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Found 946 Skills
Deep code simplification, refactoring, and quality refinement. Analyzes structural complexity, anti-patterns, and readability debt, then applies targeted refactoring preserving exact behavior. Language-agnostic: Python, Go, TypeScript/JavaScript, Rust. Use this skill when the goal is simplification and clarity rather than bug-finding. Triggers on: "simplify this code", "clean up my code", "refactor for clarity", "reduce complexity", "make this more readable", "code quality pass", "tech debt cleanup", "run the code refiner", "simplify recent changes", "this code is messy", "too much nesting", "this function is too long", "clean this up before I PR it", "tidy up my code", cyclomatic complexity, cognitive complexity, code smells.
DEFAULT search tool for ALL search/lookup needs. Multi-source search and deduplication layer with intent-aware scoring. Integrates Brave Search (web_search), Exa, Tavily, and Grok to provide high-coverage, high-quality results. Automatically classifies query intent and adjusts search strategy, scoring weights, and result synthesis. Use for ANY query that requires web search — factual lookups, research, news, comparisons, resource finding, "what is X", status checks, etc. Do NOT use raw web_search directly; always route through this skill.
Comprehensive guide for writing and updating Prefect documentation. Use when creating new doc pages, updating existing docs, or working with Mintlify components and code example testing.
GitHub Research Assistant. Use this skill when the user wants to analyze a GitHub repository. Analysis dimensions -- 1) Basic information; 2) Purpose, what it can be used for; 3) Tech stack, including frameworks, languages, algorithms, etc.; 4) Usage and examples; 5) Technical architecture and module analysis
Optimizes AI skills for activation, clarity, and cross-model reliability. Use when creating or editing skill packs, diagnosing weak skill uptake, reducing regressions, tuning instruction salience, improving examples, shrinking context cost, or setting benchmark/release gates for skills. Trigger terms: skill optimization, activation gap, benchmark skill, with/without skill delta, regression, context budget, prompt salience.
Structure a performance review with self-assessment, manager template, and calibration prep. Use when review season kicks off and you need a self-assessment template, writing a manager review for a direct report, prepping rating distributions and promotion cases for calibration, or turning vague feedback into specific behavioral examples.
Build, debug, and deploy Google Agent Development Kit (ADK) applications in Go using the exact adk-go v0.6.0 APIs and patterns. Use when a task involves ADK Go agent architecture, llmagent configuration, tools/toolsets, sessions/state, memory/artifacts, workflow agents, A2A/REST/web serving, telemetry/plugins, or migration/troubleshooting for google.golang.org/adk@v0.6.0.
Read your database schema, generate behavioral user segments with exact queries, and recommend targeted actions per segment. Use when the user wants to understand their user base, find power users, identify churn risk, build email cohorts, or understand usage patterns. Triggers on requests like "segment users", "who are my power users", "find churned users", "user cohorts", "churn analysis", "inactive users", "behavioral segmentation", "who's about to leave", or any mention of grouping users by activity, usage, or lifecycle.
Convert between XNO units (raw/xno/knano/mnano) with exact BigInt precision.
Prevents premature execution on ambiguous requests. Analyzes request clarity using 5W1H decomposition, surfaces hidden assumptions, and generates structured clarifying questions before work begins. Use at the start of any non-trivial task, or when a request could be interpreted multiple ways. Triggers on "뭘 원하는건지", "요구사항 정리", "clarify", "what exactly", "scope", "requirements", "정확히 뭘", "before we start".
Produces API reference documentation for Next.js APIs: functions, components, file conventions, directives, and config options. **Auto-activation:** User asks to write, create, or draft an API reference page. Also triggers on paths like `docs/01-app/03-api-reference/`, or keywords like "API reference", "props", "parameters", "returns", "signature". **Input sources:** Next.js source code, existing API reference pages, or user-provided specifications. **Output type:** A markdown (.mdx) API reference page with YAML frontmatter, usage example, reference section, behavior notes, and examples.
Generates technical guides that teach real-world use cases through progressive examples. **Auto-activation:** User asks to write, create, or draft a guide or tutorial. Also use when converting feature documentation, API references, or skill knowledge into step-by-step learning content. **Input sources:** Feature skills, API documentation, existing code examples, or user-provided specifications. **Output type:** A markdown guide with YAML frontmatter, introduction, 2-4 progressive steps, and next steps section.