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Found 1,289 Skills
Create analytics question files (.question.yml) in Steedos projects. Questions are report/chart definitions stored as YAML seed data files, based on the @steedos-labs/analytics package (Metabase engine). Covers file format, dataset_query structure (MBQL), display types, visualization_settings, result_metadata, and file naming conventions.
MUST be used when user asks to document TypeScript or Vue code — add TSDoc/JSDoc blocks, docblocks, или «задокументировать» functions, classes, methods, interfaces, type aliases, enums, generics, Vue composables, defineProps/defineEmits/defineModel. Enforces strict TSDoc spec (tsdoc.org) and writes all descriptions in Russian. Triggers on phrases like «добавь tsdoc», «задокументируй», «напиши док», «add tsdoc», «document this», «generate jsdoc».
Create, refine, review, critique, or iterate on page briefings under `stardust/briefings/**/*.md` (including `_site.md`) — intent, audience, key messages, CTAs, tone, page copy (headlines, hero, section copy), imagery direction, plus site-level information architecture and multi-page content reuse maps. Sole source of truth for page copy. Independent of brand extraction: can be authored before or after `/stardust:brand`. Use when the user wants to plan pages, write briefings, define audience or CTAs, plan imagery, map shared sections across pages, when the user asks to change, refine, refactor, review, improve, polish, critique, or iterate on any file under `stardust/briefings/`, or whenever the user asks to modify a file under `stardust/briefings/**/*.md`.
Execute a verified plan document. Consumes verification receipts from tl-agent-plan-audit to avoid redundant re-verification. Defines the trust model, staleness protocol, and exit gate execution process. Use when executing a .plan.md file, starting plan implementation, or when the user says "implement the plan" or "execute the plan".
Use this skill when you need to create or modify a LookML Model file (.model.lkml). This includes defining connections, includes, and configuring model-level settings.
Run the SPARC Specification phase — gather requirements, define acceptance criteria, identify constraints, and store the spec in memory
Extract a validated learning from the current session, store it in the central agent learnings file, and sync the resulting Learnings section into the agent definitions used by the supported CLIs. User-only maintenance workflow for durable agent guidance.
Design and build database schemas and data models in MotherDuck. Produces a file-based project scaffold. Use when creating tables, choosing data types, defining relationships, or restructuring data for analytics workloads.
Create, visualize, and analyze lithological and stratigraphic logs for well data. Use when Claude needs to: (1) Create lithology columns from depth intervals, (2) Parse geological descriptions into structured logs, (3) Visualize stratigraphic columns with patterns and colors, (4) Perform well-to-well correlations, (5) Extract statistics like net-to-gross ratios, (6) Define rock type lexicons and legends, (7) Export lithology data to CSV/LAS/JSON.
Query and search the EMBL-EBI Ontology Lookup Service (OLS) for biomedical ontology terms, definitions, and hierarchies across 250+ ontologies (e.g., GO, DOID, HP). Use when the user asks to search for terms, retrieve details, navigate hierarchies (parents, children, ancestors), look up properties and individuals, get autocomplete suggestions, or access ontology metadata and statistics.
Scaffolds a production-ready TypeScript CLI project with ESM, tsdown, vitest, oxlint, oxfmt, changesets, GitHub Actions, and an agent skill definition. Use when creating a new CLI tool, bootstrapping a TypeScript project, scaffolding a node CLI, starting a new npm package, or asking "scaffold a CLI project."
Translate approved GDDs + architecture into epics — one epic per architectural module. Defines scope, governing ADRs, engine risk, and untraced requirements. Does NOT break into stories — run /create-stories [epic-slug] after each epic is created.