“api”的搜索结果

通过 API 连接 X（Twitter），发布帖子和串联回复组成的长帖、上传图片、获取时间线与用户信息、搜索内容并追踪互动数据，同时处理认证、调用限制和权限错误。

• 通过 API 发布帖子、长帖和图片
• 获取时间线与用户信息
• 搜索特定话题或对话中的帖子

通过项目结构、API、数据访问和缓存示例，辅助设计、实现与审查Django应用，整理不同环境的配置及业务逻辑，并减少不必要的数据库查询。

• 整理Django项目结构与配置
• 设计Django REST Framework API
• 减少不必要的数据库查询

依据按编程语言分类的资料，协助开发和维护Claude应用。涵盖官方SDK调用、工具集成、模型迁移、费用检查、提示词审查和评估流程。

• 在应用中接入Claude API
• 开发使用自定义工具的智能体
• 为现有Claude集成迁移模型

Set spending limits, token quotas, and rate limits, which restrict requests over time. Review current consumption and apply controls per API key or globally to manage AI costs across providers.

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• Set spending limits for AI usage
• Assign token quotas per API key
• Review and update global rate limits

Automate AI ML API tasks through Rube MCP, a connection for accessing external tools. The skill guides tool discovery, connection checks, and execution using current input requirements, with guidance for bulk operations and paginated results.

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• Finding available AI ML API tools
• Checking the service connection before execution
• Running tools with their current input requirements

Design, build, debug, and optimize connections to external APIs. The skill covers REST, GraphQL, event notifications through webhooks, authentication, retries, request limits, and logging to help produce integrations whose failures can be traced.

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• Designing a new external API integration
• Building an API client with retries and authentication
• Investigating failed requests or missing results

Convert existing scripts, CLI tools, or Crawlee projects into reusable Apify Actors, programs packaged as Docker images. Define JSON inputs and outputs, integrate the SDK, test locally, and deploy to Apify.

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• Turning an existing script or CLI tool into an Actor
• Migrating a Crawlee project to Apify
• Defining JSON inputs and structured outputs

Guide authorized security assessments of REST, SOAP, and GraphQL APIs. Organize endpoint discovery, authentication checks, access control tests, and input testing, then document discovered weaknesses and evidence of unauthorized data access.

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• Plan API checks for an authorized bug bounty assessment
• Check whether users can access another account's records
• Review GraphQL schema exposure and request limits

Turn a system description into REST API endpoints, the URLs and operations applications use to exchange data. Choose an endpoint list or detailed specifications covering authentication, request fields, responses, error codes, and pagination for lists.

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• Listing the API endpoints a new system needs
• Drafting request and response specifications
• Designing authentication and error responses

Set up credentials and a development environment for your first Google Ads API request to retrieve campaigns. Choose from six official client libraries or direct HTTP requests, with guidance for account IDs, developer tokens, and common authorization errors.

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• Prepare credentials for a first Google Ads API integration
• Build an example that retrieves advertising campaigns
• Choose a client library or direct REST requests

Automate AI ML API tasks through Rube MCP, a connection for accessing external tools. The skill guides tool discovery, connection checks, and execution using current input requirements, with guidance for bulk operations and paginated results.

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• Finding available AI ML API tools
• Checking the service connection before execution
• Running tools with their current input requirements

Fill documentation gaps identified by a CARLA documentation audit, following the project's writing style. Work through one category at a time, assess which findings deserve entries, update source files, and report changes and skipped findings.

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• Add missing Python API documentation
• Expand sensor reference documentation
• Review outdated API entries for renaming or removal

Find user-configured API keys and tokens by listing their names and descriptions, then retrieve a chosen value for scripts. Helps use credentials in API calls or authentication without embedding them directly in code.

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• Check which credentials are configured for the current assistant
• Retrieve a configured API key for a script
• Get a token for git authentication

Test REST, gRPC, and WebSocket APIs for weaknesses in authentication, access controls, input handling, and configuration. Provides protocol-specific checks, tool guidance, and detection indicators to help document reproducible findings and severity during authorized assessments.

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• Check access controls across users and roles
• Review token lifecycles and request limits
• Assess gRPC and WebSocket security

Review Apache Pinot changes against naming and API conventions, including public names, method signatures, REST endpoints, JSON fields, and documentation. Use it when adding or renaming elements exposed to other code or users.

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• Reviewing public class, method, or field names
• Checking new enum constants or DataType values
• Reviewing REST endpoints and JSON fields

Build and maintain Mintlify documentation sites by writing pages, organizing navigation, and creating API references. The skill guides edits to site settings, use of built-in components, consistency with existing content, and checks for broken links and build errors.

