walkerOS

Use when writing or updating walkerOS documentation - README, website docs, or skills. Covers quality standards, example validation, and DRY patterns.

Use when creating walkerOS events, understanding event structure, or working with event properties. Covers entity-action naming, event properties, statelessness, and vendor-agnostic design.

Use when working with walkerOS destinations, understanding the destination interface, or learning about env pattern and configuration. Covers interface, lifecycle, env mocking, and paths.

Use when an AI agent calls walkerOS MCP tools from code (code execution / Code Mode, a Worker, or an app sandbox) to validate, simulate, bundle, or inspect flows and packages, and wants to filter large results in code instead of issuing many separate tool calls.

Use when working with walkerOS sources, understanding event capture, or learning about the push interface. Covers browser, dataLayer, and server source patterns.

Use when bundling walkerOS flows, testing events with simulate/push, running local servers, validating configs, or configuring Flow JSON files.

Use when creating a new walkerOS destination to send events to a vendor or

Use when creating a new walkerOS source to capture events (browser source,

Use when creating a new walkerOS transformer to modify events in the pipeline (validate, enrich, or redact) at a before/next chain position. Example-driven workflow for the transformer interface, return values, and chaining.

Use when contributing to walkerOS, before writing code, or when unsure about project conventions. Covers build/test/lint workflow, XP principles, folder structure, and package usage.

Use when working with walkerOS stores, understanding key-value storage in flows, or learning about store injection via env. Covers interface, lifecycle, $store. wiring, and available store packages.

Use when adding read-through caching to a walkerOS store, memoizing a slow API/Sheets backing, composing multi-tier cache chains, or deduplicating concurrent store reads. Covers recipes, TTL choice, error policy, and observability counters.

Use when wiring `@walkeros/transformer-ga4` into a server flow, overriding default GA4 event mappings, dropping events, adding custom event keys, or troubleshooting GA4 Measurement Protocol decoding. Covers the `before`-chain wiring contract, configuration recipes, and per-field patching with extend/remove.

Use when creating a new walkerOS CMP (consent management platform) source. Structured fill-in-the-blanks workflow that turns any CMP's consent API into a walkerOS source package. Covers CookieFirst, Usercentrics, CookiePro/OneTrust patterns and generalizes to any CMP.

Use when learning walkerOS architecture, understanding data flow, or designing composable event pipelines. Covers Source→Collector→Destination pattern and separation of concerns.

Use when working with walkerOS transformers, understanding event validation/enrichment/redaction, or learning about transformer chaining. Covers interface, return values, and pipeline integration.

Use when transforming walkerOS events in the flow (source→collector or collector→destination), configuring data/map/loop/set/condition/policy, or using $code: syntax in JSON configs.

Use when walkerOS events aren't reaching destinations, debugging event flow, or troubleshooting mapping issues. Covers common problems and debugging strategies.

Use when writing, simulating, validating, or testing with walkerOS step examples. Covers the complete lifecycle from authoring examples to CI integration.

Use when writing tests, reviewing test code, or discussing testing approach for walkerOS packages. Covers env pattern, dev examples, and package-specific strategies.

Use when configuring walkerOS event mappings for specific use cases. Provides recipes for GA4, Meta, custom APIs, and common transformation patterns.

Use when working with walkerOS sources/destinations to understand standard logging patterns, replace console.log, or add logging to external API calls. Covers DRY principles, when to log, and migration patterns.