Investigate a Grafana Cloud k6 test — describe the script, list run history, identify pass/fail status, pull raw metric time-series and log lines for one or more runs, and (if asked) safely edit the test script. Use when the user asks about a specific k6 cloud test or run, gives a `/a/k6-app/tests/<id>` or `/a/k6-app/runs/<id>` URL, asks "is this test passing", "why are my k6 tests failing", "show me metrics for run X", "show me logs for run X", or wants to add thresholds / fix a failing test. Trigger this skill even when the user doesn't explicitly say "investigate" — pasted `/a/k6-app/...` URLs, "why did run X fail", "what happened with my test", "is my test healthy", "the latest run looks weird", "checks are failing but the run says passed", or any request to diagnose a Grafana Cloud k6 run all qualify.

Author, audit, and improve Grafana SKILL.md files against Anthropic's published Agent Skills guidance and the four-dimension rubric the grafana/skills CI gate uses (conciseness, actionability, workflow clarity, progressive disclosure). Applies the canonical SKILL.md structure (YAML frontmatter + body + references/ + scripts/ + assets/), the "pushy description" trigger pattern, the three-level progressive-disclosure model, and the validate-fix-rerun feedback loop. Use when creating a new skill in this repo, when reviewing a skill PR, when a skill's Tessl review score is below 75 (the merge gate), when a skill's description isn't getting picked up by agents, when restructuring a long SKILL.md into a bundle, or when the user asks how to write, improve, optimize, audit, or fix a skill - even if they don't say "skill" explicitly (e.g. "this isn't triggering", "Tessl scored this 72", "split this doc").

Instrument any app with OpenTelemetry and ship metrics / logs / traces to Grafana Cloud or self-hosted Mimir / Loki / Tempo / Pyroscope. Covers SDK auto-instrumentation for Go, Java (Grafana JVM agent), Python (`opentelemetry-instrument`), Node.js, .NET (`Grafana.OpenTelemetry`), Beyla eBPF for zero-code; Grafana Cloud OTLP gateway + Basic-auth (instanceID + API key, base64); env-var config (`OTEL_EXPORTER_OTLP_*`, `OTEL_RESOURCE_ATTRIBUTES`); Alloy / OTel-Collector pipelines; Kubernetes Operator inject-annotations; and head + tail sampling. Use when instrumenting a service, pointing OTLP at Grafana Cloud, switching from Jaeger / Datadog / New Relic, choosing head- vs tail-sampling, or debugging "spans aren't showing in Explore" — even when the user says "auto-instrument my Java app", "send traces to Grafana", "what env vars do I set", "OTLP endpoint", or "Operator inject" without naming OpenTelemetry.

Build, modify, and ship Grafana dashboards as JSON via the HTTP API — panel types (timeseries / stat / gauge / table / heatmap / logs / traces / node-graph), `gridPos` 24-column layout, units, thresholds, template + datasource + chained variables, transformations (`organize` / `calculateField` / `filterByValue`), panel + dashboard links with `${__field.labels.x}` / `${__from}`, and Loki/Prometheus annotations. Use when scripting dashboard creation, writing the dashboard JSON for a new service, adding a `$job` dropdown variable, computing an "Error %" column with a transformation, overlaying deploys as annotations, or pushing a dashboard via `POST /api/dashboards/db` — even when the user says "create a dashboard for this metric", "add a service dropdown", "show errors as percentage", "overlay our deploys", or "export the dashboard JSON" without naming the API or schema. After every API push, verify with the returned `version` plus a GET on the dashboard UID.