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• Adding guides to an existing documentation site
• Organizing navigation and site appearance
• Creating API references from OpenAPI

Test Android and iOS apps by capturing real app traffic and checking backend APIs. When traffic is blocked or cannot be replayed, use decompilation and runtime inspection to uncover endpoints, inspect secrets, or understand request signing.

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• Capturing mobile app traffic and testing backend APIs
• Finding hidden API endpoints and embedded credentials
• Investigating certificate pinning that blocks traffic inspection

Investigate exposed source maps, configuration files, Git history, and API specifications on websites. The skill guides source reconstruction and artifact inspection to identify leaked secrets, internal routes, and build details during the initial stages of security research.

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• Checking source maps for exposed source code
• Inspecting public configuration files and Git history
• Mapping API routes from Swagger and OpenAPI specifications

Configure XRequest for API calls and streaming responses, where data arrives in successive pieces. This skill covers request settings, authentication, debugging, and environment-specific handling of credentials for standalone requests or integration with chat providers.

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• Check whether an API endpoint responds
• Configure streaming responses for an AI chat app
• Connect a private API through a chat provider

Azure API Center SDK for .NET. Centralized API inventory management with governance, versioning, and discovery. Use for creating API services, workspaces, APIs, versions, definitions, environments, deployments, and metadata schemas. Triggers: "API Center", "ApiCenterService", "ApiCenterWorkspace", "ApiCenterApi", "API inventory", "API governance", "API versioning", "API catalog", "API discovery".

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语音转文字 (ASR) (语音转文字 (ASR / 语音识别 / Speech-to-Text) 应用工程 (从业者视角) — 选型、集成、优化语音转文字能力，尤其面向移动端、低成本、快速识别的场景。覆盖: (a) 引擎/API 地图 — 云端 API(OpenAI gpt-4o-transcribe / Whisper API、Deepgram、AssemblyAI、Google / Azure / AWS Transcribe、讯飞、字节火山、阿里、腾讯、百度) vs 开源模型(Whisper / faster-whisper / whisper.cpp / distil-whisper、NVIDIA NeMo Parakeet / Canary、阿里 FunASR / Paraformer / SenseVoice、Moonshine、Vosk、Kaldi / k2 / icefall) vs 端侧·移动 SDK(whisper.cpp + CoreML / Metal、iOS Speech framework、Android SpeechRecognizer、Picovoice、SenseVoice 端侧); (b) 准确率(WER / CER) × 延迟(RTF / 流式) × 成本 三角权衡与选型决策树; (c) 成本优化 playbook — 端侧免费 / 批量折扣 / VAD 裁静音 / 量化(int8 / ggml) / 蒸馏 / 自托管 break-even; (d) 移动端集成 — 端侧 vs 云、流式 vs 批量、断点检测(endpointing)、隐私 / 离线; (e) 后处理 — 标点 / 数字规整(ITN) / 说话人分离(diarization) / 时间戳。学派分歧: 云 API vs 端侧自托管、通用大模型(Whisper) vs 专用流式(RNN-T / Conformer)、闭源 API vs 开源、准确率派 vs 成本派、英文优先 vs 中文 ASR(FunASR / SenseVoice / 讯飞)。不含: 文字转语音(TTS / 语音合成，方向相反)、声纹识别 / 说话人验证为主业、语音 agent / 对话式 AI、ASR 模型训练科研深水区。) Master OS — automated mastery of 语音转文字 (ASR / 语音识别 / Speech-to-Text) 应用工程 (从业者视角) — 选型、集成、优化语音转文字能力，尤其面向移动端、低成本、快速识别的场景。覆盖: (a) 引擎/API 地图 — 云端 API(OpenAI gpt-4o-transcribe / Whisper API、Deepgram、AssemblyAI、Google / Azure / AWS Transcribe、讯飞、字节火山、阿里、腾讯、百度) vs 开源模型(Whisper / faster-whisper / whisper.cpp / distil-whisper、NVIDIA NeMo Parakeet / Canary、阿里 FunASR / Paraformer / SenseVoice、Moonshine、Vosk、Kaldi / k2 / icefall) vs 端侧·移动 SDK(whisper.cpp + CoreML / Metal、iOS Speech framework、Android SpeechRecognizer、Picovoice、SenseVoice 端侧); (b) 准确率(WER / CER) × 延迟(RTF / 流式) × 成本 三角权衡与选型决策树; (c) 成本优化 playbook — 端侧免费 / 批量折扣 / VAD 裁静音 / 量化(int8 / ggml) / 蒸馏 / 自托管 break-even; (d) 移动端集成 — 端侧 vs 云、流式 vs 批量、断点检测(endpointing)、隐私 / 离线; (e) 后处理 — 标点 / 数字规整(ITN) / 说话人分离(diarization) / 时间戳。学派分歧: 云 API vs 端侧自托管、通用大模型(Whisper) vs 专用流式(RNN-T / Conformer)、闭源 API vs 开源、准确率派 vs 成本派、英文优先 vs 中文 ASR(FunASR / SenseVoice / 讯飞)。不含: 文字转语音(TTS / 语音合成，方向相反)、声纹识别 / 说话人验证为主业、语音 agent / 对话式 AI、ASR 模型训练科研深水区。: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on 语音转文字 (ASR / 语音识别 / Speech-to-Text) 应用工程 (从业者视角) — 选型、集成、优化语音转文字能力，尤其面向移动端、低成本、快速识别的场景。覆盖: (a) 引擎/API 地图 — 云端 API(OpenAI gpt-4o-transcribe / Whisper API、Deepgram、AssemblyAI、Google / Azure / AWS Transcribe、讯飞、字节火山、阿里、腾讯、百度) vs 开源模型(Whisper / faster-whisper / whisper.cpp / distil-whisper、NVIDIA NeMo Parakeet / Canary、阿里 FunASR / Paraformer / SenseVoice、Moonshine、Vosk、Kaldi / k2 / icefall) vs 端侧·移动 SDK(whisper.cpp + CoreML / Metal、iOS Speech framework、Android SpeechRecognizer、Picovoice、SenseVoice 端侧); (b) 准确率(WER / CER) × 延迟(RTF / 流式) × 成本 三角权衡与选型决策树; (c) 成本优化 playbook — 端侧免费 / 批量折扣 / VAD 裁静音 / 量化(int8 / ggml) / 蒸馏 / 自托管 break-even; (d) 移动端集成 — 端侧 vs 云、流式 vs 批量、断点检测(endpointing)、隐私 / 离线; (e) 后处理 — 标点 / 数字规整(ITN) / 说话人分离(diarization) / 时间戳。学派分歧: 云 API vs 端侧自托管、通用大模型(Whisper) vs 专用流式(RNN-T / Conformer)、闭源 API vs 开源、准确率派 vs 成本派、英文优先 vs 中文 ASR(FunASR / SenseVoice / 讯飞)。不含: 文字转语音(TTS / 语音合成，方向相反)、声纹识别 / 说话人验证为主业、语音 agent / 对话式 AI、ASR 模型训练科研深水区。 problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「语音转文字」「语音识别」「asr」「speech to text」「stt」

