Update docs/CHANGELOG.md from git history, GitHub releases, and code diffs. Use when: writing release notes, syncing the latest changelog entry, summarizing a new tag, or keeping changelog wording concise and consistent.

Product Owner + UX/UI Designer fusión v4 (post pm-redesign 2026-05 Punto 4). Toma 1 UI standard story (CRUD/list/detail/form/dashboard) state=refining → produce 01-spec.md UNIFICADO con Gherkin AI-resistant + wireframes inline (ASCII / HTML mockup / Figma link) + estados visuales + microcopy Spanish neutro + Playwright graders → transition state=refining→refined al ratificar. NO se usa para agentic-stories (use /ux-agentico) ni service-stories (use /po). Loop iterativo Chris hasta ratificación. Activa cuando user dice: '/po-ux', 'definamos esta historia UI', 'spec + diseño', 'pantalla CRUD', 'dashboard', 'form nuevo', 'list view', 'detail page', 'wireframe', 'mockup'.

Git and GitHub workflow assistant for Nicolify (ap_sales_agent). Creates and manages branches, handles pull requests, resolves merge conflicts, generates changelogs, and manages releases and deployments. Use when the user asks to "create a branch", "sync with github", "push changes", "merge to main", "create a release", "make a PR", "resolve conflicts", "check git status", "deploy to production", "create a version", "write a changelog", or any git/GitHub related task. Also triggers on "quiero hacer un commit", "quiero pushear", "hacemos un release", "pasamos a producción", "nueva versión", "rama nueva".

Offer Studio preset catalog expert (7th SSoT axis). Use when: adding a new preset, modifying an existing preset's sections or conditional questions, adding a new conditional question or flag, debugging 'why this section doesn't appear for tenant X', extending the preset layer to a new ExpertBusinessType, or coordinating preset changes with wizard/landing generator/sales-agent. Triggers: 'agregar preset', 'nuevo preset', 'modificar preset', 'nuevo tipo de oferta', 'nueva pregunta condicional', 'section en expertise', 'preset para este negocio', 'offer-type-preset', 'ExpertBusinessType nuevo', 'wizard preset picker', 'archetype surfacing'.

Explicit advanced workflow to inspect status, upload, or cautiously start/control local Bambu Lab printers through LAN FTPS/MQTT after validated G-code exists. Use only when the user asks for printer communication or physical print control.

Hardware product pipeline orchestrator (PRD → BOM → PCB → CAD → fabrication). Use FIRST for any request to design a hardware product, electronic device, PCB, or enclosure end-to-end. Routes to replicator-prd, replicator-parts, replicator-pcb, replicator-cad.

Evaluate the build trail of a PR — read the claude -p sessions the harness ran to build it, find where the project's context (Expert / AGENTS.md / skill / spec) served or failed the agents, then capture the learnings as evals (regression tests over the harness's own skills/context) and context fixes. Use when resolving a STUCK (diagnosis-first), auditing how a converged PR was built, or auditing a /learn memory PR. Human-driven and conversational — the trail-evaluating sibling of /evaluate-pr. Outcomes land on a branch (the PR's, or a fresh capture branch if you'll discard the PR) and reach memory via merge + /learn. Triggers - evaluate-sessions, evaluate sessions, review the build trail, diagnose stuck, audit how this was built, session observability.

One-time, guided setup of the local agent-first coding harness — the polling loop, the deterministic dispatcher, its config, the AGENTS.md contract, and the worktree provisioning that makes per-feature worktrees runnable. Use when a developer wants to set up, bootstrap, install, or initialize the coding harness for the first time in a project.

Meta skill for creating new SDD experts from domain documentation. Provide a markdown file path with domain knowledge + optional steering context. Automatically synthesizes references, generates signal scripts, validates, and registers in experts.md/signals.md catalogs. Single-prompt creation with follow-up tweaks. Triggers - create expert, new expert, make expert, expert for, domain expert, add expert (project)

One-time, guided setup of a standalone LLM-maintained wiki — a Karpathy "LLM Wiki" style knowledge base for a problem domain and your general architecture best practices. Scaffolds an external wiki vault (its own git repo) with /ingest, /query, /lint commands and a conventions doc. Use when a developer wants to start, create, bootstrap, or initialize a wiki / second-brain / knowledge base to understand a problem space before building. The front of the Human Loop's Understanding phase.

Enriches each user story's acceptance criteria with a "Relevant constraints" line pointing to the specific architecture decisions, implementation heuristics, design principles, and UI kit that apply to that story. Use this skill after any phase that introduces new constraints — after architecture decisions are written (Phase 3), after the UI kit is approved (Phase 4), and after implementation heuristics and design principles are established (Phase 5). Also invoke whenever a Phase 6 agent reads the acceptance criteria and lacks a clear picture of which constraints govern a particular story. Safe to re-run at any phase — each invocation only adds constraints not already listed; nothing is ever removed from an existing entry.

