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Found 549 Skills
Route a vague Prisma Next prompt to the right specific skill. Use for "help me with Prisma Next", "what is Prisma Next", "explain Prisma Next", "I'm new to PN", "where do I start", "what can I do with Prisma Next", "what can I do next with Prisma", "just ran createprisma", "tour of Prisma Next", "Prisma Next overview", and comparison questions like "Prisma Next vs Prisma 7", "PN vs Drizzle", "PN vs Kysely", "PN vs TypeORM". Do NOT use when the prompt clearly matches a workflow skill — adoption / quickstart / first-touch orientation / brownfield introspection, schema / contract editing, migration authoring (db update / migration plan / migrate), migration review on deploy / concurrent migrations, queries / db.orm / db.sql / TypedSQL, runtime / db.ts / middleware wiring, build / Vite plugin / Next.js plugin, debug / structured error envelopes / PN-* error codes, or feedback / bug report / feature request — load that sibling skill directly.
Propose and execute rubric or bucket upgrades. Two modes: **Full rubric bump** (highest-risk action, mandatory 5-step process + cross-model audit) and **--bucket-only lightweight recalibration** (only update bucket boundaries, no changes to rubric formulas). **Phase 2 mandates using cheat-score-blind sub-agent to re-score the calibration pool** — self-scored fallback is not accepted. Trigger phrases: "upgrade rubric"/"bump rubric"/"update formula"/"I want to add a dimension"/"adjust weights"/"recalibrate bucket"/"recalibrate bucket".
Update financial models with new data — quarterly earnings, management guidance, macro changes, or revised assumptions. Adjusts estimates, recalculates valuation, and flags material changes. Use after earnings, guidance updates, or when assumptions need refreshing. Triggers on "update model", "plug earnings", "refresh estimates", "update numbers for [company]", "new guidance", or "revise estimates".
Builds Moran's I spatial autocorrelation workflows in CARTO. Triggers when the user mentions spatial autocorrelation, Moran's I, spatial dependency, spatial correlation, spatial outliers, HH HL LH LL quadrants, high-high clusters, low-low clusters, spatial weight matrix, "is there clustering", "are values spatially correlated", local indicators of spatial association, LISA, spatial randomness test, or wants to determine whether a variable exhibits spatial clustering, dispersion, or randomness across a gridded dataset. Also relevant when the user needs to classify locations into cluster types (HH, HL, LH, LL) rather than just identifying hotspots and coldspots.
Autonomous research agent that reads RESEARCH.md, infers what's needed, dynamically adjusts TODOs, and delegates to the right skill. Supports opt-in BFS mode for autonomous design space search. Respects a configurable supervision policy (presets: manual / checkpointed / autonomous / wild) governing notifications, approval gates, resource limits, and idea-change handling. Proactively surfaces gaps and asks before acting. Trigger phrases: "start research", "continue project", "what's next?", "explore design space", "autoresearch".
Scaffold the Mimas agent instruction file tree for any repository — AGENTS.md at root, subdomain CONTEXT.md files, and the full agents-docs/ hierarchy (a sibling of any existing docs/, kept separate so human-maintained project docs stay untouched). Every file is tailored to the repo's actual tech stack, git platform, and conventions. Use this skill whenever someone wants to set up agent instructions, onboard a repo for AI-assisted development, add AGENTS.md / CONTEXT.md files, create engineering docs for agents, or mentions "set up agentic repository" or "mimas template". Even if they just say "set up this repo for agents" or "add agent docs", this is the skill to use.
Scaffold and maintain a reusable research → design → plan → orchestrate → act folder for any non-trivial work — software features, marketing campaigns, org changes. Drops a domain-agnostic spine (00-README · 01-plan · 02/03 research · 04-discussion newest-first · 05-tracking · 09-orchestration · artifact/board.html plan-board) plus stateless action-skills that augment the docs in place without clobbering hand-written prose. Composes ikenga-artifact-builder, huashu-design, frontend-design, ikenga-pkg-builder when present; degrades gracefully when not. Profile-driven: `software` (rich default, code work), `general` (lean, non-code — campaigns, org changes), and `content` (editorial/marketing with key art). TRIGGER when the user asks to start a real plan for non-trivial work ("plan a feature," "scaffold a plan folder," "set up groundwork for…"), references an existing plans/ folder by groundwork structure, or runs any of these actions: groundwork init / research / design / review / clarify / orchestrate / refresh-board / refresh-living-spec / status. DO NOT TRIGGER for one-off code changes, single-document writeups, ADRs, or content that fits in a single markdown file — those don't need a multi-doc plan folder. If the user just wants a single artifact (dashboard, mockup), route to ikenga-artifact-builder instead.
Primarily the agent's internal-thinking skill — invoke it silently to model a problem, identify trade-offs, and decide what to do, BEFORE asking the user anything or dispatching another skill. Workflow skills call `/culture` as their step-1 reasoning pass; the agent does not surface the dialogue. Only treat this as a user-facing skill when the user has explicitly opted out of writes — phrases like "no writes", "just rubber-duck this", "let's only talk", "/culture". In the user-facing path the output is conversation; the only sanctioned artifact is an opt-in `.cheese/notes/<slug>.md` handoff slug at session end if the user asks for notes. Culture never writes to production code, never commits, never opens PRs. If the dialogue reveals real work, recommend `/mold` (fuzzy → spec) or `/cook` (clear ask → code) and stop. Before `/mold` or `/cook`.
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
Expert in building and selling Notion templates as a business - not just making templates, but building a sustainable digital product business. Covers template design, pricing, marketplaces, marketing, and scaling to real revenue. Use when: notion template, sell templates, digital product, notion business, gumroad.
Create visual parameter tuning panels for iterative adjustment of animations, layouts, colors, typography, physics, or any numeric/visual values. Use when the user asks to "create a tuning panel", "add parameter controls", "build a debug panel", "tweak parameters visually", "fine-tune values", "dial in the settings", or "adjust parameters interactively". Also triggers on mentions of "leva", "dat.GUI", or "tweakpane".
Evaluates student code submissions based on conceptual mastery rather than just correctness. Use to provide high-quality educational feedback on architectural patterns and programming logic.