google

Interactively discovers requirements for a specific cloud workload and generates design recommendations and architectural guidance to build a multi-product solution in Google Cloud. Use when users need holistic, end-to-end design recommendations and architectural guidance for complex workloads on Google Cloud for specific use cases. Don't use this skill when other specialized skills exist that directly address the user-specified workload or use case. If the user's request is narrowly focused on a specific Google Cloud product, use the skills that are specific to that product. When users need assistance with workflows for onboarding, authentication, or designing foundational infrastructure, use the recipe skills that are specific to those workflows.

Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).

Configures GKE observability, including Cloud Logging, Cloud Monitoring, and managed Prometheus. Use when configuring GKE monitoring, setting up GKE logging, or configuring Prometheus metrics collection. Don't use to configure local application logging frameworks or external APMs outside GKE.

Guides developers through uploading audience members to Google products using the Data Manager API /v1/audienceMembers/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload audience members for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).

Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).

Guides developers through client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the API. Don't use for implementing audience or event ingestion logic (use the data-manager-api-audience-ingestion or data-manager-api-event-ingestion skills instead).

Guides developers through downloading, configuring, and installing the official open-source Google Ads MCP Server. Use this skill when a user wants to connect their AI assistant (such as Gemini, Claude Code, or Cursor) to their Google Ads account to query campaigns or retrieve reporting metrics using natural language.

Guides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a "retrieve campaigns" script. Troubleshoots common setup errors: USER_PERMISSION_DENIED, login_customer_id issues, and DEVELOPER_TOKEN_NOT_APPROVED. Use this skill when: - The user asks how to get started with the Google Ads API. - The user needs to set up Google Ads credentials or developer tokens. - The user wants to write a quickstart/example script for Google Ads. - The user encounters errors like USER_PERMISSION_DENIED or DEVELOPER_TOKEN_NOT_APPROVED.

Capsem benchmarking with capsem-bench and capsem-bench-rs. Use when running benchmarks, adding new benchmark categories, interpreting results, or investigating performance regressions. Covers benchmark categories (disk, rootfs, storage, startup, protocol/http, snapshot, all), the JSON output format, and how to add new benchmarks.

Capsem development toolchain -- all just recipes, what they do, when to use which, and dependency chains. Use when you need to know how to build, run, test, or ship Capsem, or when deciding which just command to run for a given change. This is the toolchain reference.

Asset building, manifest format, hash verification, and boot-time resolution for Capsem VM images. Use when debugging boot failures, manifest issues, hash mismatches, or understanding how assets flow from build to boot.

Capsem native package installer -- package install, service registration, self-update, manifest-driven asset download, corp config provisioning, and the install test harness. Use when working on package install/update/uninstall commands, service install/uninstall, asset management, corp config, install test infrastructure, or the installed layout (~/.capsem/).

Capsem release process, CI pipeline, Apple code signing, notarization, documentation site, and post-release verification. Use when preparing a release, debugging CI failures, working with Apple certificates, updating the documentation site, or cutting a new version. Covers the full release lifecycle from pre-release checklist through post-release verification.

Capsem system architecture -- service daemon, per-VM processes, CLI, MCP server, guest agent, vsock, network proxy. Use when you need to understand the system design to write code, review changes, write documentation, or debug cross-component issues. Covers the service architecture, IPC protocols, vsock ports, storage modes, network policy, MITM proxy, and key source files.

Capsem documentation site infrastructure and conventions. Use when writing, editing, or maintaining docs in the docs/ directory (docs.capsem.org), adding new doc pages, updating the sidebar, or working with Astro Starlight. Covers site structure, frontmatter, writing style, sidebar config, release pages, and dev workflow.

Capsem marketing website (capsem.org). Use when editing marketing copy, adding sections, working with components, or changing the site theme. Covers site structure, data-driven content, component library, Tailwind theme, and dev workflow.

Guide to building AI + XR applications with the XR Blocks SDK (the `xrblocks` package, source in `src/`). Use when writing, editing, or debugging WebXR / Android XR / VR / AR / mixed-reality experiences on this framework — authoring `xb.Script` classes, configuring `xb.Options`, and wiring spatial UI, hand tracking, gestures, depth & occlusion, plane/object detection, physics, spatial audio, or Gemini/OpenAI integration — and when running them in the desktop simulator or on-device. Covers the canonical app skeleton, the real `enable*` option methods, the `Script` lifecycle hooks, the global aliases (`xb.core`, `xb.user`, `xb.world`, `xb.ai`...), and the most common hallucinated-API mistakes to avoid. Read before generating XR Blocks code.

