Loading...
Loading...
Found 693 Skills
Use this skill when optimizing for AI-powered search engines and generative search results - Google AI Overviews, ChatGPT Search (SearchGPT), Perplexity, Microsoft Copilot Search, and other LLM-powered answer engines. Covers Generative Engine Optimization (GEO), citation signals for AI search, entity authority, LLMs.txt specification, and LLM-friendliness patterns based on Princeton GEO research. Triggers on visibility in AI search, getting cited by LLMs, or adapting SEO for the AI search era.
SPARC development workflow: Specification, Pseudocode, Architecture, Refinement, Completion. A structured approach for complex implementations that ensures thorough planning before coding. Use when: new feature implementation, complex implementations, architectural changes, system redesign, integration work, unclear requirements. Skip when: simple bug fixes, documentation updates, configuration changes, well-defined small tasks, routine maintenance.
Guide spec-driven feature development using a structured three-phase workflow: Requirements → Design → Tasks. Use this skill whenever the user wants to plan a feature, write a spec, or do structured design before coding. Trigger on phrases like "let's spec this out", "write a specification" or "help me think through this feature".
Use when the user needs prompt design, optimization, few-shot examples, chain-of-thought patterns, structured output, evaluation metrics, or prompt versioning. Triggers: new prompt creation, prompt optimization, few-shot example design, structured output specification, A/B testing prompts, evaluation framework setup.
Portable AI identity system using AIEOS (AI Entity Object Specification) - import, export, and manage agent personas in a standardized JSON format.
Stage 1 spec compliance review. Triggers: /review stage 1. Verifies implementation matches design specification — functional completeness, TDD compliance, and test coverage. Do NOT use for code quality checks — use quality-review instead. Do NOT use for debugging.
Design high-level functional and technical specifications by defining scope, modules, contracts, boundaries, responsibilities, architecture models, constraints, and verification criteria.
Use when the user asks to write specs before code, define acceptance criteria, plan features before implementation, generate tests from specifications, or follow spec-first development practices.
Generate FEATURES.md at the repo root by reading CONTEXT.md and docs/adr/, then enumerating the user-facing features the domain implies. Use after /grill-with-docs has settled the domain language and before /to-prd writes per-feature specs. Bridges the product→engineering gap between domain understanding and feature specification — the missing step that mattpocock's chain doesn't cover natively.
Implement Cisco's Foundry specification for agentic AI security evaluation systems with multi-agent architecture
A meta-skill for creating/writing custom Skills for the Aike Smart Parking Open Platform CLI (openydt), benchmarked against Feishu's lark-skill-maker. It is used when users want to encapsulate a specific openydt interface or a business process into a reusable Skill, create a new openydt domain Skill, standardize the directory structure and frontmatter of SKILL.md, extract the catalog command list, add --yes to write operations, or learn how to write an openydt Skill. Trigger words: create openydt skill, write an openydt skill, encapsulate openydt interface, create a parking domain skill, openydt skill maker, skill template, SKILL.md specification, how to write frontmatter, how to list command list, turn this interface into a skill, benchmark against lark-skill-maker, parking open platform skill, skill scaffolding, skill directory structure.
Run ACB (Anypoint Code Builder) system diagnostics to check if the machine meets minimum specifications and apply Windows optimizations if needed