Databases & data skills.
2,987 databases & data skills, including azure-kusto, google-agents-cli-eval and paper-context-resolver, are listed on Ahel today. Each one has a page of its own that says what it does and whether Ahel can serve it in Claude, Claude Code, ChatGPT, Codex and Cursor.
Category: Databases & data
2,987 results · page 98 of 100
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ml4t-fetch-dataSkillDatabases & data
Reliable data acquisition with provider abstraction and schema validation. Use when ingesting market data from APIs, databases, or files.
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ml4t-validate-dataSkillDatabases & data
Systematic data quality validation before modeling. Use when checking for gaps, outliers, stale prices, or schema violations in datasets.
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mlops-automationSkillDatabases & data
Automate an MLOps project with mise tasks, lefthook hooks, Docker images, GitHub Actions, and MLflow tracking on a SQL backend. Use when adding a task runner, git hooks, CI/CD, or experiment tracking to a working package.
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mlops-observabilitySkillDatabases & data
Make an ML system a glass box with reproducible runs, MLflow dataset lineage, drift monitoring, alerting, and SHAP explanations. Use when a deployed model needs traceability, monitoring, alerting, or explanation.
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mlops-prototypingSkillDatabases & data
Structure reproducible Jupyter notebooks with a fixed section layout, hoisted configuration, and leakage-free scikit-learn pipelines. Use when exploring a dataset, training a first model, or preparing a notebook for promotion.
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onec-extension-validateSkillDatabases & data
Validate a named 1C:Enterprise configuration extension through BSL module checks, full configuration checks, applicability checks, database update, and database `.cfe` verification. Use after creating or modifying an extension, when diagnosing why an extension cannot be applied, or before declaring
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onescience-data-standardizerSkillDatabases & data
OneScience data standardization executor skill (type=executor). Converts raw datasets into AI-Ready datasets across four domains: cfd / bio / climate(earth) / matchem. The target contract is pulled from the dataset spec.md of onescience-primitives; data sources support three-stage resolution: explic
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onescience-dataset-builderSkillDatabases & data
OneScience dataset construction execution skill, containing two independent tasks: (1) Generate a dataset build launcher script (wrapper) - receives a data processing code path (core business logic already implemented by other skills), analyzes the code's interfaces, and generates a launcher script
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onescience-primitive-distillerSkillDatabases & data
OneScience primitive distillation execution skill. Used to distill scientific-agent-skills, third-party research tools, databases, services, datasets, output formats, or workflow documentation into onescience-primitives asset packages, and to determine whether resource, expert, or executor implement
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opsSkillDatabases & data
Deploys, schema migrations, rollback and infrastructure. Use when "can I ship this on Friday", "this migration is scary", "what is the blast radius", "prevent accidental deletion of the database", or a change drops a column. Covers expand/contract, canary rollout, kill switches, prevent_destroy, tes
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sddSkillDatabases & data
Create a Software Design Document (SDD) defining component architecture, data contracts, API schemas, and platform compatibility before planning. Use in Tier 3 (Full Pipeline) or when modifying interfaces, hooks, databases, or multi-platform contracts.
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seuratmap2refSkillDatabases & data
Map query single-cell datasets to high-quality reference atlases using Seurat's reference mapping workflow. Performs label transfer, UMAP projection, and integration with reference annotations without modifying query expression data. Enables transfer learning from curated atlases like Azimuth PBMC o
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sota-data-engineeringSkillDatabases & data
State-of-the-art data engineering rules (2026) for building and auditing data pipelines and analytics infrastructure. Covers architecture and modeling (ELT, lakehouse vs warehouse, dimensional models, medallion layering), pipeline and orchestration discipline (idempotency, incremental loads, backfil
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sota-databasesSkillDatabases & data
State-of-the-art database engineering rules (2026) for designing, building, and auditing data layers. Covers engine selection, schema modeling, migrations, query and index craft, transactions and concurrency, reliability and scale, security, and vector/AI workloads. Use when designing a new data lay
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sota-golangSkillDatabases & data
State-of-the-art Go engineering rules (supported Go releases) that Claude applies when writing new Go code or auditing existing Go code. Covers error handling, interface/package design, goroutine and channel correctness, net/http hardening, security (SQL, exec, path traversal, CSPRNG, TLS, supply ch
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sota-phpSkillDatabases & data
State-of-the-art PHP engineering (supported PHP branches) for both writing new PHP and auditing existing PHP code. Covers strict_types and modern idioms (enums, readonly, match, fibers, property hooks), OWASP-grade security (SQL injection, XSS, file uploads, LFI/RFI, unserialize/Phar object injectio
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sota-rubySkillDatabases & data
State-of-the-art Ruby engineering rules (supported Ruby releases) that Claude applies when writing or auditing Ruby. Covers modern idioms (frozen string literals, pattern matching, Data/Struct, RBS/Sorbet/Steep typing), security (SQL injection via ActiveRecord/Sequel, ERB/XSS escaping, mass assignme
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updatescriptSkillDatabases & data
Create and maintain database update scripts for tine applications. Use when creating, modifying, or understanding Setup/Update PHP files that migrate database schema and application data between versions.
