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Found 466 Skills
Interview about a plan file to refine it through in-depth questioning. Use when you have a plan that needs validation, refinement, or deeper exploration before implementation. Triggers on "interview me about", "refine this plan", "question this spec".
Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models via HTTP API.
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.
Generate probability-weighted alternative options that challenge default thinking. Forces unconventional alternatives and exposes hidden assumptions behind the "obvious" choice. For decision-point analysis, NOT full design exploration (use brainstorming for that). Triggers on "대안", "alternatives", "옵션 뽑아", "options", "어떤 방법이", "아이디어", "다른 방법", "선택지".
Prospective failure analysis using Gary Klein's swing-mortem technique. Assumes complete failure, works backward to identify risks, leading indicators, and circuit breakers. Counters optimism bias by forcing systematic exploration of failure modes before they materialize. Use for project plans, architecture decisions, technology adoption, business strategy, or feature launches. Triggers on "리스크", "위험", "실패하면", "swing-mortem", "뭐가 잘못될 수 있어", "risk", "what could go wrong", "걱정되는 점", "failure modes", "리스크 분석", "위험 분석".
Deploys Jupyter notebooks on TrueFoundry infrastructure with optional GPU support. Use when launching JupyterLab environments, setting up ML development workspaces, or running cloud-hosted notebooks for data exploration.
Trier un bug ou une issue en explorant le codebase pour trouver la cause racine, puis créer une issue GitLab ou GitHub avec un plan de correction basé sur le TDD. À utiliser quand l'utilisateur signale un bug, veut créer une issue, mentionne « triage » ou veut investiguer et planifier la correction d'un problème.
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.
Apply Smith and Lewis's paradox theory to identify and manage organizational tensions across performing, organizing, belonging, and learning dimensions. Use this skill when the user needs to diagnose persistent either/or tensions, design dynamic equilibrium strategies that embrace both poles, or when they ask 'why does solving this problem make it worse', 'how do we pursue exploration AND exploitation simultaneously', or 'why do our strategic tensions keep recurring despite resolution attempts'.
Create structured plans for any multi-step task -- software features, research workflows, events, study plans, or any goal that benefits from structured breakdown. Also deepen existing plans with interactive review of sub-agent findings. Use for plan creation when the user says 'plan this', 'create a plan', 'write a tech plan', 'plan the implementation', 'how should we build', 'what's the approach for', 'break this down', 'plan a trip', 'create a study plan', or when a brainstorm/requirements document is ready for planning. Use for plan deepening when the user says 'deepen the plan', 'deepen my plan', 'deepening pass', or uses 'deepen' in reference to a plan. For exploratory or ambiguous requests where the user is unsure what to do, prefer ce-brainstorm first.
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.
Build high-quality visual Web artifacts using HTML/CSS/JavaScript/React — web pages, landing pages, dashboards, interactive prototypes, HTML slide decks, animated demos, UI mockups, data visualizations, and more. Use this skill whenever the user's request involves a visual, interactive, or front-end deliverable, including: - Creating web pages, landing pages, dashboards, marketing pages - Building interactive prototypes or UI mockups (with device frames) - Building HTML slide decks / presentations - Creating CSS/JS animations or timeline-driven animated demos - Turning design mockups, screenshots, or PRDs into interactive implementations - Data visualization (Chart.js / D3, etc.) - Design system / UI Kit exploration Even if the user doesn't explicitly say "HTML" or "web page," this skill applies whenever the intent is to produce something visual, interactive, or presentational. Not applicable: pure back-end logic, CLI tools, data-processing scripts, non-visual code tasks, command-line debugging.