Loading...
Loading...
Found 39 Skills
Provides comprehensive guidance for building AI-powered Generative UI applications with the Thesys C1 API and GenUI SDK. Use it when developing interactive UI components, chat interfaces, dashboards, or any application that benefits from dynamically generated React interfaces from natural language prompts.
Sketch a UI design as a throwaway `.openui` file in `docs/prototype/` for the developer to render live in the Genui VS Code extension. Use when the user wants to see a design, sketch a screen, mock up a layout, compare a few options, or says "genui this", "sketch a [page]", "mock up [thing]", "let me see a few options", "prototype this design", "draft a UI". This is specifically for visual UI mockups rendered by the Genui extension, not terminal logic prototyping.
Clayton Christensen's Disruption Analysis applied to a company, market, or business idea. Spawns a team of specialist agents — Disruption Cartographer, RPV Diagnostician, Jobs Archaeologist, Trajectory Analyst, Incumbent's Advocate — who each apply a distinct lens from Christensen's framework to evaluate disruption risk and opportunity. The lead synthesizes into a disruption verdict: is this company vulnerable to disruption from below, is this startup on a genuine disruption trajectory, or is this a sustaining innovation that incumbents will crush? Use when the user says "christensen this", "disruption analysis", "is this disruptive", "vulnerable to disruption", or wants to evaluate whether a company/market faces disruption risk. Works as a standalone analysis or paired with /munger for a complete picture.
Build web interfaces with genuine design quality, not AI slop. Use for any frontend work - landing pages, web apps, dashboards, admin panels, components, interactive experiences. Activates for both greenfield builds and modifications to existing applications. Detects existing design systems and respects them. Covers composition, typography, color, motion, and copy. Verifies results via screenshots before declaring done.
Transform AI-assisted drafts into authentic, human-sounding content. This skill provides patterns to detect and eliminate AI tells, frameworks for natural writing, and techniques for creating prose that reads as genuinely human. Use when reviewing any AI-generated content or when writing content that must not appear AI-assisted.
Expert guide for creating authentic, human-sounding content that avoids AI-generated writing patterns. Use when reviewing, editing, or creating content to ensure it sounds genuinely human and avoids AI detection markers.
Production-ready skill for integrating TheSys C1 Generative UI API into React applications. This skill should be used when building AI-powered interfaces that stream interactive components (forms, charts, tables) instead of plain text responses. Covers complete integration patterns for Vite+React, Next.js, and Cloudflare Workers with OpenAI, Anthropic Claude, and Cloudflare Workers AI. Includes tool calling with Zod schemas, theming, thread management, and production deployment. Prevents 12+ common integration errors and provides working templates for chat interfaces, data visualization, and dynamic forms. Use this skill when implementing conversational UIs, AI assistants, search interfaces, or any application requiring real-time generative user interfaces with streaming LLM responses. Keywords: TheSys C1, TheSys Generative UI, @thesysai/genui-sdk, generative UI, AI UI, streaming UI components, interactive components, AI forms, AI charts, AI tables, conversational UI, AI assistants UI, React generative UI, Vite generative UI, Next.js generative UI, Cloudflare Workers generative UI, OpenAI generative UI, Claude generative UI, Anthropic UI, Cloudflare Workers AI UI, tool calling UI, Zod schemas UI, thread management, theming UI, chat interface, data visualization, dynamic forms, streaming LLM UI
Critical analysis of research papers, academic manuscripts, preprints, and technical studies — evaluating methodology, claims-evidence alignment, contribution significance, and intellectual honesty. Produces coherent analytical responses (not checklists) that distinguish genuine weaknesses from standard field limitations. Governs intellectual posture: collegial reader, not adversarial reviewer. Triggers on: "critique this paper", "review this research", "what do you think of this paper", "analyze this study", "evaluate the methodology", "is this paper sound", "assess this research", "strengths and weaknesses of this paper", "does the evidence support the claims". Use this skill when the user provides a research paper, preprint, or technical study and asks for critical evaluation of its scientific merit, methodology, or contribution — not formatting, citation hygiene, or submission readiness (use manuscript-review for those).
Use this skill whenever deciding what features to extract from raw marketplace assets — listing photos, owner-entered listing metadata, sitter wizard responses — to power item-to-item (similar listings), user-to-item (homefeed ranking), or user-to-user (mutual-fit matching) recommenders in a two-sided trust marketplace. Covers asset auditing, first-principles feature decomposition from the decision the user is making, vision-feature extraction (CLIP, room-type classification, amenity detection, aesthetic and quality scoring), listing text and metadata encoding (categoricals, multi-hot amenities, H3 geo-hashing, sentence-transformer description embeddings, structured pet triples), sitter wizard design (information-gain ordering, multiple-choice over free text, genuine skippability, hard constraint versus soft preference), derived-composition patterns for i2i / u2i / u2u (precomputed ANN shelves, multi-modal fusion, two-tower affinity, symmetric mutual-fit scoring, interpretable subscores), feature quality governance (single registry, training-serving parity, coverage and drift alarms, PII scrubbing, schema versioning), and incremental value proof (one feature at a time, ablation A/B, kill reviews, exploration slice, permanent feature-free baseline). Trigger even when the user does not explicitly say "feature engineering" but is asking how to get more signal out of listing photos, listing metadata, or the sitter onboarding wizard, or how to improve i2i / u2i / u2u quality without blindly ingesting a new model.
The craft of communicating technical concepts clearly to developers. Developer communications isn't marketing—it's about building trust through transparency, accuracy, and genuine utility. The best devrel content helps developers solve real problems. This skill covers technical documentation, developer tutorials, API references, changelog writing, developer blog posts, and developer community engagement. Great developer communications treats developers as peers, not leads to convert. Use when "documentation, docs, tutorial, getting started, API reference, changelog, release notes, developer guide, devrel, developer relations, code examples, SDK docs, README, documentation, devrel, tutorials, api-docs, developer-experience, technical-writing, getting-started, changelogs" mentioned.
Root-cause-driven solution decision framework for the hardest problems across any domain. This is the nuclear option — it consumes significant tokens through exhaustive multi-branch root cause analysis, MECE solution enumeration, and domain-adaptive external validation. Use ONLY for genuinely difficult problems: recurring failures that resist repeated fix attempts, complex systemic issues with no clear solution path, decisions where multiple approaches exist and the wrong choice has high cost, problems with multiple interacting causes spanning components or teams. Trigger when: the user says 'what's the best way to fix X', 'why does this keep happening', 'how should we approach this', 'find the root cause', 'what are my options for fixing X', 'analyze this problem systematically', 'evaluate our options for X', 'what's the right approach and why', or expresses frustration that previous solutions didn't stick. Do NOT use for: problems where the answer is already obvious or requires no analysis, straightforward issues with clear solutions, or routine investigation. If the problem can be solved in 5 minutes of investigation, this skill is overkill.
Design and conduct mixed methods research using convergent, explanatory sequential, or exploratory sequential strategies with genuine integration of qualitative and quantitative strands. Use this skill when the user needs to choose a mixed methods design, integrate qualitative and quantitative data at design, methods, or interpretation levels, justify mixing on pragmatist grounds, or when they ask 'which mixed methods design should I use', 'how do I integrate qual and quant findings', or 'is running both qual and quant enough to be mixed methods'.