Set up private network connectivity to Grafana Cloud — AWS PrivateLink, Azure Private Link, GCP Private Service Connect, and Private Data Source Connect (PDC). Provisions VPC endpoints, private endpoints, or PSC forwarding rules per signal type (metrics / logs / traces / profiles); wires Alloy to push to the private DNS endpoint instead of the public one; verifies private DNS resolution + endpoint approval state. Use when sending telemetry to Grafana Cloud without traversing the public internet, eliminating cloud egress costs, meeting PCI-DSS / HIPAA / data-residency compliance, configuring PDC for private data-source queries, or connecting AWS / Azure / GCP workloads to Grafana — even when the user says "stop paying egress", "keep our telemetry off the public internet", or "PCI compliance for Grafana" without naming PrivateLink.

Ship Kubernetes, host, container, and cloud-provider telemetry into Grafana Cloud — `k8s-monitoring` Helm chart for K8s clusters (metrics + logs + traces + events + cost), Alloy `prometheus.exporter.unix` for Linux hosts, cAdvisor + Docker discovery for containers, and CloudWatch / Azure Monitor / Google Cloud Monitoring datasource setup. Use when onboarding a new cluster or VM fleet to Grafana Cloud, picking the right Helm values for K8s scraping, wiring kube-state-metrics + node-exporter + cAdvisor, alerting on `PodCrashLooping` / node memory / PVC capacity, or pulling AWS / Azure / GCP cloud metrics — even when the user says "monitor my cluster", "send K8s metrics to Grafana", "scrape EC2 metrics", "cluster pod logs", or "install the monitoring helm chart" without naming `k8s-monitoring` or Alloy.

Set up Grafana Cloud Database Observability for MySQL and PostgreSQL — enables `pg_stat_statements` / Performance Schema, creates a least-privilege monitoring user, configures the `database_observability.postgres` / `database_observability.mysql` Alloy components, ships query samples + visual explain plans + RED metrics + schema details to Grafana Cloud, and correlates slow queries with application traces via `db.statement` / `db.system` OTel attributes. Use when monitoring database performance, diagnosing slow queries, setting up DB observability for RDS / Aurora / Cloud SQL / Azure Database / self-managed instances, correlating DB metrics with APM, or alerting on query latency — even when the user says "my database is slow", "find the slow queries", or "monitor RDS" without saying "observability".

Connect AI coding agents (Claude Code, Cursor, VS Code, OpenAI Codex) to Grafana Cloud via the `mcp-grafana` Model Context Protocol server. Installs the server with `go install`, generates a Grafana service-account token, wires `~/.claude/settings.json` or `~/.cursor/mcp.json` with the `command` + `env` block, runs `--disable-write` for safer read-only sessions, switches to SSE transport for team-shared / VS Code setups, and verifies with `/mcp` + a `list_datasources` round-trip. Use when connecting Claude Code to Grafana, setting up MCP for Grafana, configuring the Grafana MCP server, using Grafana tools in Cursor/VS Code, querying Grafana from an AI agent, sharing the MCP server across a team — even when the user says "give my agent Grafana access", "let Claude see my metrics", or "Cursor + Grafana" without saying "MCP".

Use when starting any grafana-app-sdk work — scaffolding a Grafana app, initializing a Grafana App Platform app, picking a deployment mode (standalone operator / grafana/apps / frontend-only), wiring app-specific config, or onboarding to the SDK. Covers `grafana-app-sdk` CLI install, `project init` per deployment mode, project layout, the schema-centric workflow (CUE kinds → generated code → reconciler/admission logic), and `SpecificConfig` for env-driven app configuration. Use even if the user just says "make a new app", "Grafana app platform", "kinds and watchers", "operator scaffold", or asks about `apps/` inside the Grafana repo, without naming the SDK explicitly.

Analyze the impact of upgrading a dependency before you do it. Use when the user says "should I upgrade lodash", "what breaks if I update express", "upgrade impact", "endor upgrade", "breaking changes from upgrading", or wants to find the safest version that fixes vulnerabilities. Uses pre-computed Endor Labs data — no scanning required. Do NOT use for just checking vulnerabilities (/endor-check) or applying a fix (/endor-fix).