Transforms vague or ill-defined questions into clear, structured, and actionable "good problems" by extracting the core objective, identifying comparison dimensions, and applying structured reasoning. Use when a user wants to compare multiple options, evaluate trade-offs, make a decision between alternatives, or asks questions like "which is better", "pros and cons", "help me decide", "how should I choose", or "what are the trade-offs". Produces a rewritten problem statement with explicit comparison dimensions, a structured evaluation framework, and a decision-ready output format.

Use when driving one or more tasks end to end from the local bare repo's `main` worktree — a feature designed with the user first when its scope is open, or a ready list of tasks — ordering them, cutting a worktree per task, handing each to a subagent that runs new-feat, running prep-pr with every finding fixed rather than reported, and shepherding each pull request to a squash merge and worktree teardown. Not for a one-file change, and not outside the bare repo.

Provides access to a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.

Add new conference talks to the talks portfolio repository. Handles fetching metadata from sched.co URLs or manual input, generating talk directories with README.md files, fuzzy-matching slide PDFs from ~/Downloads/, and staging all changes. Use when user says "add talk", "new talk", "add these talks", provides sched.co URLs, or mentions adding a presentation or conference entry.

Curate an Oracle Forms modernization feature by reconciling extracted Oracle evidence, linked screenshots, a running target mockup, its Next.js implementation, existing canonical requirements, and accepted target architecture. Use when a target mockup must be converted or incrementally enriched into a review-ready feature requirement package plus an evidence-backed server-side implementation specification covering UI-to-data mappings, LOVs, validations, detailed decision rows for Delete, Add, Edit, and other operations, Oracle-constraint-to-application-message translations, transactions, tab dependencies, APIs, errors, security, and acceptance scenarios without inventing unsupported physical mappings.

Diagnose live bugs and incidents that require runtime evidence from a running service using Lightrun MCP. Use when static analysis or logs cannot explain the failure mechanism, when a hypothesis must be tested against live values or control flow, or when resuming Lightrun async actions. For latency, timeout, deadline, SLO, or hang diagnosis, use lightrun-slow-execution-diagnosis when available; if unavailable, continue here with best-effort evidence. Do not use for one-off production measurements (use lightrun-ask-prod when available; otherwise report the measurement-scope gap), pull-request review, code changes, setup, or deployment.

Overview and router for assistant-ui, the React library for building AI chat interfaces from composable primitives and a styled elements catalog. Use for high-level, cross-cutting, or architecture questions: choosing packages, picking a runtime, or understanding the layers (elements, primitives, the aui client with AuiConfig and AuiProvider, the runtime, adapters) and the message model. Covers `@assistant-ui/react` 0.15.x, `@assistant-ui/ai-sdk` for AI SDK v7 (`useChatRuntime`), `@assistant-ui/core`, `@assistant-ui/store`, `assistant-stream`, `assistant-cloud`, the LangGraph, LangChain, Google ADK, A2A, AG-UI, Eve, OpenCode, and Pi adapters, the `@assistant-ui/react-native` and `@assistant-ui/react-ink` bindings, and the `useAui`, `useAuiState`, and `useAuiEvent` hooks. For a specific area route to a focused sibling instead: setup, elements, primitives, runtime, tools, generative-ui, streaming, cloud, thread-list, copilots, markdown, react-mcp, observability, react-native, ink, or update.

Use this skill for Sprites — isolated, persistent cloud Linux environments from Fly.io with their own filesystem, URL, services, checkpoints, and network policy. Trigger it to create, list, exec into, or destroy sprites; to run builds, tests, or agents in a remote sandbox; to start long-running services and expose a preview URL; to snapshot and roll back state; to change outbound network rules; to call third-party APIs (GitHub, Slack, etc.) through the credential-injecting gateway; or whenever the user names Sprites, sprite-env, or sprites.dev. Works both from inside a sprite and from a machine outside one.

Act as the professional purchasing department for a household. Use this skill whenever someone asks what to buy, whether to buy, where to source it, when to buy, how much to order, how it should be delivered, or how much the household keeps in a year. Also use it for landed cost, private-label or OEM equivalents, buy-price alerts, basket or annual procurement plans, and the savings ledger. Use it when they mention a professional buyer, household procurement, annual savings, a buying brief, global or cross-border sourcing, delivery windows, or consolidating orders. This is not a coupon bot and not a sticker-price comparison.