Results for “base”

Expert skill for building web-based game engines and games using HTML5, Canvas, WebGL, and JavaScript. Use when asked to create games, build game engines, implement game physics, handle collision detection, set up game loops, manage sprites, add game controls, or work with 2D/3D rendering. Covers techniques for platformers, breakout-style games, maze games, tilemaps, audio, multiplayer via WebRTC, and publishing games.

This skill should be used when the user asks to "swap tokens", "exchange ETH for USDC", "buy DEGEN", "sell tokens", "swap on Base", "trade crypto", "convert ETH to WETH", "exchange tokens", "token swap code", "0x routing", or any token swap operation. Also use for questions about ERC20 approvals, allowanceTarget, swap transaction execution, or building swap transactions with the Bankr SDK.

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.

Bidirectional conversion between Elm and Roc. Use when migrating projects between these languages in either direction. Extends meta-convert-dev with Elm↔Roc specific patterns. Use when migrating Elm frontend code to Roc applications, translating browser-based Elm to platform-agnostic Roc, or refactoring Elm web applications to Roc CLI/native tools. Extends meta-convert-dev with Elm-to-Roc specific patterns.

Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.

Run a standard Claude Code review of local git changes in this repository. Args: --wait, --background, --base <ref>, --scope <auto|working-tree|branch>, --model <model>, --effort <low|medium|high|xhigh|max>. Defaults to opus + xhigh effort. Use as the default path for ordinary code-review requests when the user did not explicitly ask for stronger adversarial scrutiny or for Claude to own the implementation work.

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Use this skill when the user requests to generate, create, write, or draft a newsletter, email digest, weekly roundup, industry briefing, or curated content summary. Supports topic-based research, content curation from multiple sources, and professional formatting for email or web distribution. Trigger on requests like "create a newsletter about X", "write a weekly digest", "generate a tech roundup", or "curate news about Y".

SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if claude-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster plan".

Differentiates aldosterone-producing adenoma from idiopathic adrenal hyperplasia based on 18-hydroxycorticosterone levels, with APA patients generally having levels >100 ng/dL at 8:00 a.m. and IAH patients usually having levels <100 ng/dL. Use when reviewing 18-OHB test results to help subtype PA; triggers include 18-OHB >100 ng/dL (suggesting APA) or <100 ng/dL (suggesting IAH).

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

Publication Specialist - Writing, Review, Pre-registration & Quality Assurance Light VS applied: Avoids template-based writing + audience-specific message design Absorbed G3 (Peer Review Strategist), G4 (Pre-registration Composer), F1-F3 (Quality functions) capabilities Use when: writing abstracts, creating summaries, peer review response, pre-registration, reporting checklists, reproducibility Triggers: abstract, plain language, press release, summary, communication, peer review, revision, pre-registration, OSF, PRISMA, CONSORT, reproducibility

AI/LLM red-team assessment using the OWASP LLM Top 10 (2025) + OWASP AI Testing Guide (AITG v1, Nov 2025) frameworks, plus OWASP MCP Top 10 runtime testing for agentic/MCP targets. Tests prompt injection, jailbreaks, system prompt leakage, sensitive data extraction, excessive agency, improper output handling, model extraction, content bias, evasion, membership inference, MCP token exposure, MCP command injection, and more. Uses four tools in combination: FuzzyAI (single-turn jailbreak fuzzing), PyRIT (multi-turn orchestrated attacks), Garak (probe-based vulnerability scanning), and promptfoo (plugin-based red-team evaluation). Each tool covers different OWASP categories; running them together gives systematic coverage. Includes a conditional MCP reconnaissance phase and a post-access AI infrastructure phase (chained from /post-exploit). Produces: OWASP LLM Top 10 + AITG + MCP coverage matrix, findings per category, architecture diagram of the AI system, PoCs for confirmed exploits. Chains into /gh-export for

Comprehensive toolkit for protein language models including ESM3 (generative multimodal protein design across sequence, structure, and function) and ESM C (efficient protein embeddings and representations). Use this skill when working with protein sequences, structures, or function prediction; designing novel proteins; generating protein embeddings; performing inverse folding; or conducting protein engineering tasks. Supports both local model usage and cloud-based Forge API for scalable inference.

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Integrates Alchemy blockchain APIs using an API key. Requires $ALCHEMY_API_KEY to be set; if unavailable, use the alchemy-agentic-gateway skill instead. Use when user asks about EVM JSON-RPC calls, token balances, NFT ownership or metadata, transfer history, token prices, portfolio data, transaction simulation, webhooks, Solana RPC, or any Alchemy product integration. Covers base URLs, authentication, endpoint selection, pagination, and common patterns.

Interpreta métricas de copy e aponta o que fazer — conversão de landing, abertura e clique de e-mail, CTR e CPA de anúncio, engajamento de social. Use quando o usuário disser "analisar desempenho", "como foi a campanha", "os números do mês", "essa página não converte", "taxa de abertura caiu", "relatório de.

Interact with Hydrex liquidity pools on Base. Use when the user wants to lock HYDX for voting power, check voting power for gauge voting, vote on liquidity pool strategies, view pool information, check voting weights, participate in Hydrex governance, deposit single-sided liquidity into auto-managed vaults to earn Hydrex yields, claim oHYDX rewards from incentive campaigns, or exercise oHYDX into veHYDX. Uses Bankr for transaction execution.

TIGER v2 — Multi-scanner trading system for Hyperliquid perps via Senpi MCP. 5 signal patterns (BB compression breakout, BTC correlation lag, momentum breakout, mean reversion, funding rate arb), DSL v4 trailing stops, goal-based aggression engine, and risk guardrails. Configurable profit target over deadline. 12-cron architecture (10 TIGER + prescreener + ROAR meta-optimizer). Pure Python analysis. Requires Senpi MCP, python3, mcporter CLI, and OpenClaw cron system.

