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Use when the user wants to create, update, pull, push, or delete SLO definitions. Trigger on phrases like \"create an SLO\", \"update SLO objective\", \"push SLO\", \"pull SLOs\", \"delete SLO\", or \"GitOps sync SLOs\". For checking SLO health or status, use slo-check-status instead. For investigating a breaching SLO, use slo-investigate instead.\nallowed-tools: Bash, Read, Write, Edit\n---\n\n# SLO Management\n\nCreate, update, sync, and delete SLO definitions using gcx.\n\n## Core Principles\n\n1. Use gcx commands exclusively — do not call Grafana APIs directly\n2. Always run `--dry-run` before any push operation; proceed only if dry-run succeeds\n3. Trust the user's expertise — skip explanations of SLO concepts\n4. Use `-o json` for agent processing; default table\u002Fyaml for user display\n5. Auto-resolve datasource UIDs; only ask if auto-discovery fails\n\n## Query Type Decision Table\n\nSelect query type based on what the user describes:\n\n| User describes | Query type |\n|----------------|------------|\n| \"percentage of successful requests\", \"success rate\", \"error rate\" | `ratio` |\n| \"raw PromQL expression\", \"custom metric formula\" | `freeform` |\n| \"metric above\u002Fbelow threshold\", \"latency under X ms\", \"availability percentage\" | `threshold` |\n\n## Metric-Pattern Decision Table\n\nUse the metric name suffix to pick the query type when the user provides a metric name:\n\n| Metric suffix \u002F type | Query type | Rationale |\n|----------------------|------------|-----------|\n| `_total` counter | `ratio` | success_total \u002F all_total |\n| `_bucket` histogram | `threshold` | use le-bound threshold on quantile |\n| `_gauge` or `up` metric | `threshold` | compare to fixed threshold |\n| None of the above | `freeform` | last resort only |\n\n**Guardrail:** Freeform is a last resort. Before choosing freeform, verify the SLI cannot be expressed as ratio or threshold.\n\n**Hard requirement:** Freeform queries MUST use `$__rate_interval` in all `rate()`\u002F`increase()` calls. Literal ranges like `[5m]` are rejected by the SLO API.\n\n## Workflow 1: Create New SLO\n\n### Step 1: Determine query type using the decision table above\n\n### Step 2: Resolve destination datasource UID\n\n```bash\ngcx datasources list --type prometheus\n```\n\nUse the UID from the output. Some stacks do not populate `type` in the list\nresponse, so the filter can come back empty even though Prometheus datasources\nexist — in that case list everything and pick the canonical Grafana Cloud\nPrometheus entry (name like `grafanacloud-\u003Cstack>-prom`):\n\n```bash\ngcx datasources list\n```\n\nIf that leaves zero or multiple plausible Prometheus candidates, ask the user\nwhich UID to use rather than guessing (the stack's `default: true` datasource\nis not necessarily Prometheus).\n\n### Step 3: Build YAML from the appropriate template\n\nFor complete ratio, freeform, and threshold templates (including alerting, labels, and folder fields), see [references\u002Fslo-templates.md](references\u002Fslo-templates.md). Key structure:\n\n```yaml\napiVersion: slo.ext.grafana.app\u002Fv1alpha1\nkind: SLO\nmetadata:\n  name: \"\"        # leave empty for new SLO (server assigns UUID on create)\nspec:\n  name: \"my-api-availability\"\n  description: \"API availability over 28 days\"\n  query:\n    type: ratio   # freeform | ratio | threshold\n    ratio:        # field matches type\n      successMetric:\n        prometheusMetric: http_requests_total{status!~\"5..\"}\n      totalMetric:\n        prometheusMetric: http_requests_total\n      groupByLabels: [cluster, service]\n  objectives:\n    - value: 0.999   # 0.9 to 0.9999 typical range\n      window: 28d    # 7d | 14d | 28d | 30d\n  destinationDatasource:\n    uid: \u003Cprometheus-uid>\n```\n\n### Step 4: Validate with dry-run, then push\n\n```bash\ngcx slo definitions push slo.yaml --dry-run\ngcx slo definitions push slo.yaml\n```\n\n**Push semantics:**\n- `metadata.name` empty → always creates (server assigns UUID)\n- `metadata.name` set to UUID → upsert (updates if exists, creates if not)\n\nAfter creation, server assigns UUID. Run `gcx slo definitions list` to confirm.