Coding & Dev Tools Agent Skills

当面临信息过载或想法过多，需要筛选出值得投入资源（时间、精力）去执行的高价值想法时

当遇到令人情绪激动或陷入僵局的情境，需要跳出固有反应模式以做出更优决策时

当需要明确个人或组织想要避免的未来状态，以激发行动力时

当在线业务的一个环节（如产品、内容）运行后，需要系统性地收集反馈并驱动整体优化时

当需要进入高效、创造性的深度工作状态，并将工作体验从“压力”转化为“有挑战的游戏”时

当感到生活混乱、压力大、注意力分散，希望系统性地优化心智资源分配以提升创造力和生活体验时

当需要快速掌握一门新技能或知识领域，且希望通过实践而非单纯理论学习时

Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum...

Launch RSVP speed reader for text

Guia abrangente para Manim Community - framework Python para criar animações matemáticas e vídeos educacionais com controle programático

Adicionar, visualizar ou remover domínios para serviços Railway. Use quando o usuário quer adicionar um domínio, gerar um domínio railway, verificar domínios atuais, obter a URL de um serviço ou remover um domínio.

Padrões da biblioteca de componentes Material-UI v7 incluindo estilização com sx prop, integração de tema, design responsivo e hooks específicos do MUI. Use ao trabalhar com componentes MUI, estilização com sx prop, personalização de tema ou utilitários MUI.

Framework de computação quântica para construir, simular, otimizar e executar circuitos quânticos. Use esta skill ao trabalhar com algoritmos quânticos, design de circuitos quânticos, simulação quântica (com ou sem ruído), execução em hardware quântico (Google, IonQ, AQT, Pasqal), otimização e compilação de circuitos, modelagem e caracterização de ruído, ou experimentos e benchmarking quântico (VQE, QAOA, QPE, randomized benchmarking).

Kit de ferramentas para arquivos genômicos. Leia/escreva alinhamentos SAM/BAM/CRAM, variantes VCF/BCF, sequências FASTA/FASTQ, extraia regiões, calcule cobertura, para pipelines de processamento de dados NGS.

Use esta competência ao trabalhar com matemática simbólica em Python. Esta competência deve ser usada para tarefas de computação simbólica incluindo resolução de equações algebraicamente, realização de operações de cálculo (derivadas, integrais, limites), manipulação de expressões algébricas, trabalho com matrizes simbolicamente, cálculos de física, problemas de teoria dos números, computações de geometria e geração de código executável a partir de expressões matemáticas. Aplique esta competência quando o usuário precisa de resultados simbólicos exatos em vez de aproximações numéricas, ou ao trabalhar com fórmulas matemáticas que contêm variáveis e parâmetros.

Escreva código C eficiente com gerenciamento adequado de memória, ponteiros

Kit de ferramentas abrangente de computação quântica para construir, otimizar e executar circuitos quânticos. Use quando trabalhar com algoritmos quânticos, simulações ou hardware quântico, incluindo (1) Construção de circuitos quânticos com portas e medições, (2) Execução de algoritmos quânticos (VQE, QAOA, Grover), (3) Transpilar/otimizar circuitos para hardware, (4) Executar em IBM Quantum ou outros provedores, (5) Química quântica e ciência dos materiais, (6) Aprendizado de máquina quântico, (7) Visualizar circuitos e resultados, ou (8) Qualquer tarefa de desenvolvimento de computação quântica.

Modelagem metabólica baseada em restrições (COBRA). FBA, FVA, knockouts de genes, amostragem de fluxo, modelos SBML, para análise de biologia de sistemas e engenharia metabólica.

Filtros de química medicinal. Aplique regras de similaridade a fármacos (Lipinski, Veber), filtros PAINS, alertas estruturais, métricas de complexidade, para priorização de compostos e filtragem de bibliotecas.

