512 skills found ¡ Page 10 of 18
timescale / design-postgres-tablesUse this skill for general PostgreSQL table design. **Trigger when user asks to:** - Design PostgreSQL tables, schemas, or data models when creating new tables and when modifying existing ones.
timescale / find-hypertable-candidatesUse this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables.
benchflow-ai / pubchem-databaseQuery PubChem via PUG-REST API/PubChemPy (110M+ compounds). Search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics.
benchflow-ai / d3-visualizationBuild deterministic, verifiable data visualizations with D3.js (v6). Generate standalone HTML/SVG (and optional PNG) from local data files without external network dependencies
benchflow-ai / unit-commitment-data-modelingUse for parsing structured unit commitment input data from JSON, CSV, benchmark cases, spreadsheets, databases, or nested tables; finding fields for time periods, resources, load, reserve, generator limits, initial conditions, startup data, renewable availability, and production costs without assumiâĻ
benchflow-ai / lab-unit-harmonizationComprehensive clinical laboratory data harmonization for multi-source healthcare analytics. Convert between US conventional and SI units, standardize numeric formats, and clean data quality issues.
benchflow-ai / xlsx-parsingRead Microsoft Excel (.xlsx) files robustly with `openpyxl` (or `pandas`). Covers multi-sheet workbooks, header rows, empty cells, merged cells, comma-separated list cells, and converting a sheet to a list-of-dicts the rest of your code can consume
benchflow-ai / senior-data-scientistWorld-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence.
benchflow-ai / nws-flood-thresholdsDownload flood stage thresholds from NWS (National Weather Service)
Besty0728 / unity-assetManage Unity AssetDatabase operations
cbrock84 / business-intelligenceBuilds reporting and self-serve analytics that people actually use â metric trees, dashboard design, distribution, and the discipline that stops dashboards proliferating.
cbrock84 / chief-data-officerOwns data as an asset â governance, quality, the warehouse and semantic layer, analytics capability, and the governance of models built on top.
cbrock84 / data-modelingDesigns the warehouse and semantic layer â source-to-mart structure, dimensional modeling, grain, slowly changing dimensions, and the metric layer analytics reads through.
cbrock84 / marketing-analyticsSets up, audits, and reports on marketing measurement â tracking plans, event schemas, attribution models, and the dashboards built on them.
cbrock84 / api-designDesigns interfaces that survive their consumers â resource modeling, errors, versioning, pagination, and compatibility. Use this to design a new API, review one before it ships, decide how to version or deprecate, fix an interface consumers keep misusing, or work out whether a change is breaking.
alchaincyf / huashu-material-searchæį´ĸä¸Ēäēēį´ æåē1800+æĄįåŽįģååč§įšīŧä¸ēå 厚åĸå äēēåŗãåŊį¨æˇæå°"ä¸Ēäēēįģå"ã"įåŽæĄäž"ã"į´ æ"ã"äēēåŗ"æļäŊŋį¨ã
Kaelio / metabase_ingestConvert Metabase questions, models, and metrics into ktx Semantic Layer source definitions. Covers result-metadata to KSL column type mapping, FK/PK detection, near-duplicate deduplication, pre-aggregation decomposition, join-graph connectivity, and how to react to priorProvenance from earlier ingesâĻ
Kaelio / lookml_ingestMap a LookML view/model/explore into ktx semantic layer sources. Covers the LookML to ktx primitive table, provenance tagging, and three worked examples (overlay, standalone from derived_table, standalone with sql_always_where). Load when the turn contains `.lkml` content.
Kaelio / slktx's semantic layer - a structured catalog of sources (tables/views), measures, joins, and segments expressed as YAML. Covers the schema and how to query it via `sl_query`
maxrave-dev / data-layer-footgunsRoom/SQLite, DataStore and repository traps: migrations, NOT IN with NULLs, LIKE escaping, delete order, local-time bucketing, imports, caching, paging. Use before writing a query or migration, or when data comes back wrong.
daymade / douban-skillExport and sync Douban (čąįŖ) book/movie/music/game collections to local CSV files via Frodo API. Supports full export (all history) and RSS incremental sync (recent items)
CloudAI-X / convex-backendConvex backend development guidelines
first-fluke / oma-backendImplement server APIs, authentication, and application data access.
utkusen / sast-sqliDetect SQL injection vulnerabilities in a codebase using a three-phase approach: recon (find unsafe SQL construction sites), batched verify (trace user input to those sites in parallel subagents, 3 sites each), and merge (consolidate batch results).
Anil-matcha / notionWork with Notion: search pages, read page properties, query databases, create pages, append blocks, update page properties. Trigger phrases: notion, notion page, notion database.
Anil-matcha / supabaseRead and write a Supabase Postgres database over PostgREST: list tables, query, insert, update, and delete rows. Trigger phrases: supabase, supabase table, query supabase.
Anil-matcha / neonInspect Neon serverless Postgres: projects, branches, databases. Branch create and delete need exact-match confirmation; connection passwords are masked. Trigger phrases: neon, serverless postgres, database branch, postgres project.
Anil-matcha / podbeanManage Podbean podcast hosting: podcasts and episodes via OAuth API. Trigger phrases: podbean, podcast hosting, publish episode, podcast episodes.
uphiago / hunt-schema-enumerationEnumerate hidden tables, fields, and endpoints via API error hints. Agnostic across PostgREST, Zod, FastAPI, GraphQL, and REST.
gooseworks-ai / lead-qualificationLead qualification engine with conversational intake. Asks structured questions to understand your qualification criteria, generates a reusable qualification prompt, then batch-enriches leads via Apify LinkedIn scraping and scores them with parallel processing.