\n\n## Workflow 2: Update Existing SLO\n\n### Step 1: Get current definition\n\n```bash\ngcx slo definitions get \u003CUUID> -o yaml > slo.yaml\n```\n\n### Step 2: Modify the YAML file\n\nEdit the relevant fields (objective value, query, alerting, etc.).\nDo not modify `metadata.name` (UUID) or `readOnly` fields.\n\n### Step 3: Dry-run, then push\n\n```bash\ngcx slo definitions push slo.yaml --dry-run\ngcx slo definitions push slo.yaml\n```\n\n## Workflow 3: GitOps Sync (Pull\u002FPush)\n\n### Pull all SLOs to disk\n\n```bash\ngcx slo definitions pull -d .\u002Fslos\n# Writes to .\u002Fslos\u002FSLO\u002F\u003Cuuid>.yaml\n```\n\n### Push directory of SLOs\n\n```bash\ngcx slo definitions push .\u002Fslos\u002FSLO\u002F*.yaml --dry-run\ngcx slo definitions push .\u002Fslos\u002FSLO\u002F*.yaml\n```\n\n## Workflow 4: Delete SLO\n\n### Step 1: Confirm SLO identity\n\n```bash\ngcx slo definitions list\ngcx slo definitions get \u003CUUID>\n```\n\nConfirm the UUID and name with the user before deletion.\n\n### Step 2: Delete\n\n```bash\ngcx slo definitions delete \u003CUUID> --force\n```\n\nUse `--force` to skip the confirmation prompt when running in agent mode\n(there is no `-f` shorthand on delete).\n\n## Configuration Guidance\n\n**Objective values** (stored as 0–1, displayed as percentage):\n- Typical range: 0.9 (90%) to 0.9999 (99.99%)\n- Common starting points: 0.99 (99%), 0.999 (99.9%), 0.9999 (99.99%)\n\n**Window options:** `7d`, `14d`, `28d`, `30d`\n- 28d is most common; matches many SLO frameworks\n- Shorter windows (7d) react faster but have higher variance\n\n**Alerting best practices:**\n- `fastBurn`: Pages on-call (high burn rate, short window — catches rapid budget consumption)\n- `slowBurn`: Creates tickets (low burn rate, long window — catches gradual degradation)\n\n**Labels:** Use consistent label keys (team, service, environment, tier) for filtering and grouping.\n\n**GroupByLabels** (ratio\u002Fthreshold queries): Add labels like `cluster`, `service`, `endpoint` for dimensional breakdown in status and investigation.\n\n## Output Format\n\nAfter create\u002Fupdate:\n```\nSLO: \u003Cname>\nUUID: \u003Cuuid>\nStatus: Created | Updated\nObjective: \u003Cvalue>% over \u003Cwindow>\nDatasource: \u003Cuid>\n```\n\nAfter pull:\n```\nPulled \u003CN> SLO definitions to \u003Cdir>\u002FSLO\u002F\n```\n\nAfter delete:\n```\nDeleted: \u003Cuuid> (\u003Cname>)\n```\n\n## Error Handling\n\n- **Push fails with 400**: Check YAML structure matches template; verify `destinationDatasource.uid` is valid\n- **Push fails with 404 on update**: UUID in `metadata.name` not found; check with `gcx slo definitions list`\n- **Pull creates empty directory**: No SLOs in this context; check `gcx config view` for active context\n- **`--type prometheus` filter returns empty**: the list API may not populate `type` on this stack; run `gcx datasources list` without the filter and match the Cloud 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Trigger on phrases like \"list conversations\", \"search generations\", \"what did the agent do\", \"debug LLM conversation\", \"create evaluator\", \"set up evaluation rule\", \"test evaluator\", \"check scores\", \"evaluate generation quality\", or \"set up online evaluation\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1850,1853,1854,1857],{"name":1851,"slug":1852,"type":15},"Agents","agents",{"name":9,"slug":8,"type":15},{"name":1855,"slug":1856,"type":15},"Monitoring","monitoring",{"name":13,"slug":14,"type":15},"2026-07-25T05:30:40.29622",{"slug":1860,"name":1860,"fn":1861,"description":1862,"org":1863,"tags":1864,"stars":20,"repoUrl":21,"updatedAt":1874},"agento11y-instrument","instrument LLM apps for agent observability","Sets up and instruments a developer's own LLM app or