Display and filter security findings from Endor Labs. Use when the user says "show findings", "list vulnerabilities", "what did the scan find", "endor findings", "show me critical reachable vulns", or wants to browse/filter results after a scan. Supports filtering by severity, reachability, category (vuln/sast/secrets/license). Do NOT use for running a new scan (/endor-scan) or explaining a specific CVE (/endor-explain).

Check if a specific dependency has known vulnerabilities or malware using Endor Labs. Use when the user names a package and wants to know if it's safe, says "check lodash", "is express vulnerable", "any CVEs in django", "endor check", "is this package safe", or provides a package name after installing a dependency. Do NOT use for scanning an entire repo (/endor-scan) or viewing existing findings (/endor-findings).

Core building blocks of Suricata signatures and multi-condition DPI logic

Automatically generate regression tests for Java codebases by analyzing changes between old and new code versions. Use when users need to: (1) Generate tests after refactoring or code changes, (2) Ensure previously tested behavior still works in new versions, (3) Cover modified or newly added code paths, (4) Migrate existing tests to work with updated APIs or signatures, (5) Maintain test coverage during code evolution. Supports JUnit and TestNG frameworks with unit tests, parameterized tests, and exception testing patterns.

Algolia launch, regression, and implementation QA. Use when auditing an Algolia build before release, validating relevance changes, checking search UI behavior, verifying event instrumentation, diagnosing analytics gaps, reviewing secured keys, or creating a smoke test plan for search, browse, autocomplete, indexing, and configuration changes. Do NOT use to make live account changes or inspect live account data; use algolia-mcp or algolia-cli first. Do NOT use as the primary implementation skill when the task is clearly data modeling, events setup, InstantSearch, Autocomplete, NeuralSearch, or Agent Studio; use the focused skill first and this skill for final QA.

Work with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.

Audit a workspace for recurring friction, pick the highest-leverage one, and build the automation that removes it. Use when the user asks "what should I automate", "what's wasting my time", "find the friction in my workflow", wants a self-improvement pass over their own tooling, or runs this on a recurring loop.

Opinionated guidance for constructing and interpreting Honeycomb queries on trace and event datasets — operation selection (percentiles not AVG, HEATMAP for distributions), relational field patterns (root., parent., any., none.), calculated fields, query math, and result interpretation (P99/P50 ratios, heatmap bands, TOTAL/OTHER rows, raw JSON via query_result_json). Use this skill when the user wants to query spans, traces, or log/event data in Honeycomb — requests like "show me latency", "error rate", "find slow requests", "find outliers", "interpret results", "relational fields", "calculated fields", or "download raw results". This skill covers all dataset types except metrics datasets (dataset_type=metrics) — for those, use metrics-queries instead.

Implements a use case's backend: FastAPI router, Pydantic request/response schemas, service/domain layer, and SQLAlchemy models/queries. Use when the user asks to "implement the backend for UC-xxx", "build the API endpoint", "add a FastAPI route", "write the service layer", or mentions FastAPI implementation, Pydantic schemas, or SQLAlchemy queries for a specific use case.

Evaluate a repo agent harness (AGENTS.md, rules, skills, skill refs) for broken paths/commands, redundant instructions, and usefulness using a stack-agnostic dual-judge protocol with planted traps. HIGH PRIORITY questionnaires at top: Q1 optional docs, Q2 B/C budget before Track A (certainty/tokens). A always runs after Q2; B/C opt-in. ADRs/RFCs excluded from T2. Mixed apply uses 11-mixed-apply.md (KEEP/CUT). Use when the user says harness eval, harness-eval, harness debug, audit AGENTS.md, audit skills/rules, instruction audit, redundancy of agent instructions, usefulness of skills, Ship/Review/Hold/Slim/Keep-core for harness, or wants Track A/B/C harness evaluation. Do NOT use for harness setup or init, feature spec-driven work (tlc-spec-driven), or applying Ship/Slim trims unless the user explicitly asks after the report.