365 skills · sorted by relevance
Collect an X conversation from its root post ID, including replies and nested replies visible to the logged-in account. Return structured text, author details, engagement counts, and reply relationships for reviewing discussions or preparing further analysis.
Collect posts from X profiles by username, choosing regular posts, posts with replies, or media posts. Receive structured text, author details, engagement counts, and media information for account research and content tracking.
Search Douyin videos by keyword and collect structured results with creator details, engagement counts, descriptions, hashtags, covers, and download links. Filter by posting period and sort by relevance, likes, or newest posts.
Collect used-item listings from Goofish searches, including titles, prices, images, seller locations, and interest counts. Filter by price or listing date and sort results to build lists for researching China's second-hand market.
Extract details from an Etsy listing URL, including displayed prices, product options and their price ranges, images, descriptions, shop information, ratings, and favorites. Use these records for competitor research or tracking individual listings.
Collect product listings from Etsy keyword search results, one page at a time. Gather titles, prices, ratings, shop names, and product links, with advertising and shipping indicators, to support competitor research and product comparisons.
Automates website navigation, form entry, and information extraction through browser commands. Helps test web applications, reuse saved login state, and capture screenshots, PDFs, or recordings of browser workflows for inspection and documentation.
Implement HTTP headers that pass GitHub Actions secrets through environment variables in gh-aw’s copilot engine. This reference explains secret extraction, generated MCP configuration, execution-step settings, and tests for keeping secret values out of configuration files.
Investigate file inclusion and path traversal flaws that let applications access unintended files. The skill guides checks for sensitive data exposure and possible code execution, using content evidence or repeatable indirect signals to avoid false positives.
Find scientific papers in PubMed by turning a research question into targeted search terms and synonyms. Collect titles, authors, abstracts, and identifiers into a structured paper list ready for relevance evaluation.
Deploy teams of AI agents on Flow Nexus and automate development, research, or data processing workflows. Define step dependencies and event triggers, assign suitable agents, and monitor progress, queues, and execution history.
Automate a real browser from the terminal to navigate pages, fill forms, extract data, and investigate interface problems. Use page snapshots to identify controls, and capture screenshots or traces, records of browser activity, for review.
Automate website navigation, form filling, clicks, data extraction, and screenshots through the browse CLI, a command-line tool. Choose a local browser or a remote Browserbase session to suit the website and task.
Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".
The English summary is being prepared. Showing the original description.
Organization-grade identity-fabric mapping: tenant/federation fingerprinting and the pre-auth user-ENUMERATION oracle methodology — enumeration and fingerprint only, never credential submission. Covers domain-to-tenant resolution (Microsoft getuserrealm.srf Managed/Federated namespace check, Entra OIDC metadata tenant-GUID extraction, Autodiscover v2), keyless Microsoft tenant-federation mapping (GetFederationInformation SOAP -> sibling-domain discovery, discover-only ROE, FEDERATED_WITH provenance edge held out of attack-path pivoting), Okta org-slug derivation + OIDC fingerprint + governed custom-domain enumeration, ADFS passive/active fingerprint + version inference, Google Workspace MX-correlated detection, generic OIDC (Auth0/Keycloak/Ping Identity/OneLogin/Duo) discovery, SAML metadata (5 paths), Azure AD Seamless-SSO Negotiate-challenge detection, Microsoft Defender for Identity (MDI) sensor-API presence check, the user-enumeration oracle methodology for Microsoft GetCredentialType (IfExistsResult semantics: exists / doesn't-exist / exists-in-federated-tenant / throttled) and Okta /api/v1/authn (errorCode differential), Medium-detectability discipline with a hard 20-candidate-per-tenant cap and admin/role interest-based ranking, and name x confirmed-email-pattern login-candidate synthesis that FAILS CLOSED with zero output when no org pattern is confirmed. Grounded directly in a production ASM implementation's sso_idp.py, tenant_recon.py, and core/email_patterns.py modules. Deepens — does not duplicate — offensive-osint skill's Identity Fabric endpoint reference with the tenant-federation MAP, the oracle WORKFLOW, and the candidate-SYNTHESIS methodology that reference lacks. Use when fingerprinting an organization's identity provider, mapping its tenant/federation boundary, running an authorized pre-auth user-enumeration pass, or synthesizing login candidates from harvested names to feed that oracle — never for password spray, credential submission, or auth bypass.
