Topic: claude-code
35,830 skills in this topic.
-
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
ReinaMacCredy/maestro 26
-
maestro:research
Structured research workflow for maestro features. Guides tool selection across three tiers (codebase exploration, Context7 for library docs, NotebookLM for deep analysis), defines research patterns, finding organization via memory_write, and completion criteria. Use during the research pipeline stage after feature_create and before plan_write. Also use when investigating a problem space, comparing technical approaches, gathering context on unfamiliar code, or needing to understand external library APIs before making architectural decisions.
ReinaMacCredy/maestro 26
-
maestro:plan-review-loop
Deep-review any plan (maestro, Codex, Claude Code plan mode, or plain markdown) using iterative subagent review loops with BMAD-inspired adversarial edge-case discovery. Spawns reviewer subagents that find issues using pre-mortem, inversion, and red-team techniques, auto-fixes them with structured fix strategies, and re-reviews until the plan passes with zero actionable issues. Use when the user says 'review the plan', 'deep review', 'check the plan thoroughly', 'review loop', 'validate before approving', or wants rigorous plan validation before execution. Also use proactively before plan-approve when the plan is complex or high-risk.
ReinaMacCredy/maestro 26
-
maestro:brainstorming
Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
ReinaMacCredy/maestro 26
-
maestro-v2-migration
Guide for working with maestroCLI's v2 architecture. Covers the context-to-memory rename, 4-state task model, plain file backend, pre-agent hooks, research phase, and memory promotion. Use when touching v2 code, encountering legacy patterns (e.g. 'context' instead of 'memory', old task states), adding new v2 features, or debugging v2 behavior. Also use when you see imports from adapters/fs/context, references to 'contextAdapter', or task states that don't match the 4-state model.
ReinaMacCredy/maestro 26
-
maestro-skill-author
Create, update, or debug maestro built-in skills. Covers SKILL.md frontmatter, reference directory structure, step-file architecture, build-time embedding, naming conventions, alias management, and registry validation. Use when creating a new maestro built-in skill, modifying an existing SKILL.md, adding reference files, debugging skill loading failures, updating the skills registry, or working on the skills full port. Also use when frontmatter validation fails, skills don't appear in skill-list, or reference files fail to load.
ReinaMacCredy/maestro 26
-
maestro-pipeline-test
Run a full end-to-end smoke test of all maestro CLI commands in a single session. Use this skill when testing the maestro pipeline, verifying tool installation, validating a maestro setup, or checking that all tool groups work (feature, plan, task, memory, meta, graph, handoff, search). Trigger on "test maestro", "smoke test", "pipeline test", "verify all tools", "run pipeline test", or whenever the user wants to confirm maestro is functioning correctly -- even if they just say "does it work?" in a maestro context.
ReinaMacCredy/maestro 26
-
maestro-dev
Development workflow for maestroCLI itself. Encodes the hexagonal architecture pattern (port -> adapter -> use-case -> command -> MCP tool -> test) and project-specific conventions. Use when implementing new maestro features, adding CLI commands, extending the MCP server, creating new adapters, modifying ports, writing use-cases, or debugging maestro's own code. Also use when you need to understand how maestro's layers connect or where to put new code.
ReinaMacCredy/maestro 26
-
cli-for-agents
Designs or reviews CLIs so coding agents can run them reliably: non-interactive flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure. Use when building a CLI, adding commands, writing --help, or when the user mentions agents, terminals, or automation-friendly CLIs.
ReinaMacCredy/maestro 26
-
project-analyzer
Analyzes project structure and generates appropriate Claude Code subagents based on detected tech stack
SawanoLab/adaptive-claude-agents
-
common
SawanoLab/adaptive-claude-agents
-
adaptive-review
SawanoLab/adaptive-claude-agents
-
skills
SawanoLab/adaptive-claude-agents
-
cli-ux-tester
Expert UX evaluator for CLIs, terminal tools, and developer APIs. Use when reviewing command usability, error messages, help systems, or developer experience.
