Results for “signals”

Synthesize or append structured wiki notes from dashboard signals into brain/ or global/ per capture-llm-wiki schema with citations. Use when user wants LLM to compound vault knowledge from USASpending context — human review recommended.

Motion Canvas framework reference covering project setup, core concepts (generators, signals, refs, scene hierarchy, timing, utilities), and 2D components (shapes, paths, text, media, layout, camera, transitions, custom components). Use when building or editing Motion Canvas scenes.

Identify at-risk customer accounts by analyzing usage patterns, engagement signals, and support history to generate churn risk scores and intervention recommendations. Use when the user requests churn analysis or provides relevant inputs for this workflow.

Generates Angular code and provides architectural guidance for projects, components, services, and more, covering reactivity, forms, dependency injection, routing, accessibility, animations, styling, testing, and CLI tooling.

Defines service level objectives, creates error budget policies, designs incident response procedures, develops capacity models, and produces monitoring configurations and automation scripts for production systems.

Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure covering screening, deep dive, entry planning, and post-purchase monitoring.

Scans a project for stack signals and pain points, searches the skills-hub registry and local skills, scores candidates, and presents a ranked shortlist with install commands.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `stock-rumors`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Rumor Scanner — find early signals including M&A rumors, insider activity, analyst upgrades/downgrades, social whispers, and SEC/regulatory activity via AIsa API. Ranked by impact score. Use when the user asks about rumors, insider trading, M&A activity, analyst changes, or early market signals.

Access real-time X/Twitter attention intelligence for Base chain tokens via the checkr API, including trending tokens, social spikes, attention/price divergence signals, and narrative summaries.

Research companies, industries, or competitor sets using web search and seven analytical lenses to produce structured intelligence for downstream product management tasks.

Screen US equities for parabolic exhaustion patterns, generate conditional pre-market short plans, and monitor intraday trigger signals using 5-min bars.

Verifies phone numbers for carrier and SIM-swap fraud signals, and places AI-powered outbound voice calls through BlockRun's gateway with automatic x402 wallet payment.

Analyzes content quality and E-E-A-T signals, scores readability, keyword use, structure, and AI citation readiness, and flags thin or outdated content.

Analyze marketing pages and provide actionable recommendations to improve conversion rates, covering value proposition, headlines, CTAs, visual hierarchy, trust signals, objection handling, and friction points.

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

Integrates endpoint health signals from CrowdStrike ZTA, Microsoft Intune, and Jamf into conditional access policies to enforce device compliance before granting resource access.

Find adjacent vendors and subs (not top market primes) who fill a capability gap against a displacement target using USASpending flows and SAM entity signals. Use when user defines a teaming gap and wants vault-ready partner shortlist with citations.

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Turn a pile of accounts into a stack-ranked priority list with a reason on every row. A layered score (gates first, then an evidence-weighted base rank over the signals you actually have, then bounded boosts for product usage and buyer intent) that stays fair across channels and never scores a blank field as a zero. Built for B2B GTM teams, customizable to your signals and your ICP. Trigger on "score these accounts", "rank by fit", "composite ICP score", "stack-rank my list", "who should I work first", "prioritize these leads", or any multi-signal account qualification.

Identifies and analyzes statistical arbitrage opportunities through pair trading, using correlation analysis, cointegration testing, and z-score calculations to generate entry/exit signals for market-neutral strategies.

Audits over-engineered codebases by factoring layers into live obligations, quotienting redundant distinctions, ablating unearned surface, and normalizing survivors while preserving required behavior. Produces an evidence-backed Reduction Certificate, cuts, migration phases, proof signals, and rollback.

Detects unusual options activity and classifies smart money signals to help follow institutional positioning, including volume/OI ratio spikes, block trades, sweep orders, and net premium flow.

Implement HTTP data fetching in Angular v20+ using resource(), httpResource(), and HttpClient. Use for API calls, data loading with signals, request/response handling, and interceptors. Triggers on data fetching, API integration, loading states, error handling, or converting Observable-based HTTP to signal-based patterns.

Implement routing in Angular v20+ applications with lazy loading, functional guards, resolvers, and route parameters. Use for navigation setup, protected routes, route-based data loading, and nested routing. Triggers on route configuration, adding authentication guards, implementing lazy loading, or reading route parameters with signals.

RoadRunner asset path lookup tables for map format conversions in MATLAB. Maps lane markings, signs, signals, barriers, objects, and lane types to RoadRunner asset paths. Use when converting map formats to RRHD, resolving asset paths, or assigning visual assets to HD Map objects.

Build RoadRunner HD Map entities in MATLAB — lanes, boundaries, markings, junctions, signs, signals, barriers, parking. Use when creating driving scenes from scratch, authoring road networks for simulation and testing automated driving systems, or assembling RRHD maps from Lanelet2 or other HD map sources.

Calculates IV Rank and IV Percentile for any ticker to determine whether implied volatility is high or low relative to its 252-day history, and provides trading signals based on IV zones.

Generates a post-release blameless retrospective from project signals — synthesizing DORA-like metrics, WorkItem outcomes, session timeline, and drift deltas into a structured Artifact + LogEntry. Use at the end of a release cycle when asked to run a retro, "post-release review", "retrospective", or "post-mortem".

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%.

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".

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.

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.

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'.

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.