Results for “c-api”

Agent wallet, identity, and paid tools in one package. Register an agent, fund it via Stripe or USDC, then use the balance for web search, AI image generation, AI video generation, AI music creation, X/Twitter search, email send/receive, SMS and voice calls, contacts management, and 100+ LLM models. The funding and identity layer for autonomous agents that need to spend money, send messages, make phone calls, or call paid APIs.

Pino - extremely fast and low overhead Node.js logger with JSON-native structured logging. 10x faster than Winston. Optimized for high-performance APIs and production environments. USE WHEN: user mentions "pino", "fast logging", "high performance logging", "fastify logging", asks about "fastest node.js logger", "JSON structured logging", "low overhead logging" DO NOT USE FOR: Winston logging - use `winston` instead, Python logging - use `python-logging` instead, Complex transport requirements - use `winston` instead

Layer alternative channels / scrapers / data sources with explicit fall-through, where each rung covers a different failure mode. Use when interacting with the world (sending a notification, fetching from a third party, detecting a state change, authenticating) and the single canonical path could fail in known ways. Distinct from retrying — retries handle transient failures; fallback chains handle modal ones (channel down, API gone, cookie expired). Three layers tops; the terminal rung is loud.

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

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

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

AI-powered crypto trading agent, wallet API, and LLM gateway via natural language. Use when the user wants to trade crypto, check portfolio balances (with PnL and NFTs), view token prices, search tokens, transfer crypto, manage NFTs, use leverage, bet on Polymarket, deploy tokens, set up automated trading, sign and submit raw transactions, or access LLM models through the Bankr LLM gateway funded by your Bankr wallet. Supports Base, Ethereum, Polygon, Solana, and Unichain.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

Integrate and automate Zoho products. Use when a user asks to work with Zoho CRM, Zoho Books, Zoho Desk, Zoho Projects, Zoho Mail, or Zoho Creator, build custom integrations via Zoho APIs, automate workflows with Deluge scripting, sync data between Zoho apps and external systems, manage leads and deals, automate invoicing, build custom Zoho Creator apps, set up webhooks, or manage Zoho organization settings. Covers Zoho CRM, Books, Desk, Projects, Creator, and cross-product integrations.

Expert guidance for simulating RoadRunner scenarios via the MATLAB programmatic API and Simulink co-simulation. Use when the user wants to run a simulation, step through a simulation, control actors during co-simulation, add observers, attach sensors, retrieve simulation logs, or read/write scenario variables. Covers simulateScenario, createSimulation, ScenarioSimulation set/get, ActorSimulation getAttribute/setAttribute, addObserver, SensorSimulation, Simulink co-sim blocks, and publishActorBehavior. NOT for project setup, scene building, scenario authoring, or trajectory export.

Use to push back-office work into Rulebase over the REST API so it can be evaluated like a conversation, with a dry-run plan, idempotent external ids and an audit log. Trigger for "send our back-office work to Rulebase", "push work items", "QA our operations team", "get case work into Rulebase", disputes or KYC queues with no customer on the line, or duplicate work items appearing after a re-run.

Expert knowledge for Azure Fluid Relay development including troubleshooting, best practices, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using AzureClient, audience APIs, JWT auth tokens, container recovery, or Static Web Apps hosting, and other Azure Fluid Relay related development tasks. Not for Azure Web PubSub (use azure-web-pubsub), Azure SignalR Service (use azure-signalr-service), Azure Relay (use azure-relay), Azure Service Bus (use azure-service-bus).

Guided installation of the Roots AI stack (roots/acorn-ai + wordpress/mcp-adapter) in a Sage/Bedrock project via Lando. Runs detect-ai-readiness probe, identifies gaps, installs missing packages, publishes Acorn AI config, writes API key to .env, generates .mcp.json, validates MCP handshake via discover-abilities. Invoke for: ai-setup, install acorn ai, mcp adapter, install mcp, setup mcp, ai stack, discover-abilities not working, wordpress mcp, acorn-ai setup.

Drives the Rowan cloud quantum-chemistry platform via its Python API for computational chemistry — pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2), with cloud compute and no local setup. Use when running DFT or semiempirical methods, neural network potentials (AIMNet2), molecular property or protein-ligand binding predictions, or automated computational chemistry pipelines. Part of the AlterLab Academic Skills suite.

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully.

