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Found 5,651 Skills
Comprehensive codebase reading engine. Systematically reads actual source code line by line through a 6-phase protocol — scoping, structural mapping, execution tracing, deep reading, pattern synthesis, and structured reporting. Source code is the source of truth. Use when needing to truly understand how code works, not just what documentation claims.
Discovers business domains in a Swift codebase by tracing what users can DO — not by reading folder names or architecture docs. Maps each domain's vertical slice (Types → Config → Repo → Service → Runtime → UI), identifies providers (external SDK bridges), and separates cross-cutting concerns. Produces a domain map that drives all downstream decisions: folder structure, SPM targets, enforcement specs, migration plans. Use this skill whenever the user wants to understand their codebase domains, find what's cross-cutting vs domain-specific, restructure a Swift project, figure out where code belongs, or map a product's capabilities to architectural boundaries. Triggers on "what are my domains", "where does this belong", "map this codebase", "what's cross-cutting", "organize this project", "is this a domain or infra", "restructure this", "architecture review", or any request to understand the business domain structure of a Swift codebase.
SQL patterns for database querying and design
Identifies and fixes performance bottlenecks in code, databases, and APIs. Measures before and after to prove improvements.
Analyze and design pricing strategies including cost-plus, value-based, competitive, penetration, and skimming approaches with psychological pricing techniques. Use this skill when the user needs to set or change prices, evaluate pricing models, understand price elasticity, or apply psychological pricing — even if they say 'how much should we charge', 'are we priced right', or 'our margins are too low'.
Store and retrieve agent memories across jobs. Enables long-term context, learning from past interactions, and building agent knowledge bases. Based on OpenClaw's memory-core architecture.
Remove AI-generated traces from text. Suitable for editing or reviewing text to make it sound more natural and human-written. Based on the comprehensive guide of "Signs of AI Writing" from Wikipedia. Detects and fixes the following patterns: exaggerated symbolism, promotional language, superficial analysis ending with -ing, vague attribution, overuse of dashes, rule of three, AI vocabulary, negative parallelism, excessive connecting phrases.
Designs production-grade RAG pipelines with chunking optimization, retrieval evaluation, and pipeline architecture. Use when building a RAG system, selecting a chunking strategy, choosing a vector database, optimizing retrieval quality, designing embedding pipelines, or evaluating RAG performance with RAGAS metrics.
Answer questions against the knowledge base wiki. Use when the user asks a question about their collected knowledge, wants to explore connections between topics, says "what do I know about X", or wants to search their wiki, second brain, or knowledge base.
Generate tests from Allium specifications. Use when the user wants to propagate tests, generate test files from a spec, write tests for a specification, create property-based tests, produce state machine tests, check test coverage against spec obligations, or understand what tests a specification requires.
Use when adding login, logout, and user profile to a Flask web application using session-based authentication - integrates auth0-server-python for server-rendered apps with login/callback/profile/logout flows.
Complete coaching skills for Taiwanese nursing staff to write evidence-based nursing reports (evidence-based reading reports, evidence-based case analyses), designed specifically for the N1–N4 nursing advancement system and the review formats of the Taiwan Nurses Association and Taiwan Evidence-Based Nursing Association. This skill must be triggered when users mention terms such as "evidence-based nursing report", "evidence-based case analysis", "evidence-based reading report", "N2 report", "N3 report", "N4 report", "nursing advancement report", "nursing promotion", "PICO", "5A Steps", "CASP Appraisal", "nursing EBP", "EBN", "evidence-based nursing", "evidence-based care", "evidence level", "literature appraisal", or when any nursing staff asks about promotion writing, transforming clinical problems into evidence-based topics, evidence-based literature search strategies, CASP appraisal forms, Oxford evidence levels, APA 7th edition format, applying evidence-based interventions to cases, challenging nursing routines, dispelling nursing myths, etc. Even if users casually say "I need to write a report", "I want to advance to N3", "Help me find a topic", "Help me set up PICO", "How to appraise this literature", this skill should be actively activated to provide complete structures, sentence patterns, and writing strategies with the highest review pass rate.