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Guideline for designing, implementing, and verifying secure APIs following OWASP API Security Top 10 (2023) best practices. Use when the user wants to: (1) review API code or design for security vulnerabilities, (2) design a secure REST, GraphQL, or gRPC API architecture, (3) implement API authentication and authorization (OAuth2, JWT, API keys, mTLS), (4) configure rate limiting, input validation, or CORS, (5) audit API endpoints for BOLA, BFLA, or mass assignment vulnerabilities, (6) create API security checklists or verification plans, (7) fix API security bugs or harden existing APIs, (8) set up API security testing (OWASP ZAP, Schemathesis, Burp Suite), or (9) handle any API security concern including SSRF prevention, resource consumption limits, business flow protection, API inventory management, and secure third-party API consumption.

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Generate Zod v4 TypeScript schemas from OpenAPI (openapi.yaml / openapi.json) definitions. This skill exists because npm packages like openapi-zod-client do not support Zod v4 — Claude reads the YAML/JSON directly and writes the conversion. Use this skill whenever the user wants to convert OpenAPI/Swagger definitions to Zod schemas, generate TypeScript types from API specs, or create validation schemas from openapi.yaml. Trigger on keywords: 'openapi', 'swagger', 'zod', 'API schema', 'yaml to types', 'schema generation', 'validation generation'. OpenAPI定義からZodスキーマを生成するスキル。openapi.yamlから型を作りたい、APIスキーマをTypeScriptの型にしたい、Zodバリデーションを作りたい、といったリクエストで使う。「openapi」「swagger」「zod」「APIスキーマ」「yamlから型」「スキーマ生成」「バリデーション生成」などのキーワードが出たら積極的にこのスキルを使うこと。

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提供LLM API费用管理的设计示例，将按任务复杂度选择模型、记录预算、重试临时错误和缓存共用提示词结合起来，用于检查累计费用与调整调用方式。

• 检查LLM应用的API费用
• 按批处理难度选择模型
• 对照预算检查累计费用