agent to send generations and agentic workflow to Grafana Agent Observability (the Agent Observability SDKs) — greenfield setup, fixing broken instrumentation, or filling gaps in existing instrumentation. Uses gcx for the parts a static prompt can't do: `gcx login` \u002F `gcx cloud stacks` to find the stack, and `gcx agento11y agents|conversations|generations` to VERIFY that data actually lands — so it iterates (instrument → run → verify → fix) until generations arrive, not blindly. Reads the app's code, detects language\u002Fframework, classifies instrumentation state (none \u002F partial \u002F broken), then runs a fixed gap checklist whose #1 item is the silent failure no other prompt catches: the SDK emits OTel spans\u002Fmetrics but never creates a TracerProvider\u002FMeterProvider, so without them all metrics go to a no-op and are lost. Also checks agent_version (required for per-version Performance charts), set_result completeness, SYNC vs STREAM, parent_generation_ids DAG links, and workflow-step coverage. Recommends changes citing file:line and, only with explicit confirmation, applies minimal diffs that don't change app behavior. Pulls SDK reference from agento11y's llms.txt rather than restating it, and hands off to `agento11y-test-starter` once data flows. It does NOT write test suites or set up tenant evaluations, rules, or guards — offline test suites are `agento11y-test-starter`, tenant eval rules + guards are `agento11y-prod-setup`; does NOT install coding-agent telemetry plugins (that is llms.txt \"Path A\"); does NOT mint or store credentials or invent endpoints. Trigger on phrases like \"instrument my app\", \"send my agent's traces to Grafana\", \"set up AI observability for my app\", \"my generations aren't showing up\", \"why is Performance empty\", \"add Agent Observability to my code\", \"fix my instrumentation\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1865,1866,1867,1870,1873],{"name":1851,"slug":1852,"type":15},{"name":9,"slug":8,"type":15},{"name":1868,"slug":1869,"type":15},"Instrumentation","instrumentation",{"name":1871,"slug":1872,"type":15},"LLM","llm",{"name":13,"slug":14,"type":15},"2026-07-31T05:53:52.580237",{"slug":1876,"name":1876,"fn":1877,"description":1878,"org":1879,"tags":1880,"stars":20,"repoUrl":21,"updatedAt":1887},"agento11y-prod-setup","setup production evaluation for AI agents","Sets up production evaluation and guardrails for a DEPLOYED AI agent in Grafana Agent Observability, grounded in the agent's own code and its real ingested traffic. The judgment layer on top of the `agento11y` skill: it reads the agent's source (system prompt, tools, entrypoint) AND samples its live traffic via gcx, checks what evaluators\u002Frules\u002Fguards already exist, then recommends only what's missing — online eval rules (score live conversations for regressions) and guards (warn-first request-path policies that redact \u002F tool-filter and may later be promoted to deny). It drafts reviewable YAML and, only with explicit confirmation, applies via `gcx agento11y`. New guards are drafted in warn mode (safe on live traffic — warn records but never blocks). It DOES create stack-level objects — that is the point — but every write is confirmed. It never rewrites or redeploys the agent. Trigger on phrases like \"set up production evaluation\", \"my agent is in prod what should I evaluate\", \"catch quality regressions\", \"add guardrails to my agent\", \"redact PII from my agent\", \"block dangerous tools\", \"set up online evals and guards\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1881,1882,1885,1886],{"name":1851,"slug":1852,"type":15},{"name":1883,"slug":1884,"type":15},"Evals","evals",{"name":9,"slug":8,"type":15},{"name":13,"slug":14,"type":15},"2026-07-31T05:53:53.576347",{"slug":1889,"name":1889,"fn":1890,"description":1891,"org":1892,"tags":1893,"stars":20,"repoUrl":21,"updatedAt":1902},"agento11y-test-starter","build and run agent test suites","Use early in an AI-agent project — before