Stand up Grafana Tempo as a cost-efficient distributed-tracing backend that only needs object storage, and write TraceQL queries against it. Covers OTLP + Jaeger + Zipkin ingestion, the distributor → live-store → block-builder → object-storage write path, metrics-generator for RED spanmetrics + service graphs, Helm `tempo-distributed` deployment, multi-tenant `X-Scope-OrgID`, TraceQL span / resource / event scopes, structural operators (`>>`, `<<`), `rate()` + `quantile_over_time` metrics, and the traces-to-logs / metrics / profiles datasource links. Use when deploying Tempo, writing a TraceQL query for slow / errored requests, debugging "no traces showing in Explore", sizing queriers / compactors, configuring S3 / GCS / Azure block storage, or wiring trace ↔ log ↔ profile correlation — even when the user says "tracing backend", "find slow requests", "show me the service graph", "store traces in S3", "Jaeger compatible store", or "what called this span" without naming Tempo.

Auto-instrument an application's HTTP / gRPC / DB traffic with Grafana Beyla eBPF — no code changes, no SDK, no restart. Covers requirements (Linux 5.8+ with BTF, CAP_SYS_ADMIN, host PID), language matrix (Go / Java / Python / Ruby / Node / .NET / Rust / C++ / PHP), Docker + Helm + DaemonSet install, port- / process- / Kubernetes-metadata discovery, OTLP traces + Prometheus metrics export, routes decorator (cardinality control), trace sampling, and Grafana Cloud via Alloy. Use when adding observability to a service you can't recompile, instrumenting a closed-source binary, getting RED metrics + spans onto Tempo/Mimir without touching the app, or rolling Beyla as a cluster-wide DaemonSet — even when the user says "zero-code APM", "instrument legacy app", "trace this binary", "eBPF observability", or "no SDK" without naming Beyla.

Find the Prometheus metrics that drive your Grafana Cloud bill. `dpm-finder` is a Grafana Professional Services CLI that ranks metrics by Data Points per Minute (DPM) with per-label-set breakdown, optional `--cost-per-1000-series` pricing, and a Prometheus-exporter mode. Use when investigating high Grafana Cloud spend, hunting noisy / high-cardinality metrics, comparing pre/post recording-rule cardinality, or feeding cost data into dashboards — even when the user says "why is my Mimir bill so high?", "find the biggest metrics", "cardinality offenders", or "optimize Prometheus cost" without naming dpm-finder.

Implement reconcilers and watchers for grafana-app-sdk apps — write `TypedReconciler[*MyKind]` reconcile functions, apply generation-based skip patterns, do conflict-safe status updates via `resource.UpdateObject`, configure `BasicReconcileOptions` (namespace, label/field filters, finalizer management), use `Watcher` for event-style handling, reconcile `UnmanagedKinds` (resources your app doesn't own), and register the whole thing in `app.go`. Use when writing a reconciler, implementing the reconcile loop, adding async business logic, handling create/update/delete events, processing resource state changes, scheduling periodic resyncs with `RequeueAfter`, picking between Watcher and Reconciler, or wiring a controller into `app.go` — even when the user says "process this resource", "handle X events", or "write a controller" without saying "reconciler".

Evaluate open source package health before adoption. Use when the user says "should I use this package", "is lodash well-maintained", "endor score express", "package health", "compare lodash vs underscore", "evaluate this dependency", or wants activity, popularity, security, and quality scores. Do NOT use for checking known CVEs in a package (/endor-check) or scanning the whole repo (/endor-scan).

Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.

Full build workflow for adding new syscall descriptions to syzkaller

Produce a gradeable rubric file from an issue, PRD, or free-form goal — sharpened to the standard required by Anthropic's Managed Agents user.define_outcome event. Sidecar artifact (issues/NNN-*.rubric.md or rubrics/SLUG.md); does not modify source files. Use when the user wants to define "what done looks like" for grader-checkable success criteria. Triggers: /write-a-rubric, "write a rubric", "outcome rubric", "define-outcome", "managed-agent outcome", "make this gradeable".

Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when the user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.

Break a PRD or feature description into implementable user stories with acceptance criteria. Use when handing off to engineering or breaking down work for sprint planning.

Use when releasing a new plugin version, bumping versions, creating git tags, or publishing GitHub releases for this marketplace

Explores a Spring Boot application and builds primary context: tech stack, module structure, domain entities, REST endpoints. Triggers on explicit requests: "explore project", "describe project", "project overview", "what is this project", "project structure", "tech stack", "give me context about the project", or whenever you need to understand the project before starting any task.

Safety rules, workflows, and tool reference for debugging applications via IntelliJ debugger: breakpoints, debug sessions, stepping, evaluating expressions, inspecting runtime state. TRIGGER when: user wants to debug, investigate a bug, set breakpoints, inspect runtime behavior, step through code, or understand why code behaves unexpectedly at runtime. Trigger phrases (EN): "debug", "breakpoint", "step through", "step into", "step over", "why does this crash", "why is this null", "launch in debug mode", "trace execution", "run with debugger", "evaluate expression". Trigger phrases (RU): "отладить", "дебаг", "брейкпоинт", "почему падает", "пошагово пройти", "зайти в метод", "посмотреть значение переменной", "запустить в режиме отладки", "почему null", "стектрейс". Also trigger when user wants to understand runtime behavior or investigate incorrect behavior.

Query and manage Google NotebookLM notebooks with persistent profile auth, source sync, batch/multi queries, and structured exports. Use when user asks to query NotebookLM, 'ask my notebook', shares NotebookLM notebook URLs, wants to list/create notebooks, manage sources, do bulk folder sync, dedupe, or audit exports.

Clarify ambiguous requirements through focused dialogue before implementation. Use when requirements are unclear, features are complex (>2 days), or involve cross-team coordination. Ask two core questions - Why? (YAGNI check) and Simpler? (KISS check) - to ensure clarity before coding.

Clarify ambiguous requirements through focused dialogue before implementation. Use when requirements are unclear, features are complex (>2 days), or involve cross-team coordination. Ask two core questions - Why? (YAGNI check) and Simpler? (KISS check) - to ensure clarity before coding.

Manual-only skill for minimizing total codebase size. Only activate when explicitly requested by user. Measures success by final code amount, not effort. Bias toward deletion.

Per-trade smart-money signals — each result is a discrete buy or sell event from a tracked smart-money wallet, with trigger price, current price, max gain since trigger, and exit rate. BSC and Solana only. Use for: "smart money buy signal on $X", "any whale just bought $Y", "alpha signals in the last hour", "copy-trade-worthy signals", "trigger price and max gain on these trades", "on-chain trading signals from smart money".

Architect, build, and debug Kafka Streams apps (JVM-embedded stream processing). Use when user mentions KStream, KTable, topology, TopologyTestDriver, StreamsBuilder, interactive queries, GlobalKTable, joins/windows/aggregations, or debugging issues (rebalancing, state stores, lag, deserialization errors). Also use when user wants to optimize Kafka Streams for WarpStream or tune Kafka Streams client configuration for WarpStream. Do NOT trigger for Flink, connectors, CDC, or plain producer/consumer.

Run Warden to analyze code changes before committing. Use when asked to "run warden", "check my changes", "review before commit", "warden config", "warden.toml", "create a warden skill", "add trigger", or any Warden-related local development task.