Results for “signa”

Generates a three-panel analysis for any ticker following Duan Yongping's seller-only options strategy: Sell Put at a willing-buy price, Covered Call for yield, and a VIX-based panic-buy signal.

Query Codecov for flaky-test signal, failure history, and coverage data via the codecov-api wrapper. Use when asked about flaky tests, intermittent test failures, why a test is failing, coverage on a PR/file/branch, or whenever browser access to Codecov is blocked by the login wall.

Detect Cobalt Strike beacon network activity using TLS certificate signatures, JA3/JA3S/JARM fingerprints, HTTP C2 profile matching, beacon jitter analysis, and named pipe detection via Zeek, Suricata, and Python PCAP analysis.

Detect Golden Ticket attacks in Active Directory by analyzing Kerberos TGT anomalies including mismatched encryption types, impossible ticket lifetimes, non-existent accounts, and forged PAC signatures in domain controller event logs.

Audits and fixes technical SEO, on-page metadata, structured data, Core Web Vitals, llms.txt, and AI-search optimization for ChatGPT, Perplexity, and AI Overviews, including E-E-A-T signals and programmatic SEO.

Daily customer health scoring across the active book of business. Pulls usage signals from PostHog and subscription state from Stripe, scores each active customer per the brand's customer-success playbook, updates the Notion customer DB, and Slack-alerts on at-risk transitions. Runs daily on cron schedule.

BISON v2.0 — Conviction Holder (Hardened). Top 10 assets by volume. All signals are score contributors — no hard gates. Scanner enters via create_position internally (Wolverine pattern). RatchetStop exits. Thesis exit REMOVED. v2.0: every hard gate converted to score contributor, ensureExecutionAsTaker=false, conviction-scaled margin 25-37%.

You are an expert in Svix, the enterprise webhook delivery platform. You help developers send reliable webhooks to customers with automatic retries, signature verification, delivery monitoring, endpoint management, and event type filtering — replacing custom webhook infrastructure with a purpose-built service used by companies like Clerk, Resend, and Liveblocks.

Detect NTLM relay attacks by analyzing Windows Event 4624 logon type 3 with NTLMSSP authentication, identifying IP-to-hostname mismatches, Responder traffic signatures, SMB signing status, and suspicious authentication patterns across the domain.

AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X. Use when the user wants to find, qualify, and reach high-value contacts.

Drafts a Receipt of Franchise Disclosure Document proving FTC Franchise Rule compliance under 16 C.F.R. § 436. Produces an execution-ready acknowledgment with franchisee identification, delivery date, FDD version, exhibit inventory, and dual signature blocks. Use when creating FDD receipts, franchise disclosure acknowledgments, or Item 19 FPR attestations.

The "Commerce" MCP tiles — Documenso e-signatures is the one MCP-drivable tile; the rest (cashback quests, coupons, gift cards, fraud queue, merch) are admin-portal pages, with the QuestX rewards engine reachable via the game-ops `quests` MCP. Use for contracts and commerce-program admin.

Use to measure customer effort from behavioural signals instead of CES surveys, and to audit whether a composite effort score is honest. Trigger for "customer effort score", "behavioural CES", effort without survey, repeat contacts and channel switches, transfers and reopens, or "our CES doesn't match operational data".

Use to map support contacts onto the product lifecycle, interpret contact as a lifecycle signal, and avoid journey-map theatre. Trigger for "customer journey map support", "contact by lifecycle stage", onboarding support drivers, churn and support overlap, stage-specific contact reasons, or when journey mapping is worth doing.

Models cascading what-if scenarios across all business functions to prepare for compound adversity, using a structured six-step framework that maps variables, domain impacts, cascade effects, severity levels, early warning signals, and hedging strategies.

Builds distinctive, production-grade UI by committing to one of 12 named visual directions, implementing a real typography scale, spacing system, and one signature flourish, then gating the result through a measurable anti-slop checklist and contrast/touch-target verification.

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.

Multi-signal trend forecasting for autonomous agents. Combines prediction market odds, Twitter/X social sentiment, news velocity, and stock market data into a unified trend analysis with confidence scoring. Powered by AIsa — one API key, five data streams. Use when: the user needs X/Twitter research, monitoring, posting, or engagement workflows.

Acorn CLI commands for WordPress automation — lando acorn make:command, artisan-style commands, Command::class, $signature, $description, handle() method, command arguments and options, output formatting, dependency injection in commands, calling other commands, AppServiceProvider registration, wp acorn schedule:run, scheduled commands, data import scripts, maintenance commands, theme automation tasks, lando acorn list

Query the openFDA API for drugs, medical devices, adverse event reports, recalls, regulatory submissions (510k, PMA), and substance identification (UNII). Use when searching FDA safety data, pharmacovigilance and adverse-event signals, device clearances, drug labels, or recall records for regulatory data analysis and safety research. Part of the AlterLab Academic Skills suite.