ship, before real traffic — to build a starter test suite for the agent and run it offline. Reads the agent's own code (system prompt, tools, task), writes a labeled draft suite of test cases (happy\u002Fedge\u002Fadversarial) grounded in real lines, and recommends how to score each case (the evaluators\u002Fjudges the offline runner uses). Assesses how runnable the agent is: for an easily-invoked agent it generates a runner stub (run_experiment.py) with two holes to fill and can optionally run it (only with permission, only against the endpoint the developer configured); for agents needing a harness or full runtime it points to the existing eval infra. It runs OFFLINE and never creates tenant-level evaluators, rules, or guards — that is `agento11y-prod-setup`, for a deployed agent with real traffic. Trigger on phrases like \"how do I test my agent before shipping\", \"write test cases for my agent\", \"set up tests for my agent\", \"check my agent before prod\", \"I have no traffic yet, how do I evaluate it\", \"test my agent offline\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1894,1895,1896,1899],{"name":1851,"slug":1852,"type":15},{"name":9,"slug":8,"type":15},{"name":1897,"slug":1898,"type":15},"QA","qa",{"name":1900,"slug":1901,"type":15},"Testing","testing","2026-07-31T05:53:51.62785",{"slug":1904,"name":1904,"fn":1905,"description":1906,"org":1907,"tags":1908,"stars":20,"repoUrl":21,"updatedAt":1919},"create-dashboard","create Grafana dashboards with gcx","Designs and creates Grafana dashboards with gcx, using `gcx dashboards snapshot` as a visual feedback loop. Use when the user wants to create a new Grafana dashboard, add panels, variables, or annotations to an existing dashboard, design dashboard panels, variables, queries, or layout, or make a material visual redesign. Triggers on \"create dashboard\", \"new dashboard\", \"build dashboard\", \"dashboard for \u003Cservice>\", \"add panels\", \"add variable\", \"add annotation\", \"improve this dashboard\", or \"iterate on a dashboard\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1909,1912,1915,1918],{"name":1910,"slug":1911,"type":15},"Dashboards","dashboards",{"name":1913,"slug":1914,"type":15},"Data Visualization","data-visualization",{"name":1916,"slug":1917,"type":15},"Design","design",{"name":9,"slug":8,"type":15},"2026-07-25T05:30:46.289717",{"slug":1921,"name":1921,"fn":1922,"description":1923,"org":1924,"tags":1925,"stars":20,"repoUrl":21,"updatedAt":1934},"debug-with-grafana","investigate application issues with Grafana","Structured workflow for investigating application problems with Grafana observability data (metrics, logs, traces) via gcx. Covers live firefighting AND retrospective incident analysis: incident triage, root-cause analysis, blast-radius checks (did an incident spill into other services), verifying whether a deployment or rollout triggered an incident, finding which service, endpoint, or path owns the most errors or slow requests, checking whether retries or queue backlogs piled up, and quantifying error or latency shares over a time window. Trigger on: \"my API is returning 500 errors\", \"latency is spiking\", \"investigate why requests are failing\", \"triage the incident\", \"blast radius\", \"root cause\", \"did the rollout cause it\", \"which endpoint owns the most 5xx\", \"did retries pile up\", or any request to analyse an earlier incident window using telemetry. For authoring dashboards use create-dashboard; for dashboard inventory use manage-dashboards.