Mede o tamanho estrutural da feature ativa lendo requirements, duvidas, plan e tasks do ciclo forward, e gera size.json mais size.md com T-shirt sizing deterministico baseado em tasks e ajuste de risco. Use quando o usuario digitar "/reversa-pricing-size", "reversa-pricing-size", "dimensionar feature" ou "calcular tamanho da feature". Roda depois de `/reversa-to-do` e antes de `/reversa-pricing-estimate`.

Expert knowledge for Azure Attestation development including troubleshooting, best practices, security, configuration, and deployment. Use when validating attestation tokens, authoring policies, managing SGX/TPM baselines, or securing private endpoints, and other Azure Attestation related development tasks. Not for Azure Confidential Computing (use azure-confidential-computing), Azure Virtual Enclaves (use azure-virtual-enclaves), Azure Key Vault (use azure-key-vault), Azure Dedicated HSM (use azure-dedicated-hsm).

Autonomously optimize any Claude Code skill by running it repeatedly, scoring outputs against binary evals, mutating the prompt, and keeping improvements. Based on Karpathy's autoresearch methodology. Use when: optimize this skill, improve this skill, run autoresearch on, make this skill better, self-improve skill, benchmark skill, eval my skill, run evals on. Outputs: an improved SKILL.md, a results log, and a changelog of every mutation tried.

Write unit and integration tests for Angular v20+ applications using Vitest or Jasmine with TestBed and modern testing patterns. Use for testing components with signals, OnPush change detection, services with inject(), and HTTP interactions. Triggers on test creation, testing signal-based components, mocking dependencies, or setting up test infrastructure. Don't use for E2E testing with Cypress or Playwright, or for testing non-Angular JavaScript/TypeScript code.

Design system implementation in Sage/Tailwind v4 — Figma to @theme tokens, design tokens CSS, Tailwind v4 @theme, color tokens, typography tokens, spacing scale, Blade UI components, kitchensink page, design-to-code, @layer base @layer components, CSS custom properties, resources/css/app.css, Paper MCP, Figma MCP, design file to code, SVG icons, responsive layout, design system audit, UI component library, atom design, layout components

Executable documentation governance with compound engineering and abductive learning. Enforces the Seven Laws through type compilation, schema validation, and hookify-based enforcement. Implements programmatic compound engineering where K' = K ∪ crystallize(assess(τ)) for monotonic knowledge growth. Integrates abstracted abductive learning (OHPT protocol) for systematic debugging and pattern extraction. Trigger when writing code, debugging, establishing governance, or when mentioned vibecode, compound, abductive, or executable documentation. Self-validating and homoiconic.

Transform diverse inputs (YouTube videos/audio, existing Suno songs, raw lyrics, audio files, or conversational ideas) into highly optimized Suno V5 custom song generation prompts with intelligent character optimization (5000 lyrics, 1000 style limits), proven metatag reliability, V5-enhanced emotion tags, and template-based best practices. Use when user wants to create music with Suno, provides content for song generation, or needs help crafting effective V5 prompts.

Deploy and configure Xray proxy servers. Use when a user asks to set up VLESS, VMess, Trojan, or Shadowsocks proxies, configure Reality or TLS transport, deploy Xray with XTLS, set up fallback routing, manage multi-user access, configure traffic routing rules, set up CDN-based tunneling, build subscription links for client apps, monitor Xray traffic, or bypass network restrictions. Covers all major Xray protocols, transports, and deployment patterns.

Model interpretability and explainability with SHAP (SHapley Additive exPlanations) — feature importance and plots (waterfall, beeswarm, bar, scatter, force, heatmap). Use when explaining ML model predictions, computing feature importance, debugging models, analyzing bias or fairness, comparing models, or implementing explainable AI across tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model. Part of the AlterLab Academic Skills suite.

Interpretabilidade e explicabilidade de modelos usando SHAP (SHapley Additive exPlanations). Use essa skill ao explicar predições de modelos de machine learning, computar importância de features, gerar plots SHAP (waterfall, beeswarm, bar, scatter, force, heatmap), depurar modelos, analisar vieses ou justiça de modelos, comparar modelos ou implementar IA explicável. Funciona com modelos baseados em árvores (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), modelos lineares e qualquer modelo black-box.

Expert knowledge for Azure Boards development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, and integrations & coding patterns. Use when managing work items, queries/charts, GitHub links, Scrum boards/sprints, or WIQL-based integrations, and other Azure Boards related development tasks. Not for Azure DevOps (use azure-devops), Azure Test Plans (use azure-test-plans), Azure Pipelines (use azure-pipelines), Azure Repos (use azure-repos).

Takes an approved plan from docs/plans/ and drives it to an open PR. Implements it by milestones, commits per milestone in the repo's style, and opens the PR against the repo's base branch. Use whenever the user approves a plan, says "ship it", "go", "start", "implement it", "do it", or asks to open a PR for already-planned work — or in Spanish "dale", "arrancá", "implementalo", "hacelo".

Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, create PR. Use when asked to "ship", "deploy", "push to main", "create a PR", "merge and push", or "get it deployed". Proactively invoke this skill (do NOT push/PR directly) when the user says code is ready, asks about deploying, wants to push code up, or asks to create a PR. (gstack)

Audit, write, or revise .vale.ini, or work through vale findings on a repo. Use when adding Vale, troubleshooting silent passes or noisy findings, evolving config, or applying the suggestion → warning → error cleanup cascade after a vale run (interactive or pre-commit failure). Applies the two-hook pre-commit pattern (sync + lint), explicit Packages and per-format BasedOnStyles, scoping/ignores for false positives, and a shared accept.txt vocabulary.