ali5ter/claude-cli-ux-skill 1
-
google-maps-reviews-api-skill
This skill is designed to help users automatically extract reviews from Google Maps via the Google Maps Reviews API. Agent should proactively apply this skill when users request to find reviews for local businesses (e.g., coffee shops, clinics), monitor customer feedback for a specific brand or location, analyze sentiment of reviews for competitors, extract reviews for a chain of stores or services, track reputation of a local restaurant, gather user testimonials for a specific venue, conduct market research on service quality of local businesses, monitor reviews for a new retail location, collect feedback on public attractions or parks, identify common complaints for a specific service provider, research the best-rated places in a city, analyze recurring themes in reviews for a specific industry.
browser-act/skills 135
-
google-maps-api-skill
This skill helps users automatically scrape business data from Google Maps using the BrowserAct Google Maps API. Agent should proactively trigger this skill for needs like finding restaurants in a specific city, extracting contact info of dental clinics, researching local competitors, collecting addresses of coffee shops, generating lead lists for specific industries, monitoring business ratings and reviews, getting opening hours of local services, finding specialized stores (e.g., Turkish-style restaurants), analyzing business categories in a region, extracting website links from local businesses, gathering phone numbers for sales outreach, mapping out service providers in a specific country.
browser-act/skills 135
-
google-image-api-skill
This skill helps users automatically extract structured image data from Google Images via BrowserAct API. Agent should proactively apply this skill when users express needs like finding images for specific keywords, gathering product style images for competitors, building visual datasets at scale, scanning visual search results for market research, tracking localized image trends by country, compiling related image thumbnails and links, extracting image titles and source logos, fetching click through URLs from image results, monitoring competitor visual assets, sourcing creative content for specific topics, looking up product pictures in different regions, collecting structured image metadata without opening detail pages.
browser-act/skills 135
-
browser-act
Browser automation CLI for AI agents with anti-detection stealth browsing, captcha solving, and parallel multi-browser support. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, scraping sites with bot detection, or automating any browser task. Also use when the user needs to connect to their existing Chrome session, configure proxy-based stealth browsing, or run parallel browser sessions. Triggers on requests to open a website, fill out a form, click a button, take a screenshot, scrape data from a page, login to a site, automate browser actions, handle captcha challenges, or any task requiring programmatic web interaction.
browser-act/skills 135
-
amazon-reviews-api-skill
This skill helps users automatically extract Amazon product reviews via the Amazon Reviews API. Agent should proactively apply this skill when users express needs like getting reviews for Amazon product with ASIN B07TS6R1SF, analyzing customer feedback for a specific Amazon item, getting ratings and comments for a competitive product, tracking sentiment of recent Amazon reviews, extracting verified purchase reviews for quality assessment, summarizing user experiences from Amazon product pages, monitoring product performance through customer reviews, collecting reviewer profiles and links for market research, gathering review titles and descriptions for content analysis, scraping Amazon reviews without requiring a login.
browser-act/skills 135
-
amazon-product-search-api-skill
This skill is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request searching for products related to keywords, finding best-selling items from specific brands, monitoring product prices and availability on Amazon, extracting product listings for market research, collecting product ratings and review counts for competitive analysis, finding specific products with a maximum count, searching Amazon in different languages for localized results, tracking monthly sales estimates for brand products, gathering product URLs and titles for a product catalog, scanning Amazon for Best Seller tags in a specific category, monitoring shipping and delivery information for brand items, building a structured dataset of Amazon search results.
browser-act/skills 135
-
amazon-product-api-skill
This skill helps users extract structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications. Use this skill when users want to search for products on Amazon, find the best selling brand products, track price changes for items, get a list of categories with high ratings, compare different brand products on Amazon, extract Amazon product data for market research, look for products in a specific language or marketplace, analyze competitor pricing for keywords, find featured products for search terms, get technical specifications like material or color for product lists.
browser-act/skills 135
-
amazon-competitor-analyzer
Scrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
browser-act/skills 135
-
amazon-buy-box-monitor-api-skill
This skill helps users extract basic product details other sellers prices and seller ratings from Amazon via ASIN automatically using the BrowserAct API. Agent should proactively apply this skill when users express needs like query Amazon buy box information, monitor Amazon product prices, extract Amazon product details by ASIN, check other sellers prices on Amazon, get Amazon seller ratings and feedback count, monitor buy box ownership for a specific ASIN, track Amazon fulfillment methods for competitors, compare Amazon product prices across different sellers, retrieve Amazon buy box availability status, analyze Amazon seller profile details.
browser-act/skills 135
-
amazon-best-selling-products-finder-api-skill
This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.
browser-act/skills 135