Develop and test XR Blocks apps on the desktop without a headset using the built-in simulator — a simulated user, hands, depth, and planes rendered in a normal browser, with control modes for moving the user, posing hands, or driving controllers. Use when running/iterating locally, reproducing XR interactions on desktop, posing hands for gesture work, or adding the optional 2D simulator settings UI. Covers the `?formFactor=desktop` autostart, `options.simulator.*`, `xb.SimulatorMode`, the `SimulatorAddons` 2D UI import, and the `onSimulatorStarted()` hook.

Write sequential asynchronous functional, integration, or simulator tests for xrblocks apps using the testing addon. Use this when you need to mock WebGL/WebAudio in headless environments (like JSDOM / Vitest), simulate user locomotion, trigger controller pointing, raycasts, and select/squeeze hand inputs. Covers `TestRunner` and `TestRunnerConfig`.

Build rich spatial user interfaces in XR Blocks apps with the uiblocks addon — flexbox-laid-out 3D cards and panels with gradients, strokes, rounded corners, drop/inner shadows, MSDF text, material icons, images, and spatial behaviors (head-leash, billboard, grab/manipulate, object-anchor, show/hide animations). Use when authoring or debugging `UICard` / `UIPanel` / `UIText` / `UIImage` / `UIIcon` UI imported from `xrblocks/addons/uiblocks/src` (wrapping `@pmndrs/uikit` + yoga-layout) — for panels, menus, HUDs, dialogs, or any styled, web-like UI in WebXR / Android XR. Includes the bootstrap (`options.uikit.enable(uikit)` + `raycastSortFunction`), styling/layout rules, behavior config, and a troubleshooting playbook for clicks/styling/sizing failures. (For lightweight panels with no extra deps, prefer core `xb.SpatialPanel` instead.) Includes a design guide (§6) for UX designers composing complex, elegant, multi-section spatial UI — tokens, spatial comfort, elevation/shadows, passthrough legibility, motion, a

Add real-time multiplayer to an XR Blocks app with the netblocks addon — presence avatars (remote heads + hands), replicated `NetObject` transforms with cooperative ownership, typed pub/sub RPC events, and opt-in spatial WebRTC voice, over pluggable transports (BroadcastChannel for local dev, WebRTC/PeerJS for serverless P2P, WebSocket relay for scalable rooms). Use when authoring or debugging shared/co-located XR, `enableNet()`, `joinRoom()`, `NetObject`, `session.events`, or `session.voice` imported from `xrblocks/addons/netblocks/src`. For the wire protocol, transport details, and threat model, read the full reference in this folder's README.md.

Add audio-driven avatar mouths to an XR Blocks app with the lipsync addon — heuristic vowel-formant viseme mapping that turns any `MediaStream` (mic or remote peer's voice) into mouth shapes on a `StylizedFace` decal attached to an avatar's head. Zero ML runtime, no model download. Use when you want shared rooms to stop being silent spheres and become faces that visibly speak, or to lip-sync a TTS playback to an NPC. Covers `LipsyncMouth`, `xb.StylizedFace`, the `target`/`audioContext`/`fftSize` constructor options, and the `session.voice.onTrack` netblocks pairing. Lower-level pieces (`FormantVisemeMapper`, `MfccExtractor`, `computeAudioFeatures`) and types (`VisemeWeights`, `VisemeTarget`) are exported for swapping in a model-based mapper. Full reference at src/addons/lipsync/.

Add audio-driven avatar mouths to an XR Blocks app with the lipsync addon — heuristic vowel-formant viseme mapping that turns any `MediaStream` (mic or remote peer's voice) into mouth shapes on a `StylizedFace` canvas decal attached to an avatar's head. No ML runtime, no model download. Use when authoring or debugging avatar mouths in single-user demos or in multiplayer scenes paired with `xb-netblocks` (every remote peer's voice stream drives their own face). Public surface: `LipsyncMouth` (the driver), `xb.StylizedFace` (the decal, in xrblocks core), `session.voice.onTrack` for the netblocks hook, plus the lower-level `FormantVisemeMapper`, `MfccExtractor`, `computeAudioFeatures` and types (`VisemeWeights`, `VisemeTarget`, `AudioFeatures`) for plugging in a model-based mapper later. For the DSP pipeline, caveats, and samples read this folder's README.md.

