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Found 1,304 Skills
Define initial seed data for Steedos objects using .data.json, .data.yml, or .data.csv files in main/default/data/. Records are imported on service startup (insert-only) and on space initialization (upsert). Covers file naming, record structure, _id requirement, template variables (${space_id}, ${space_owner_id}), EJSON date format, and import behavior (onlyInsert vs upsert).
Concord integration. Manage data, records, and automate workflows. Use when the user wants to interact with Concord data.
ActiveProspect integration. Manage data, records, and automate workflows. Use when the user wants to interact with ActiveProspect data.
JFrog integration. Manage data, records, and automate workflows. Use when the user wants to interact with JFrog data.
ZeroTier integration. Manage data, records, and automate workflows. Use when the user wants to interact with ZeroTier data.
ClickHouse integration. Manage data, records, and automate workflows. Use when the user wants to interact with ClickHouse data.
2markdown integration. Manage data, records, and automate workflows. Use when the user wants to interact with 2markdown data.
Novel Research Skill. Used for searching and organizing writing materials, genre references, real-world research, professional details, historical and geographical information, technical data, case inspirations, visual references, and market observations; stored in research.yaml, records, or notes. Activated when users request information searching, material collection, latest updates, research verification, background authenticity, modifying research notes, or saving sources.
Oracle Fusion Cloud Financials integration. Manage data, records, and automate workflows. Use when the user wants to interact with Oracle Fusion Cloud Financials data.
Capture implementation notes after code implementation and review/fix. Records design decisions, deviations, tradeoffs, and open questions to docs/issue#XXXX.html. Triggers on: /note-it, 记录笔记, implementation notes.
Guides cleaning and standardizing tabular datasets before analysis, modeling, or reporting—profiling, quality rules, missing values, duplicates, outliers, type coercion, encoding fixes, record linkage, deduplication, high-level PII handling (not legal advice), actuarial/insurance field scrubbing, reproducible scrub pipelines, validation checks, and sign-off. Distinct from warehouse ETL or statistical modeling. Use when the user asks for "data scrubbing", "clean this dataset", "scrub the data", "data cleaning", "dedupe records", "handle missing values", "outlier treatment", "standardize columns", "data quality rules", "profile this table", or "prepare data for modeling". Not warehouse pipelines (data-warehouse-engineer), ML modeling (data-scientist, actuary), privacy programs (compliance-engineer), FinOps only (finops-analyst), or assumption governance (assumption-setting).
Placekey integration. Manage data, records, and automate workflows. Use when the user wants to interact with Placekey data.