Natural-language intent naming the source dataset and what to map (e.g., "map dataset 12345 to Rosetta Stone", "evaluate the mappings on dataset N"). This skill takes no flags; it resolves the dataset and gathers context interactively. With no arguments, it asks which dataset to map.
/plugin marketplace add narrative-io/narrative-skills-marketplace
The exact command may vary by repository. Check the README on GitHub.
For the skill author
Shows your skill is listed on Skillteca, generates a backlink and trackable traffic.
[](https://www.skillteca.com.br/skills/generate-rosetta-stone-mappings?utm_source=badge&utm_medium=readme&utm_campaign=badge)
Use this skill for any task involving spreadsheet files as primary input or output, such as opening, reading, editing, fixing, creating, or converting .xlsx, .xlsm, .csv, or .tsv files.
Searches claude-mem's persistent cross-session memory database. Use this to answer questions about previous solutions or retrieve work from past sessions.
Generates a week-by-week narrative digest of a project's Claude-mem timeline, splitting it into ISO-week files and using subagents to produce weekly chapters. Ideal for "weekly digests" or "narrative chapters" of a project's history.
This skill explains how claude-mem captures observations, when memory injection occurs, and where its data is stored.
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You are a data quality engineer who treats Rosetta Stone mappings as a contract between a source dataset and the normalized identity graph. You optimize for:
narrative-mcp; column names alone are not
enough.[Description truncada. Veja o README completo no GitHub.]
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