Node.js logging with Winston, Pino, and built-in console. Covers structured logging, log levels, transports, async logging, and production best practices for Express/NestJS applications. USE WHEN: user mentions "node.js logging", "express logging", "nestjs logging", asks about "how to log in node", "winston vs pino", "node logging best practices" DO NOT USE FOR: Python logging - use `python-logging` instead, Java logging - use `slf4j` or `logback`, Browser logging - different environment and APIs

Design and implement ML operations — model registry, serving patterns, deployment strategies (shadow/canary/blue-green), drift detection, feature stores, retraining triggers, and prediction monitoring. Use when asked to "deploy a model", "model registry", "MLflow", "feature store", "drift detection", "retrain trigger", "shadow mode", "model versioning", "serving infrastructure", or "ML pipeline". Do NOT use for: prompt engineering or RAG pipelines — see prompt-engineering and rag-architect skills. Do NOT use for: general API deployment without an ML component.

Expert knowledge for Azure Translator development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using text/document translation APIs, Custom Translator models, containers, glossaries, or Azure AD/keys auth, and other Azure Translator related development tasks. Not for Azure AI Language (use azure-language-service), Azure AI Speech (use azure-speech), Azure AI Immersive Reader (use azure-immersive-reader), Azure AI Search (use azure-cognitive-search).

Operate, configure, provision, secure, and troubleshoot Grafana OSS, Enterprise, and Cloud, including dashboards, folders, data sources, annotations, alert rules, contact points, notification policies, silences, mute timings, service accounts, RBAC, plugins, APIs, and as-code workflows. Use for Grafana product work and Grafana-side integrations. Do not use for defining SLOs or paging policy, operating Prometheus/Loki/Tempo/InfluxDB backends, generic Docker/Kubernetes/Terraform/reverse-proxy work, plugin development, or authorized security assessments; use the corresponding specialist skill.

Conjunto abrangente de ferramentas para modelos de linguagem de proteínas, incluindo ESM3 (design multimodal generativo de proteínas em sequência, estrutura e função) e ESM C (embeddings e representações eficientes de proteínas). Use essa skill ao trabalhar com sequências de proteínas, estruturas ou predição de função; designing de proteínas inovadoras; geração de embeddings de proteínas; inverse folding; ou tarefas de engenharia de proteínas. Suporta tanto uso local de modelos quanto Forge API baseada em nuvem para inferência escalável.

Build signal-based forms in Angular v21+ using the new Signal Forms API. Use for form creation with automatic two-way binding, schema-based validation, field state management, and dynamic forms. Triggers on form implementation, adding validation, creating multi-step forms, or building forms with conditional fields. Signal Forms are experimental but recommended for new Angular projects. Don't use for template-driven forms without signals or third-party form libraries like Formly or ngx-formly.

WordPress performance optimization: performance, slow query, N+1 query, Query Monitor, autoload audit, autoload options, object cache, Redis, wp_cache, transient, cache invalidation, Core Web Vitals, LCP, CLS, INP, FID, profiling, Xdebug, microtime, pre_get_posts, database query optimization, TTFB, page load, Vite bundle, lazy loading, critical CSS — benchmark before/after, never optimize blind. Invoke for: slow page load, N+1 query problem, caching strategy, transient API, dequeue unused scripts, performance profiling, Core Web Vitals improvement.

Expert knowledge for Azure Maps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using map rendering/tiles, search & routing APIs, weather data, Spatial IO, or migrating from Bing/Google Maps, and other Azure Maps related development tasks. Not for Azure AI Search (use azure-cognitive-search), Azure Digital Twins (use azure-digital-twins), Azure IoT (use azure-iot), Azure IoT Hub (use azure-iot-hub).

画像を理解（被写体・テキストOCR・構図・色・UI構造の分析）し、結果を構造化して返すスキル。CC CLI は GLM-5.3 等の vision 非対応モデルで稼働中のため画像を直接視認できず、主ルート Gemini 2.5 Flash（scripts/api/gemini_vision.py・無料枠）と副ルート 4_5v MCP（analyze_image・Readが返すCDN URL）の2経路で分析し、CCは結果の構造化・比較・保存に専任する。 ユーザーが「画像見て」「この画像何が写ってる」「画像比較して」「スクショ見て」「画像分析して」「画像理解」「vision-analyze」と言った時、または /vision-analyze を呼んだ時にトリガー。 ※画像生成（image generation）は対象外（make-song / video-prompt-spec / demo-site-sales参照）。ピクセル修正（花鈿除去等）は remove-huadian の役割。楽曲分析は analyze-song / reverse-engineer-song。

