Results for “search-tools”

Firecrawl gives agents and pipelines fast, reliable web context with strong search, scraping, and page-interaction tools. Umbrella skill that routes to firecrawl-search, firecrawl-scrape, and firecrawl-research, and documents install, credentials, and the keyless fallback.

Reference for configuring and using LangChain4j vector stores, covering setup, search, filtering, and ingestion.

Automate Serply operations through Composio's Serply toolkit via Rube MCP, with tool discovery and connection management.

Conducts multi-source web research using firecrawl and exa MCP tools, synthesizing findings into cited reports with source attribution.

Full-stack task execution pipeline — discovers tools via semantic search, routes to the right agent, then executes via GODMODE. Chains manus-tool-discovery → manus-orchestrator → godmode-system in sequence.

Manages files and folders in protocols.io workspaces: upload, download, search, organize, and delete files via the File Manager API.

Read, write, edit, list, copy, move, and search files directly using builtin tools, with fallback to Python or bash for complex operations.

Detects available memory tools and maps them to a structured memory system for cross-session recall, with file-based fallback.

Stays current on UI design patterns, tools, and frameworks by monitoring release notes and running targeted search queries.

Searches global company registrations via OpenCorporates and SEC EDGAR, offering tools to find companies, retrieve details, and locate SEC filings.

Automate Zoho Inventory tasks via Rube MCP (Composio): items, orders, warehouses, shipments, and stock management. Always search tools first for current schemas.

Routes tasks to locally installed CLI tools using semantic matching. Triggers on tasks requiring shell commands, file operations, code search, data processing, visualization, or external tool invocation. Uses cli-index for semantic routing.

Provides 25 paid HTTP endpoints on Base mainnet that bill agents per call in USDC for web search, AI analysis, crypto and stock data, SEC filings, company intelligence, news, sentiment scoring, and a macro dashboard, returning structured JSON.

Grounds legal drafting in verified government references across 29+ US, EU, and Canadian jurisdictions, with CLI tools for searching templates, fetching metadata, and generating contract scaffolds.

Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact). Deduplicates against CRM (Google Sheets). Supports Apollo API and MCP tools.

Conducts autonomous multi-source research using a planner/executor architecture and an MCP server, with tools for deep research, quick search, report writing, and source retrieval.

Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter.

Orchestrates evidence-based research across local PDFs, scholarly search, citation-context tools, web sources, and code repositories to produce traceable syntheses with counterevidence audits.

Queries real-time vulnerability intelligence from NIST NVD, CISA KEV, EPSS, and MITRE ATT&CK via a remote MCP server, offering seven tools for CVE lookup, search, and trending analysis.

Search reference implementations and code examples from Adobe's Block Collection and community Block Party for AEM Edge Delivery blocks, plugins, and build tools.

Runs comprehensive SEO audits and analysis for websites, covering technical SEO, content quality, schema markup, Core Web Vitals, local SEO, and AI search optimization using browser automation tools.

Report the brand's organic performance from fb.ai — Search Console clicks/impressions/positions plus AI-engine visibility (whether ChatGPT, Perplexity and friends cite the brand). All traffic-monitor tools are free, so there is no quota gate. Run weekly or monthly.

Navigate Oracle Cloud Infrastructure's Enterprise AI services: choose models, build agents with RAG and tools, estimate costs, secure access, and integrate with Oracle Database, APEX, and other platform services.

Read and extract content from any web page using a real Chrome browser — including SPAs, JavaScript-rendered sites, and complex dynamic pages. Use when fetching page content that headless tools can't render, searching the web, or reading fully rendered pages via your own browser.

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.

Expert knowledge for Azure Copilot development including troubleshooting, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when sizing VMs, generating Bicep/Terraform, configuring Cosmos DB storage, or debugging App Service/VM disks, and other Azure Copilot related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Search (use azure-cognitive-search), Azure AI Bot Service (use azure-bot-service).

Search and deploy services from Railway's template marketplace. Use when user wants to add a service from a template, find templates for a specific use case, or deploy tools like Ghost, Strapi, n8n, Minio, Uptime Kuma, etc. For databases (Postgres, Redis, MySQL, MongoDB), prefer the railway-database skill.

Search and deploy services from Railway's template marketplace. Use when user wants to add a service from a template, find templates for a specific use case, or deploy tools like Ghost, Strapi, n8n, Minio, Uptime Kuma, etc. For databases (Postgres, Redis, MySQL, MongoDB), prefer the railway-database skill.

Route active project/repo memory requests into one honest packet: memory-layer choice, load-context, search-context, store-conclusions, setup-integration, or repo-packer route-out. Use when agents need searchable decisions, manifests, stable links, handoff notes, and small “read this first” packets across sessions. Route long-lived markdown knowledge bases to `llm-wiki`, structural graph memory to `graphify`, human-authored vault organization to note/vault skills, and one-shot repo packing to tools like Repomix, Gitingest, or Code2Prompt.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

Search, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

Import/export textures crash-safely, query the Content Browser selection, and check if an asset is open (AssetDiscoveryService). Search, load, save, move, rename, duplicate, and delete assets are handled by Unreal's native AssetTools toolset or EditorAssetLibrary. Use when the user asks to import an image from disk, export a texture, query the Content Browser selection, or check whether an asset is open in an editor.

Systematic methodology for auditing the Hermes Skills Hub (and external sources) to identify gaps, overlaps, redundancies, and conflicts when building a skill library for any project. Covers browsing, targeted searching, cross-referencing with web/GitHub, comparing candidates against existing inventory, verifying install safety, and planning installation order. Use when starting a new project and assembling tools, or when evaluating whether to add external skills beyond what's currently installed.

Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)