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datadog-dashboards

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Corrects the wrong defaults a model has when building Datadog dashboards, verified against Datadog's docs in July 2026. Use when creating, editing, or reviewing a Datadog dashboard — choosing widgets, writing metric/log/span queries, or emitting widget JSON. Covers the queries that render a plausible number and are still wrong — `.as_count()` is appended automatically in the graph editor but never through the API, so programmatic counts silently average; `p95` resolves only on distribution metrics, and averaging one is an average of averages; ratios need `.as_count()` on both sides or they divide interpolated averages. Also covers grounding queries in metrics that exist rather than invented names, wire type strings that diverge from UI names (Pie Chart is `sunburst`, Table is `query_table`), and Datadog's own layout standard. Assumes the Datadog MCP server is connected. NOT for Terraform or raw Dashboard API management, monitor and SLO authoring, or non-Datadog observability tools.

skills/.experimental/datadog-dashboards/SKILL.md

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Aug 15, 2026
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MIT

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# Datadog Dashboards

The decisions Datadog forces when you build a dashboard, and how to settle them. Every rule names the wrong default it corrects; there is no rule for what the model already gets right.

**Pinned to a date, not a version.** Datadog ships continuously, so every claim here was verified against docs.datadoghq.com in **July 2026**. Re-verify before trusting anything version-shaped — deprecations here (`q`, `default`, `is_read_only`, `week_before()`) still parse today.

**Assumes the Datadog MCP server is connected** (`https://mcp.<site>/v1/mcp`, `toolsets=dashboards,widgets`). Widget schemas are deliberately *not* restated in this skill — `get_widget_reference` returns them current at call time, and a copy here would go stale. If the server is not connected, set it up first (`ship-endpoint-follows-the-site`); this skill does not cover Terraform or raw API management.

## When to Apply

Use this skill when:

- Creating or editing a Datadog dashboard, or reviewing one someone else built — especially a board assembled programmatically rather than in the graph editor, which is where the `.as_count()` divergence bites
- Writing any Datadog query destined for a widget: metric queries with space aggregators and modifiers, or `logs` / `spans` / `rum` queries with `search` + `compute` + `group_by`
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