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1926,1929,1930,1933],{"name":1927,"slug":1928,"type":15},"Debugging","debugging",{"name":9,"slug":8,"type":15},{"name":1931,"slug":1932,"type":15},"Incident Response","incident-response",{"name":13,"slug":14,"type":15},"2026-07-18T05:11:10.445428",{"slug":1936,"name":1936,"fn":1937,"description":1938,"org":1939,"tags":1940,"stars":20,"repoUrl":21,"updatedAt":1947},"diagnose-entity-graph","diagnose Grafana Entity Graph issues","Diagnose Entity Graph problems: missing entities, missing edges, disconnected clusters, or filtering issues. Use when the user reports that Entity Graph doesn't look right, services are missing, edges aren't appearing, or environments can't be filtered. Triggers for: \"entity graph is empty\", \"services missing from entity graph\", \"no edges in entity graph\", \"disconnected services\", \"can't filter entity graph\", \"entity graph not working\", \"diagnose entity graph\", \"debug knowledge graph\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1941,1942,1943,1946],{"name":1927,"slug":1928,"type":15},{"name":9,"slug":8,"type":15},{"name":1944,"slug":1945,"type":15},"Graph Analysis","graph-analysis",{"name":13,"slug":14,"type":15},"2026-07-25T05:30:39.380934",24,{"items":1950,"total":2081},[1951,1968,1987,2007,2014,2022,2029,2036,2043,2050,2057,2069],{"slug":1952,"name":1952,"fn":1953,"description":1954,"org":1955,"tags":1956,"stars":1965,"repoUrl":1966,"updatedAt":1967},"faro-setup-web","instrument web apps with Grafana Faro","Instruments a web app with Grafana Faro Web SDK for frontend observability. Use when setting up error tracking, Web Vitals, session monitoring, or distributed tracing in a browser app.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1957,1960,1963,1964],{"name":1958,"slug":1959,"type":15},"Distributed Tracing","distributed-tracing",{"name":1961,"slug":1962,"type":15},"Frontend","frontend",{"name":1855,"slug":1856,"type":15},{"name":13,"slug":14,"type":15},1103,"https:\u002F\u002Fgithub.com\u002Fgrafana\u002Ffaro-web-sdk","2026-07-12T07:43:24.63314",{"slug":1969,"name":1969,"fn":1970,"description":1971,"org":1972,"tags":1973,"stars":1984,"repoUrl":1985,"updatedAt":1986},"configuring-yesoreyeram-infinity-datasource","configure Grafana Infinity data source","Configure the Infinity data source — base URL and allowed hosts, the authentication methods (basic, bearer token, API key, digest, OAuth passthrough, OAuth 2.0 client credentials\u002FJWT, Azure, Azure Blob, AWS), TLS, custom HTTP headers, network and security settings, the custom health check, and provisioning with a config file. Use when a user asks how to set up, configure, or change settings for the Infinity data source; how to authenticate to an API; how to allow hosts; how to provision it as YAML; or how to troubleshoot connection, authentication, or health-check issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1974,1977,1980,1983],{"name":1975,"slug":1976,"type":15},"API Development","api-development",{"name":1978,"slug":1979,"type":15},"Authentication","authentication",{"name":1981,"slug":1982,"type":15},"Configuration","configuration",{"name":9,"slug":8,"type":15},1056,"https:\u002F\u002Fgithub.com\u002Fgrafana\u002Fgrafana-infinity-datasource","2026-07-12T07:43:25.939136",{"slug":1988,"name":1988,"fn":1989,"description":1990,"org":1991,"tags":1992,"stars":1984,"repoUrl":1985,"updatedAt":2006},"querying-yesoreyeram-infinity-datasource","query data with Infinity datasource","Build queries with the Infinity data source — the query types (JSON, CSV, TSV, XML, GraphQL, HTML, UQL, GROQ, Google Sheets, Series, Transformations), the parsers (Frontend\u002Fsimple, Backend JSONata, JQ, UQL, GROQ) and which support alerting, the sources (URL, Inline, Reference, Azure Blob, Random walk), output formats (table, timeseries, logs, trace, node graph, dataframe), root selector and columns, computed columns\u002Ffilters\u002Fsummarize, pagination, and template variables. Use when a user asks how to query Infinity; how to fetch JSON\u002FCSV\u002FXML\u002FGraphQL\u002FHTML from a URL or inline; how to select rows and columns; how to transform data with UQL\u002FGROQ\u002FJSONata\u002FJQ; how to make a query work with alerting; how to paginate; or how to use variables in a query.