Add real-time multiplayer to an XR Blocks app with the netblocks addon — presence avatars (remote heads + hands), replicated `NetObject` transforms with cooperative ownership, typed pub/sub RPC events, and opt-in spatial WebRTC voice, over pluggable transports (BroadcastChannel for local dev, WebRTC/PeerJS for serverless P2P, WebSocket relay for scalable rooms). Use when building shared or co-located XR. Covers `enableNet()`, `joinRoom()`, `NetObject`, and `session.events`; the full reference (wire protocol, transports, threat model) is at src/addons/netblocks/.

This skill should be used when the user wants to "create a new Python ADK sample", "scaffold a new Python sample recipe", "generate a new Python sample in contrib", "add a new Python sample to the adk-samples repository", or "create a Python adk sample". It utilizes an automated script to copy template files and resolve basic placeholders.

Scan an ADK recipe directory and generate a manifest.yaml for it based on the schema at .github/schemas/manifest-schema.json. Use when the user wants to create or generate a manifest.yaml for a recipe under core/ or contrib/.

Accesses real-time spatial data, weather, and traffic routing to design accurate itineraries.

Performs a strict evaluation of a video asset using Google's official 'ABCD' framework (Attract, Brand, Connect, Direct) based on transcript and metadata.

Deconstructs high-performing or viral videos to extract actionable creative insights from metadata and transcript.

Provides a high-signal briefing on events in a specific location and timeframe, backed by primary video sources and transcripts.

Extracts the strongest arguments from heated YouTube comment threads, identifying key battlegrounds and community consensus.

Saves time by autonomously reading transcripts, synthesizing arguments, and generating direct jump-links to key moments.

Synthesizes raw learnings and codebase analysis into an interlinked Markdown Knowledge Base (KB). Use at the beginning of a loop to build or update architecture.md, entities, and vulnerabilities. Don't use for generating threat models or formulating execution plans.

Calculates the final risk score based on empirical evidence and architectural impact. Use when findings have been fully processed by previous stages and you need to append final risk scores to the finding files. Don't use for discovering new vulnerabilities or writing patches.

Synthesizes trust boundaries, attack surfaces, and attacker profiles into a living threat model. Use as Stage B of the Knowledge Base generation process, reading architecture and entity definitions from the KB. Don't use for analyzing source code or extracting raw learnings from JSONL files.

Analyzes individual security findings to identify and construct complex exploit chains. Use after validation stages to see if multiple low-severity bugs can be combined into a higher impact vulnerability. Don't use for initial codebase auditing or writing patch code.

Consolidates raw security findings to eliminate redundant reports. Use when raw findings have been generated by the researcher and need consolidation before review. Don't use for initial code auditing or patch generation.

Audits production source code files based on the strategy in plan.json. Use when a review plan exists and you need to perform static analysis and deep-dive reviews of targeted files. Don't use for planning, deduplicating, or writing patches.

Assesses the production viability of findings, filtering out debug-only features and assertion traps. Use when findings have been validated and you need to confirm they are triggerable in production release builds (with assertions disabled). Don't use for writing reproduction scripts or patches.

Acts as the persistent supervisor, launching and monitoring the automated review campaign. Use when running a long-running, continuous security review campaign that needs autonomous coordination. Don't use for executing individual review stages directly.

Extracts and verifies the runnability and code coverage of all Python code blocks inside a Markdown file. Generates a detailed compilation and execution report.

ADK architectural knowledge — graph orchestration, resumption, execution flow, node contracts, observability, and LLM context orchestration. Use this skill whenever you need to understand the architecture, event flow, or state management of the ADK system, or when designing or modifying core components. Triggers on "how does X work", "design of", "architecture of", "event flow", "resumption state", "checkpoint", "BaseNode", "NodeRunner".

ADK development style guide for routine nits — Python idioms, codebase conventions, imports, typing, Pydantic patterns, formatting, logging, async/concurrency, and file organization. Use this skill whenever writing code, tests, or reviewing PRs for the ADK project to ensure compliance with styling and coding conventions. Triggers on "code style", "how should I format", "naming convention", "lint", "nit", "imports", "typing", "Pydantic patterns", "testing rules", "async", "io".

Central hub for building, testing, and iterating on ADK agents. Trigger this skill when the user wants to create a new agent, configure modes (task, single-turn), or build graph-based workflows.

