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Found 516 Skills
The root skill of the easysdd workflow family — introduces the workflow system and routes users to the correct sub-skill. Trigger scenarios: Users mention "easysdd", "sdd", "spec-driven", "how to use this set of processes", "which skill should I use", "where to start", or describe a new feature but haven't decided on the entry stage. Known intents (brainstorm/design/implementation/acceptance/BUG/exploration, etc.) will trigger the corresponding sub-skill first instead of this skill.
Use when the user asks for repeated rollouts, marked decision processes, high-dimensional search, stochastic optimization, local-optima exploration, ensemble comparison, or recursive reasoning with a visible evidence trail.
Audits AI-implemented work for honest completion. Runs independent-evaluator checks against task artifacts, transcripts, tests, CI evidence, requirement-to-test mapping, status front matter, and quality gates; flags skipped tests, weakened assertions, mock-only confidence, snapshot drift, happy-path-only coverage, flaky retries, and status/evidence mismatches. Use when validating completed Compozy tasks, AI-authored PRs, or codex-loop iterations. Do not use for real-user QA, persona/journey testing, exploratory charters, or product usability sessions; use qa-execution for those.
Automated hypothesis generation and testing using large language models. Use this skill when generating scientific hypotheses from datasets, combining literature insights with empirical data, testing hypotheses against observational data, or conducting systematic hypothesis exploration for research discovery in domains like deception detection, AI content detection, mental health analysis, or other empirical research tasks.
Expert SwiftGen decisions for iOS/tvOS: when type-safe assets add value, template selection trade-offs, organization strategies, and build phase configuration. Use when setting up SwiftGen, choosing templates, or debugging generation issues. Trigger keywords: SwiftGen, type-safe, Asset, L10n, ImageAsset, ColorAsset, FontFamily, swiftgen.yml, structured-swift5, code generation, asset catalog
Uncertainty-aware non-linear reasoning system with recursive subagent orchestration. Triggers for complex reasoning, research, multi-domain synthesis, or when explicit commands `/nlr`, `/reason`, `/think-deep` are used. Integrates think skill (reasoning), agent-core skill (acting), and MCP tools (infranodus, exa, scholar-gateway) in recursive think→act→observe loops. Uses coding sandbox for execution validation and maintains deliberate noisiness via NoisyGraph scaffold. Supports `/compact` mode for abbreviated outputs and `/semantic` mode for rich exploration.
This skill should be used when the user asks to "use the oracle" or "ask the oracle" for deep research, analysis, or architectural questions. The oracle excels at multi-source research combining codebase exploration and web searches, then synthesizing findings into actionable answers. Use for complex questions requiring investigation across multiple sources, architectural analysis, refactoring plans, debugging mysteries, and code reviews.
Log exploration and analysis using Quickwit search engine. Incident investigation, error pattern analysis, and observability workflows. Three index discovery modes for different performance and convenience trade-offs.
Deep web research with parallel investigators, multi-wave exploration, and structured synthesis. Spawns multiple web-researcher agents to explore different facets of a topic simultaneously, launches additional waves when gaps are identified, then synthesizes findings. Use when asked to research, investigate, compare options, find best practices, or gather comprehensive information from the web.\n\nThoroughness: quick for factual lookups | medium for focused topics | thorough for comparisons/evaluations (waves continue while critical gaps remain) | very-thorough for comprehensive research (waves continue until satisficed). Auto-selects if not specified.
Learn about Moralis and Web3 development. Invoked without a question, gives a friendly platform walkthrough — what's available, what data you can fetch, and how everything fits together. Invoked with a question, answers it directly. Use for "what is Moralis", "can Moralis do X", "what chains are supported", "how do I get started", "which API should I use", pricing, feature comparisons, or any exploratory questions. Routes to the correct technical skill (@moralis-data-api or @moralis-streams-api) after answering.
Upstream codebase exploration for open source contribution. Outputs contribution guidelines, PR patterns, and maintainer expectations. Triggers: "pr research", "upstream research", "contribution research", "explore upstream repo".
Best practices for developing tools, dashboards and interactive data apps with HoloViz Panel. Create reactive, component-based UIs with widgets, layouts, templates, and real-time updates. Use when developing interactive data exploration tools, dashboards, data apps, or any interactive Python web application. Supports file uploads, streaming data, multi-page apps, and integration with HoloViews, hvPlot, Pandas, Polars, DuckDB and the rest of the HoloViz and PyData ecosystems.