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1993,1996,1999,2000,2003],{"name":1994,"slug":1995,"type":15},"CSV","csv",{"name":1997,"slug":1998,"type":15},"Data Analysis","data-analysis",{"name":9,"slug":8,"type":15},{"name":2001,"slug":2002,"type":15},"GraphQL","graphql",{"name":2004,"slug":2005,"type":15},"JSON","json","2026-07-15T05:34:05.773947",{"slug":1845,"name":1845,"fn":1846,"description":1847,"org":2008,"tags":2009,"stars":20,"repoUrl":21,"updatedAt":1858},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2010,2011,2012,2013],{"name":1851,"slug":1852,"type":15},{"name":9,"slug":8,"type":15},{"name":1855,"slug":1856,"type":15},{"name":13,"slug":14,"type":15},{"slug":1860,"name":1860,"fn":1861,"description":1862,"org":2015,"tags":2016,"stars":20,"repoUrl":21,"updatedAt":1874},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2017,2018,2019,2020,2021],{"name":1851,"slug":1852,"type":15},{"name":9,"slug":8,"type":15},{"name":1868,"slug":1869,"type":15},{"name":1871,"slug":1872,"type":15},{"name":13,"slug":14,"type":15},{"slug":1876,"name":1876,"fn":1877,"description":1878,"org":2023,"tags":2024,"stars":20,"repoUrl":21,"updatedAt":1887},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2025,2026,2027,2028],{"name":1851,"slug":1852,"type":15},{"name":1883,"slug":1884,"type":15},{"name":9,"slug":8,"type":15},{"name":13,"slug":14,"type":15},{"slug":1889,"name":1889,"fn":1890,"description":1891,"org":2030,"tags":2031,"stars":20,"repoUrl":21,"updatedAt":1902},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2032,2033,2034,2035],{"name":1851,"slug":1852,"type":15},{"name":9,"slug":8,"type":15},{"name":1897,"slug":1898,"type":15},{"name":1900,"slug":1901,"type":15},{"slug":1904,"name":1904,"fn":1905,"description":1906,"org":2037,"tags":2038,"stars":20,"repoUrl":21,"updatedAt":1919},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2039,2040,2041,2042],{"name":1910,"slug":1911,"type":15},{"name":1913,"slug":1914,"type":15},{"name":1916,"slug":1917,"type":15},{"name":9,"slug":8,"type":15},{"slug":1921,"name":1921,"fn":1922,"description":1923,"org":2044,"tags":2045,"stars":20,"repoUrl":21,"updatedAt":1934},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2046,2047,2048,2049],{"name":1927,"slug":1928,"type":15},{"name":9,"slug":8,"type":15},{"name":1931,"slug":1932,"type":15},{"name":13,"slug":14,"type":15},{"slug":1936,"name":1936,"fn":1937,"description":1938,"org":2051,"tags":2052,"stars":20,"repoUrl":21,"updatedAt":1947},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2053,2054,2055,2056],{"name":1927,"slug":1928,"type":15},{"name":9,"slug":8,"type":15},{"name":1944,"slug":1945,"type":15},{"name":13,"slug":14,"type":15},{"slug":437,"name":437,"fn":2058,"description":2059,"org":2060,"tags":2061,"stars":20,"repoUrl":21,"updatedAt":2068},"manage Grafana Cloud resources via gcx","Manages Grafana Cloud resources via the gcx CLI. Trigger when the user wants to inspect, create, update, delete, query, or automate any Grafana resource - dashboards, datasources, alerts, SLOs, synthetic checks, oncall, incidents, fleet, k6, knowledge graph, or adaptive telemetry.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2062,2065,2066,2067],{"name":2063,"slug":2064,"type":15},"CLI","cli",{"name":9,"slug":8,"type":15},{"name":1855,"slug":1856,"type":15},{"name":17,"slug":18,"type":15},"2026-07-31T05:53:50.587304",{"slug":2070,"name":2070,"fn":2071,"description":2072,"org":2073,"tags":2074,"stars":20,"repoUrl":21,"updatedAt":2080},"gcx-demo","present gcx demo tours","Run a narrated, read-only demo tour of gcx for customer or colleague presentations. Showcases the breadth of gcx across every Grafana Cloud product area — resources, datasources, metrics, logs, traces, SLOs, alerts, synthetic monitoring, IRM, k6, fleet, and more. All commands are strictly read-only. Trigger when the user says \"demo gcx\", \"show off gcx\", \"customer demo\", \"gcx tour\", or \"\u002Fgcx-demo\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2075,2076,2077],{"name":2063,"slug":2064,"type":15},{"name":9,"slug":8,"type":15},{"name":2078,"slug":2079,"type":15},"Presentations","presentations","2026-07-25T05:30:45.282458",80]