Author new samples for the ADK Python repository. Use this skill when the user wants to create a new sample demonstrating a feature or agent pattern (e.g., dynamic nodes, standalone agents, fan-out/fan-in) or when adding examples to subdirectories under `contributing/`.

Creates or updates code unit design documents for source code documentation.

Creates detailed code unit guides for source code documentation.

Set up a local development environment for the ADK Python project. Use when the user wants to get started developing, set up their environment, install dependencies, or prepare for contributing.

A skill living directly under the assets root.

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Skill that has a directory outside the allow-list.

A valid skill for testing.

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Casts a fireball at a specified target.

Enforce C++ static thread safety annotations and correct synchronization primitives. Use this skill when designing multi-threaded classes or editing guarded member fields.

Build, deploy, run, and benchmark Filament binaries on connected Android devices or emulators. Use this skill for compiling, pushing, and executing Android tests or benchmarks.

Enforce correct Filament object creation and destruction lifecycles. Use this skill when initializing rendering pipelines or allocating/deallocating GPU buffers and entities.

Enforce correct mathematical primitives and naming conventions in Filament code. Use this skill when performing coordinate transformations, vector math, or projection setups.

Guidelines and SOP for synchronizing public C++ API changes (methods, enums, options structs) to Java (Android JNI) and JavaScript/TypeScript (Web/WASM Embind).

Standard verification pipeline to execute after modifying C++ source or header files. Use this skill to format includes, build the engine, and run core tests.

Enforce the strict topological header inclusion layering and reordering rules in Filament. Use this skill when adding or modifying `#include` directives in C++ source or header files.

Clean and build Filament targets for development, debugging, and production. Use this skill whenever you need to clean the workspace or compile desktop targets.

This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management", or needs ADK (Agent Development Kit) Python API patterns and code examples. Part of the Google ADK skills suite. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, and state management. Do NOT use for creating new projects (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).

This skill should be used when the user wants to "deploy an agent", "deploy my ADK agent", "set up CI/CD", "configure secrets", "troubleshoot a deployment", or needs guidance on Agent Runtime, Cloud Run, or GKE deployment targets, or awareness of Agent Gateway. Covers deployment workflows, service accounts, rollback, and production infrastructure. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for API code patterns (use google-agents-cli-adk-code), evaluation (use google-agents-cli-eval), or project scaffolding (use google-agents-cli-scaffold).

This skill should be used when the user wants to "run an evaluation", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Agent Platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Do NOT use for API code patterns (use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code).

This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini Enterprise", "publish to Gemini Enterprise", or needs guidance on the agents-cli publish gemini-enterprise command. Also use when the user wants to "manage agents in Agent Registry" or "list/update/delete registered agents". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment (use google-agents-cli-deploy).

This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the Google ADK (Agent Development Kit) skills suite. Covers `agents-cli scaffold create`, `scaffold enhance`, and `scaffold upgrade` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy).

This skill should be used when the user wants to "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle and coding guidelines. Entrypoint for building ADK agents. Always active — provides the full workflow (scaffold, build, evaluate, deploy, publish, observe), code preservation rules, model selection guidance, and troubleshooting steps for ADK or any agent development.

Use this skill to fuzz open source C/C++ software projects.

Use this skill to interact with the OSS-Fuzz infrastructure.

Use this skill to fuzz open source Go software projects.

Use this skill to fuzz open source JVM projects (Java, Kotlin, Scala, etc.) using Jazzer.

Use this skill to fuzz open source Python software projects using Atheris.

Use this skill to fuzz open source Rust software projects.

How to add a new error code in BoringSSL.

How to add a new object with a NID and/or OID to BoringSSL.

How to add a new source file to the BoringSSL build.

How to build BoringSSL and run its tests.

How to run BoringSSL's ssl/test/runner suite (protocol-level BoGo tests)

How to regenerate/update pre-generated files (e.g., perlasm, build files) in BoringSSL.

Helps the user configure the Google SecOps Remote MCP Server for Antigravity. Use this when the user asks to "set up" or "configure" the security tools for Antigravity.

Helps the user configure the Google SecOps Remote MCP Server for Gemini CLI. Use this when the user asks to "set up" or "configure" the security tools for Gemini CLI.

Expert guidance for proactive threat hunting. Use this when the user asks to "hunt" for threads, IOCs, or specific TTPs.

Expert guidance for deep security investigations. Use this when the user asks to "investigate" a case, entity, or incident.

Expert guidance for security alert triage. Use this when the user asks to "triage" an alert or case.