR to verify changed code is tested. Supports Vitest and Cargo projects. Invoked with /test-generator or phrases like "generate tests", "test my changes", "cover the diff".
Use when evaluating AI tools and agentic workflows against workflow gaps, when conducting quarterly landscape scans, or when assessing integration feasibility of new tools for startup workflows.
Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics.
A cognitive framework based on learning first principles, providing learning method diagnosis, efficiency assessment, and optimization advice. Use when: (1) Diagnosing if current learning methods align with first principles, (2) Evaluating learning plan efficiency and time investment, (3) Analyzing learning behavior problems and providing improvement suggestions, (4) Determining if learning content is worth the time investment. Core principle chain: Self-learning → Induction → Self-output → Expression restructuring → Logical understanding → Practice.
Test pyramid and testing strategy — unit, integration, and end-to-end test ratios, mocking strategies, test isolation, and what to test. Reference when planning test coverage or evaluating test quality.
Comprehensive guide for implementing feature flags and A/B tests using the Flags SDK (the `flags` npm package). Use when: (1) Creating or declaring feature flags with `flag()`, (2) Setting up feature flag providers/adapters (Vercel, Statsig, LaunchDarkly, PostHog, GrowthBook, Hypertune, Edge Config, OpenFeature, Flagsmith, Reflag, Split, Optimizely, or custom adapters), (3) Implementing precompute patterns for static pages with feature flags, (4) Setting up evaluation context with `identify` and `dedupe`, (5) Integrating the Flags Explorer / Vercel Toolbar, (6) Working with feature flags in Next.js (App Router, Pages Router, Middleware) or SvelteKit, (7) Writing custom adapters, (8) Encrypting/decrypting flag values for the toolbar, (9) Any task involving the `flags`, `flags/next`, `flags/sveltekit`, `flags/react`, or `@flags-sdk/*` packages. Triggers on: feature flags, A/B testing, experimentation, flags SDK, flag adapters, precompute flags, Flags Explorer, feature gates, flag overrides.
Comprehensive prompt and context engineering for any AI system. Four modes: (1) Craft new prompts from scratch, (2) Analyze existing prompts with diagnostic scoring and optional improvement, (3) Convert prompts between model families (Claude/GPT/Gemini/Llama), (4) Evaluate prompts with test suites and rubrics. Adapts all recommendations to model class (instruction-following vs reasoning). Validates findings against current documentation. Use for system prompts, agent prompts, RAG pipelines, tool definitions, or any LLM context design. NOT for running prompts, generating content, or building agents.
Use this skill any time the user wants financial analysis, earnings research, or investment-related reports. This includes: earnings call summaries, quarterly financial analysis, stock research, equity research reports, financial due diligence, company valuations, DCF models, balance sheet analysis, income statement breakdowns, cash flow analysis, SEC filing summaries, investor memos, portfolio analysis, IPO analysis, M&A research, and credit analysis. Also trigger when: user says 分析财报, 做个估值, 股票研究, 财务尽调, 现金流分析, 收入分析, 季度财务分析. If financial research or analysis is needed, use this skill.
Apply when reviewing or designing security-sensitive boundaries in VTEX IO apps. Covers public versus private exposure, trust assumptions at route and integration boundaries, sensitive data handling, validating what crosses the app boundary, and avoiding leakage across accounts, workspaces, users, or integrations. Use for route hardening, data exposure review, or evaluating whether a service boundary is too permissive.
Use historical analogies to inform strategic decisions by identifying structural similarities and differences between past and present situations. Use this skill when the user draws on historical precedent to justify a strategy, needs to evaluate whether a historical comparison is valid, or wants to learn from past events — even if they say 'this is like the dotcom bubble', 'history repeats itself', or 'what can we learn from how X handled this'.
Apply mechanism design (reverse game theory) to engineer incentive-compatible rules for allocation problems. Use this skill when the user needs to design auctions, voting systems, or matching markets, or when evaluating whether a proposed mechanism satisfies incentive compatibility and individual rationality constraints.