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Found 3,526 Skills
Create a complete SPEC from scratch through an exhaustive requirements interview before any planning or implementation. Use this skill whenever the user asks to create, define, clarify, scope, or write a spec/SPEC/PRD/requirements document from an idea, especially when they want to avoid assumptions, start at "step zero," or prepare input for later planning workflows. This skill must question goals, requirements, constraints, edge cases, business rules, and acceptance criteria before drafting the final spec.
Start here for first-time CARTO use — install the CLI, authenticate, switch profiles, understand JSON output and async job patterns. Also orients on the two parallel access paths into the CARTO platform (CLI for authoring/scripting, MCP server for inline interactions in chat hosts) and which skills cover each.
Builds site selection and cannibalization analysis workflows in CARTO. Triggers when the user mentions site selection, cannibalization, cannibalizing, new store location, where to open, optimal location, facility placement, network impact, overlapping catchments, twin areas, similar locations, look-alike areas, find locations like my best, store overlap, revenue impact of new store, commercial hotspots, demand hotspots, location scoring, location ranking, expand network, new branch, franchise placement, EV charging siting, or wants to evaluate candidate sites, quantify overlap between trade areas, or find areas that resemble top-performing locations.
Builds Geographically Weighted Regression (GWR) workflows in CARTO. Triggers when the user mentions GWR, geographically weighted regression, spatially varying relationships, local regression, local coefficients, spatial regression, "what drives X in different areas", "why do prices vary spatially", "local factors affecting Y", varying coefficients, coefficient maps, spatial non-stationarity, or wants to model how the relationship between a dependent variable and predictors changes across geography. Produces per-cell regression coefficients that reveal how predictor importance shifts from place to place.
Help developers integrate Chainlink Data Feeds into smart contracts and applications. Use for price feed integration, feed address lookup, consumer contract generation, multi-chain data feeds (EVM, Solana, Aptos, StarkNet, Tron), MVR bundle feeds, SVR/OEV feeds, feed monitoring, historical data, L2 sequencer checks, rates/volatility feeds, SmartData/RWA feeds, or debugging feed integrations. Trigger on any mention of Chainlink price feeds, oracle data, AggregatorV3Interface, latestRoundData, or feed addresses.
Help developers integrate Chainlink VRF into smart contracts. Use for consumer contract generation with VRFConsumerBaseV2Plus, subscription setup and funding (LINK or native), keyHash and gas lane selection, coordinator address lookup and debugging VRF integrations. Trigger on any mention of VRF, verifiable randomness, on-chain random number generation, requestRandomWords, fulfillRandomWords, VRF subscription, VRF coordinator, keyHash, or provably fair randomness in a smart contract, even if the user does not say 'VRF' explicitly.
Vendor-neutral skill to draft a blameless incident postmortem from structured incident inputs (timeline, impact, contributing factors) and produce an actionable report.
Vendor-neutral skill to check a data retention schedule for completeness and risk (coverage, deletion handling, legal holds) and produce a structured findings report.
Vendor-neutral skill to analyze onboarding funnel dropoff and propose prioritized interventions.
Create and manage Oodle log-based metric rules — extract metrics from log streams using filter expressions and groupBy labels.
This skill should be used when the user asks to "set up oodle integration", "onboard to oodle", "integrate kubernetes with oodle", "connect AWS to oodle", "install oodle collector", or mentions setting up observability with Oodle. Discovers the environment, recommends matching integrations from available setup specs, and executes step-by-step installation. Not for querying existing metrics, logs, or traces (use /oodle-metrics-query, /oodle-logs, /oodle-traces instead).
Elastic ML anomaly detection skill — investigation/RCA, score explanation, job operations (create, datafeed, start/stop, results), and troubleshooting (missing docs, memory limits, datafeed health, lifecycle). Operates against Kibana Agent Builder MCP tools (`ad_*`) on `.ml-anomalies-*`, `.ml-config`, `.ml-notifications-*`, `.ml-annotations-*`. Use when answering "what broke?"/"which entity?"/RCA, "why is score high/low?"/renormalization, "datafeed stopped"/"memory limit", or any request to set up or configure an ML anomaly detection job.