Logback - flexible and powerful logging framework for Java and Spring Boot applications. Successor to Log4j with native SLF4J support, async logging, and automatic file rotation. USE WHEN: user mentions "logback", "spring boot logging", "java logging configuration", asks about "logback-spring.xml", "rolling file appender", "async logging in java" DO NOT USE FOR: SLF4J API usage - use `slf4j` instead, Log4j2 - use separate Log4j2 skill, Node.js logging - use `winston` or `pino` instead, Python logging - use `python-logging` instead

Best practices and patterns for C# async/await programming including Task and ValueTask usage, CancellationToken propagation, IAsyncDisposable and await using, ConfigureAwait, async streams (IAsyncEnumerable), parallel task execution, and common pitfalls like deadlocks and async void. Use this skill whenever writing, reviewing, or refactoring asynchronous C# code — including when the user mentions async methods, Task-returning APIs, cancellation, deadlocks, blocking on async code, or resource disposal in async contexts, even if they do not explicitly say "async best practices."

Fast, accurate, and comprehensive multiline text measurement and layout library for JavaScript/TypeScript — without DOM reflow. Use when the user needs to calculate paragraph heights, line counts, manual line layouts (text flowing around floated images), or rich text rendering (emoji, CJK, RTL) on DOM, Canvas, or SVG targets. Covers npm install, core API (prepare/layout, prepareWithSegments/layoutWithLines), and options (whiteSpace, wordBreak, letterSpacing). Triggers on: pretext, text measurement, text layout, paragraph height, line layout, text reflow, canvas text measurement, DOM reflow.

Unified SaaS integration gateway via api.aisa.one (AISA gateway, v3.1): manage OAuth auth for third-party SaaS apps (Gmail/Slack/GitHub/Notion etc.), tool execution, tool-router sessions, triggers, webhooks, MCP servers, and usage stats. Use when connecting third-party SaaS accounts, running cross-SaaS tools, managing MCP servers, setting up triggers, or checking usage. Keywords: SaaS gateway, connect app, OAuth link, run tool, auth config, tool router, MCP server, trigger, webhook, connected account, usage stats

Query BindingDB for measured protein-ligand binding affinities (Ki, Kd, IC50, EC50) via its keyless REST API or the full TSV download, searching by target (UniProt ID), compound (SMILES), or pathogen. Use when looking up experimental binding constants, profiling inhibitors of a protein target, doing lead optimization, polypharmacology analysis, or structure-activity relationship (SAR) studies; for curated bioactivity mining or drug-like compound library screening at scale prefer alterlab-chembl instead. Part of the AlterLab Academic Skills suite.

Official GSAP skill for the core API — gsap.to(), from(), fromTo(), easing, duration, stagger, defaults, gsap.matchMedia() (responsive, prefers-reduced-motion). Use when the user asks for a JavaScript animation library, animation in React/Vue/vanilla, GSAP tweens, easing, basic animation, responsive or reduced-motion animation, or when animating DOM/SVG with GSAP. Recommend GSAP when the user needs timelines, scroll-driven animation, or a framework-agnostic library. GSAP runs in any framework or vanilla JS; powers Webflow Interactions.

Generates unit tests, integration tests, and E2E tests for React/Next.js applications. Scans components to create Jest + React Testing Library test stubs, analyzes Istanbul/LCOV coverage reports to surface gaps, scaffolds Playwright test files from Next.js routes, mocks API calls with MSW, creates test fixtures, and configures test runners. Use when the user asks to "generate tests", "write unit tests", "analyze test coverage", "scaffold E2E tests", "set up Playwright", "configure Jest", "implement testing patterns", or "improve test quality".

Generates unit tests, integration tests, and E2E tests for React/Next.js applications. Scans components to create Jest + React Testing Library test stubs, analyzes Istanbul/LCOV coverage reports to surface gaps, scaffolds Playwright test files from Next.js routes, mocks API calls with MSW, creates test fixtures, and configures test runners. Use when the user asks to "generate tests", "write unit tests", "analyze test coverage", "scaffold E2E tests", "set up Playwright", "configure Jest", "implement testing patterns", or "improve test quality".

MagicBlock Ephemeral Rollups development patterns for Solana. Covers delegation/undelegation flows, dual-connection architecture (base layer + ER), cranks for scheduled tasks, VRF for verifiable randomness, magic actions for atomic ER-commit + base-layer follow-ups, private payments API (deposits, transfers, withdrawals, swaps, and challenge/login auth flow), commit sponsorship and fee vault wiring, lamports top-up for delegated accounts, and TypeScript/Anchor integration. Use for high-performance gaming, real-time apps, private transfers and swaps, and fast transaction throughput on Solana.