Build throwaway code that answers exactly one design question — a tiny terminal app to feel out logic/state models, or several radically different UI variants switchable on one route. Use when the user wants to "prototype", "mock up", "sketch", "try a few versions", "see what it'd look like", "feel out this state machine", or is stuck choosing between designs they can only judge by seeing or driving them. Also used by the whiteboard skill for napkin-type tickets.

Show the quick-reference guide for the whiteboard planning system (whiteboard, hot-seat, napkin, connotation-cop) — the flow, what to say, and the rules. Use when the user asks "whiteboard help", "how do I use the whiteboard", "what's the flow", "remind me how whiteboard works", "which skill do I use", or seems unsure how to start or continue a whiteboard effort. This skill only DISPLAYS the guide — it never starts a board, resolves tickets, or does any work.

Flip a problem, goal, or decision 180 degrees to find what forward thinking misses. Asks what would guarantee failure, then works backward to what must be avoided or changed. Load when the user says "invert this", "flip this problem", "what would guarantee failure", "think backward", "reverse engineer the goal", "think about it backwards", or when deep-thinking diagnoses an inversion frame. Also triggers on "what's the opposite of success here", "how would we sabotage this". Two methods: Failure Inversion and Opposite Goal. Max 2 clarifying questions before inverting. Always returns forward actions. For broader analysis, deep-thinking calls this.

Run a pre-mortem — imagine the project has already failed one year from now and work backward to find the root causes before they happen. Load when the user asks for a pre-mortem, wants to imagine failure before committing, asks "what could go wrong before we start", "assume this fails — why", "risk analysis before launch", "what kills this project", "what could go wrong", or when deep-thinking diagnoses a pre-mortem frame. Based on Gary Klein's prospective hindsight method, which surfaces failure causes more effectively than forward risk analysis. Most useful right before a major commitment.

Apply one logical code change with mandatory impact mapping, git snapshot, verification, and automatic revert on failure. Load when the user asks for a safe edit, verified change, one change at a time with rollback, or codespine-style edit loop. Also triggers on "safe change", "edit with verification", "don't break the build", "revert if tests fail", or any non-trivial code edit where blast radius matters. Always runs dependency-mapping first. Pairs with incremental-implementation for multi-slice work; this skill is one atomic verify cycle per invocation.

Capture durable project memory from work, debates, debugging discoveries, learned conventions, deferred options, and session outcomes. Load when the user says remember this, save this learning, record what happened, update project memory, or preserve context for future agents.

Score an unbuilt business idea on desirability, viability, feasibility, distribution wedge, why-now, founder-market-fit, market size, alternatives, defensibility, capital intensity, and regulatory/ethical risk — and return a GO / ITERATE / KILL verdict with kill criteria and a next kill test. Load when the user asks to evaluate a business idea, score a startup idea, screen an idea, decide whether to pursue this venture, do an idea review, or says "is this a good business idea", "should I build this", "evaluate this startup", "screen this idea", "go/no-go on this idea", "kill or pursue". Sub-skill of `venture-exploration`. Calls `fermi` for sizing, `assumption-mapping` for hidden beliefs, optional `pre-mortem` / `adversarial-hat` for high-stakes ideas. Does NOT evaluate built products — for that use `reality-check`.

Record durable project decisions with rationale, alternatives, assumptions, status, and revisit triggers. Load when the user says record this decision, we decided, decision log, why did we choose, revisit this later, or capture architectural/process rationale.

Analyse experiment results, run validity checks (SRM, exposure parity, data integrity, novelty/primacy), interpret causally, make a ship/iterate/kill decision against the pre-declared rule, and append to cumulative learnings. Forces honest readouts — strips significance claims from underpowered or peek-violating tests; never lets directional results masquerade as causal wins. Load when results exist, or when the user says "read out this experiment", "analyse the test", "did the test win", "interpret the results", "what did we learn", "ship or kill", or when the experimentation orchestrator routes here.

Imported skill app from langchain

Imported skill parser from vercel

Imported skill diff from langchain

Imported skill package from vercel

Imported skill graph from langchain

Imported skill store from langchain

Imported skill validate from vercel

Imported skill memory from langchain