Detects all languages used on a webpage — both declared (html@lang, hreflang, nested lang=, meta content-language) and actually present in the body text using Google CLD3 WASM. Reconciles the two signal sets and flags mismatches for i18n audits, hreflang validation, and multilingual content verification.

One-time setup that makes fb.ai cold email actually sendable — add a sending domain, get the DNS records published, verify, add a sender signature, and get it confirmed. Has two unavoidable human waits (DNS, Postmark email); the skill stops and hands back at each. Run once per brand, then re-run to resume.

Analyze betting market sentiment including line movement, sharp vs public money, steam moves, reverse line movement, and market signals. Use when reading line movement to determine where the smart money is going. Also trigger for 'line movement', 'sharp money', 'public money', 'steam move', 'reverse line movement', 'RLM', 'where the money is', or 'wiseguy action'.

Detect PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.

Use when setting up vehicle network communication in MATLAB using Vehicle Network Toolbox. Covers CAN/CAN FD (fully implemented), with architecture for J1939, XCP, and future protocols. Handles hardware discovery, channel creation, bus configuration, message exchange, signal encoding/decoding, and analysis across all supported vendors. (Vector, Kvaser, PEAK-System, NI, SocketCAN, MathWorks Virtual).

You are an expert in DSPy, the Stanford framework that replaces prompt engineering with programming. You help developers define LLM tasks as typed signatures, compose them into modules, and automatically optimize prompts/few-shot examples using teleprompters — so instead of manually crafting prompts, you write Python code and DSPy finds the best prompts for your task.

Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to analyze a stock, check a ticker, or compare investments.

WebRTC peer-to-peer communication. Signaling, ICE/STUN/TURN, media streams, data channels, screen sharing, and SFU integration (mediasoup, LiveKit). USE WHEN: user mentions "WebRTC", "video call", "peer-to-peer", "P2P", "screen sharing", "data channel", "STUN", "TURN", "mediasoup", "LiveKit" DO NOT USE FOR: server-to-client streaming - use `sse`; chat messaging - use `socket-io`

Produces a decision-grade dossier on a specific company, person, nonprofit, or government org by testing the user's hypothesis rather than confirming it. Outputs an editable Word document with verdict, identity facts, 12-month activity timeline, network and reputation signals, and red flags.

Analyzes competitor products by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media into structured competitive intelligence. Produces feature comparison matrices, SWOT analyses, positioning maps, UX audits, pricing breakdowns, action plans, and presentations.

Transforms Chan Theory technical analysis into an executable, reproducible research workflow with strict level, structure, and invalidation gates for A-shares, Hong Kong stocks, ETFs, indices, and futures. For research and study only; never issues stock tips or promises returns.

Analyze AMS waveform data using Mixed-Signal Blockset utilities: phase noise measurement, clock jitter, anti-aliased resampling, timing measurements, lock time, INL/DNL, ADC/DAC calibration, HSpice import. Use when analyzing time-domain voltage from PLL/VCO/clock simulations, measuring phase noise from variable-step solver output, computing jitter, or resampling non-uniform data.

Compact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or per-project .handoff/), redact secrets before write, suggest skills for the next session, and auto-load the latest handoff on the next SessionStart. First-run setup asks where to save so the project folder never gets cluttered. Use when the user says 'hand this off', 'handoff doc', 'summarize this for a new session', 'compact this conversation', 'I'm ending this session', 'pick this up later', or any variation signaling intent to pass work to a fresh agent. Also trigger on implicit signals: the user announcing they're switching machines, ending the day mid-task, or context is growing long without a natural stopping point.

Configure Microsoft Entra ID (Azure AD) Conditional Access policies for zero trust access control, covering signal-based policy design, device compliance, risk-based authentication, named locations, session controls, and NIST SP 1800-35 integration.

Quantifies market top probability using O'Neil Distribution Days, Minervini leading stock deterioration, and Monty defensive sector rotation, producing a 0-100 composite score with risk zone classification for tactical 2-8 week timing signals.

Knowledge base from "Oversubscribed: How to Get People Lining Up to Do Business with You" by Daniel Priestley. Use when applying Priestley's frameworks for demand generation, the Campaign Driven Enterprise (CDE) method, signalling, the 7-Hour Rule, products-for-prospects, becoming oversubscribed, or building a Key Person of Influence brand — or when studying or referencing the book.