
Claude Skills by narrative-io
github.com/narrative-ioApply a set of Rosetta Stone attribute mappings to a Narrative dataset by wrapping them in a one-shot workflow that calls the `CreateRosettaStoneMappingsIfNotExist` task. Consumes the structured output of `/generate-rosetta-stone-mappings`, normalizes the generator's snake_case to the workflow task's camelCase, re-validates every expression against the dataset's current schema, gates on user approval, submits via `narrative_workflows_create`, polls the triggered run, and reports per-mapping c...
Author and submit a Narrative workflow from a natural-language intent. Picks the closest example from `assets/examples/`, adapts it to the user's case, walks the YAML against the spec, resolves the data plane, and submits via `narrative_workflows_create` only after the user has approved the rendered spec. Use when: "create a workflow that does X", "schedule a daily refresh of dataset Y", "wrap this NQL as a workflow", "build a pipeline that creates view A then refreshes view B", "submit this ...
Translate a fuzzy analytical question into a rigorous investigation plan. Interrogates the ask, grounds the plan in the available data dictionary, applies analytical best practices, and produces a structured brief of query specifications for a downstream query-writing skill. Plans, does not write SQL. Use when: "why did X drop", "is there a relationship between A and B", "who are our highest-value customers", "what's driving the change in Y", "investigate this trend", "design an analysis for"...
Find the canonical Rosetta Stone attribute that best matches a fuzzy description, semantic phrase, or required schema shape. Searches the catalog with pagination, describes the shortlist in one batched call, ranks candidates by name + shape match, and returns the canonical attribute ID plus close alternatives. Use when: "find the X attribute", "what's the graph-edge attribute ID", "look up the email Rosetta Stone attribute", "search the attribute catalog for Y", "which attribute has SOURCE_ID...
Generate, evaluate, and improve Rosetta Stone attribute mappings for a Narrative dataset. Use when: "map this dataset to Rosetta Stone", "suggest normalized attributes for dataset N", "evaluate the mappings on dataset N", "why is this mapping low confidence", "fix this expression", "improve this NQL mapping expression". (narrative-common)
Write, validate, and (optionally) execute an NQL query against a Narrative dataset. Drafts the query from the user's question, runs `narrative_nql_validate` until it compiles, explains the query in plain English, and only runs it on explicit approval (or when invoked with `--run`). Use when: "write an NQL query for X", "query this dataset", "validate this NQL", "run NQL against dataset <id>", "how many rows match Y", "show me the top N records from <dataset>". (narrative-common)
Interactively build a Narrative identity graph workflow from one or more first-party datasets and (optionally) third-party data sources. Confirms each input dataset is mapped to the Rosetta Stone graph edge attribute (mapping it via /generate-rosetta-stone-mappings if not), then composes and submits a workflow that unions every edge source and labels connected components. Use when: "build an identity graph", "generate an identity graph", "create an identity graph", "stitch these datasets into...
Audit a dataset or access rule before it joins an identity-graph build (access rules behave like datasets in NQL and are used interchangeably here). Enumerates failure modes (hub identifiers, high-degree nodes, behaviorally suspicious values, over-connected identifiers, source-specific quirks), tests hypotheses in parallel, quantifies damage by rows / edges / entities, proposes minimal filters ranked by severity, and — when issues are found — returns a validated `CREATE MATERIALIZED VIEW` NQL...
Compare your data to a partner's data in the marketplace. Given a dataset you already own with person/edge data, this skill walks you through picking a partner data source to match against, choosing which identifier types to match on, optionally selecting which enrichment attributes to attach, and then submits the report — returning overlap, match counts, and demographic coverage. Use when: "how does my data compare to your marketplace", "compare my data to [partner]", "how much overlap do I ...