dt-app-notebooks

The dt-app-notebooks skill teaches an agent how to work with Dynatrace notebooks, which are JSON documents stored in the Document Store that hold an ordered array of sections — markdown blocks for narrative and DQL blocks for queries with visualizations. It solves the problem of authoring and maintaining these notebooks correctly by codifying the JSON schema, the mandatory create/update workflow, and the rules that keep generated notebooks valid rather than leaving an agent to guess at structure.

The skill documents the full notebook JSON shape (name, type, content.version, defaultTimeframe, and per-section state), section types (markdown, dql, and the rare function), and the supported visualization types grouped into time-series, categorical, single-value/gauge, tabular, distribution/status, geographic map, and matrix/correlation families with their required field types. It prescribes a mandatory-order workflow: load domain skills before generating DQL, validate every section query, always download an existing notebook with dtctl before modifying it (never reconstruct JSON from scratch, which would silently overwrite UI edits), and deploy with dtctl apply so validation runs automatically. Reference files cover analyzing existing notebooks, section field requirements, and the create/update sequence.

It targets Dynatrace platform engineers, SREs, and observability practitioners who build dashboards and analysis notebooks, plus anyone automating notebook generation. Typical uses include creating a service-health notebook, adding a DQL visualization section, extracting queries from an existing notebook, or updating a notebook safely without clobbering manual edits.