The English summary is being prepared. Showing the original description.
Steganography detection and extraction playbook. Use when analyzing images (LSB, PNG chunks, JPEG DCT, EXIF), audio (spectrogram, DTMF), files (polyglots, appended data, ADS), and text (whitespace, zero-width, homoglyphs) for hidden data.
The English summary is being prepared. Showing the original description.
Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction task.
The English summary is being prepared. Showing the original description.
Orchestrates a systematic review and meta-analysis workflow following PRISMA 2020 guidelines, from protocol development through multi-database search, screening, data extraction, and evidence synthesis. Use when conducting evidence-based reviews, meta-analyses, or scoping revi...
The English summary is being prepared. Showing the original description.
Analyze KiCad projects and PDF schematics: schematics, PCB layouts, Gerbers, footprints, symbols, netlists, and design rules. Reviews designs for bugs, traces nets, cross-references schematic to PCB, extracts BOM data, checks DRC/ERC, DFM, power trees, and regulator circuits. Every finding carries a confidence label and evidence source with trust_summary rollup. Analyzes PDF schematics from dev boards, reference designs, eval kits, and datasheets. Supports KiCad 5–10. Use whenever the user mentions .kicad_sch, .kicad_pcb, .kicad_pro, PCB design review, schematic analysis, PDF schematics, reference designs, Gerber files, DRC/ERC, netlist issues, BOM extraction, signal tracing, power budget, DFM, or wants to understand, debug, compare, or review any hardware design. Also for "check my board", "review before fab", "what's wrong with my schematic", "is this ready to order", "check my power supply", "verify this circuit", OSHWA certification readiness, or any electronics/PCB design question.
The English summary is being prepared. Showing the original description.
Analyze KiCad projects and PDF schematics: schematics, PCB layouts, Gerbers, footprints, symbols, netlists, and design rules. Reviews designs for bugs, traces nets, cross-references schematic to PCB, extracts BOM data, checks DRC/ERC, DFM, power trees, and regulator circuits. Every finding carries a confidence label and evidence source with trust_summary rollup. Analyzes PDF schematics from dev boards, reference designs, eval kits, and datasheets. Supports KiCad 5–10. Use whenever the user mentions .kicad_sch, .kicad_pcb, .kicad_pro, PCB design review, schematic analysis, PDF schematics, reference designs, Gerber files, DRC/ERC, netlist issues, BOM extraction, signal tracing, power budget, DFM, or wants to understand, debug, compare, or review any hardware design. Also for "check my board", "review before fab", "what's wrong with my schematic", "is this ready to order", "check my power supply", "verify this circuit", OSHWA certification readiness, or any electronics/PCB design question.
The English summary is being prepared. Showing the original description.
Convert PDF files to Markdown using opendataloader-pdf. Extracts text, tables, headings, lists, and images with correct reading order. Use for PDF parsing, PDF to Markdown conversion, document extraction, and AI-ready data preparation.
The English summary is being prepared. Showing the original description.
Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a vibration / biosignal / radar / sensor signal needing features for downstream ML or analysis. Includes optional GPU acceleration via canUseGPU and gpuArray. Does not cover filter design, audio-specific feature extraction (use audioFeatureExtractor in Audio Toolbox instead), batch dataset orchestration, or 2D / image features.
The English summary is being prepared. Showing the original description.
This skill should be used when the user asks to "scan AI systems for security threats", "check for prompt injection vulnerabilities", "assess model security posture", "detect data poisoning risks", or "audit AI/ML pipeline security".
The English summary is being prepared. Showing the original description.
Live-data research via the glim.sh MCP - web search, full page extraction, X/Twitter, Reddit, GitHub, Amazon, and YouTube transcripts - synthesized into a cited digest. Pay-per-call from the connected account balance; OAuth Connect via the dashboard MCP panel.
The English summary is being prepared. Showing the original description.