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wp-redis-object-cacheSkillDatabases & data
Configure, audit, troubleshoot, and extend the Redis Object Cache plugin (`redis-cache`) for WordPress persistent object caching. Covers the `wp-content/object-cache.php` drop-in, `wp redis status|enable|disable|update-dropin`, `WP_REDIS_*` constants, Predis/PhpRedis/Relay client selection, cache gr
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wrdsSkillDatabases & data
Connect to and query WRDS (Wharton Research Data Services) from any research project. Use this skill whenever the user needs to download, query, or explore data from WRDS — including Compustat, CRSP, FactSet, I/B/E/S, or any other WRDS-hosted database. Also trigger when the user mentions WRDS tables
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agentfemSkillDatabases & data
Build, review, run, validate, migrate, or extend AgentFEM finite-element projects. Use for AgentFEM studies, meshes, materials, constraints, loads, solution steps, results, campaigns, scientific datasets, surrogate/PINN/neural-operator integration, verification, public API extensions, and agent or G
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building-iceberg-tablesSkillDatabases & data
Design and operate Apache Iceberg tables — partitioning and hidden partitioning, partition/schema evolution, snapshots and time travel, compaction and small-file cleanup, and MERGE/upsert for lakehouse tables on Spark, Flink, Trino, or Snowflake. Use when creating or maintaining Iceberg tables, choo
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building-ingestion-pipelinesSkillDatabases & data
Build batch and incremental data ingestion (extract-load) pipelines — full vs incremental extraction, change data capture (CDC), watermarks and high-water marks, API pagination and rate limits, and choosing managed EL tools (Fivetran, Airbyte) vs custom code. Use when ingesting data from databases,
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cc-context-budgetingSkillDatabases & data
Manage Claude Code's context window — token arithmetic, /compact strategy, anchor preservation, progressive loading, session analytics. Use this skill whenever a session gets long, context approaches limits, after /compact, when deciding what to load into CLAUDE.md vs leave in references, or when an
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cloudbaseSkillDatabases & data
Use when building, deploying, or debugging Tencent CloudBase (腾讯云开发 / TCB) apps in Trae — Web, WeChat Mini Program, cloud functions, CloudRun, auth, NoSQL/PostgreSQL, storage, and built-in AI. Prefer CloudBase MCP tools first, then load published CloudBase skills for scenario details.
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code-review-edho-ferdianSkillDatabases & data
Senior-engineer code review across five domains — Code Quality, Security, Performance, Blueprint/Spec Consistency, and Test Quality — plus conditional lenses auto-detected from scope (database, accessibility, RAG, ML, healthcare, agent/LLM — see Phase 0 below for the full list). Produces an evidence
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cross-referenceSkillDatabases & data
Cross-reference ENCODE data with PubMed, bioRxiv, ClinicalTrials.gov, Open Targets, GTEx, ClinVar, GWAS Catalog, gnomAD, Ensembl, and other scientific databases. Use when the user wants to find publications, preprints, or clinical trials related to ENCODE experiments, chain ENCODE data with other sc
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data-contextSkillDatabases & data
This skill should be used when the user asks to 'set up data analysis for our database', 'extract tribal knowledge about dataset', 'generate data skill', 'document this dataset', 'what does this column mean', 'create data dictionary', 'help me understand this data schema', 'capture domain knowledge
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data-layer-patterns-edho-ferdianSkillDatabases & data
Design and setup guidance for the data layer — Postgres schema design, Prisma ORM patterns, Redis caching/queue patterns, and cross-ORM migration strategy (expand-contract). A design-time companion to code-review-edho-ferdian's database-lens (which reviews existing SQL/ schema/migrations) — use this
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data-provenanceSkillDatabases & data
Track exact provenance for every operation on ENCODE data — tool versions, reference files, scripts, parameters, and timestamps — to enable publication-ready methods writing. Use when the user processes ENCODE files, runs any bioinformatics tool, creates filtered/merged datasets, runs pipelines, per
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