Codex Brain
codexLocal-first persistent memory plugin for Codex: a vault with transaction-reviewed writes, source/claim provenance ledgers, and onboarding/assistant skills that propose content instead of writing on their own.
11 skills · hooks
Data engineering workflows for dimensional modeling, data warehouse design, data quality, ETL, ELT, and analytical architecture.
Plugin data-engineering in guipmourao/agents. Commands read from the repo's manifest — 1 month ago.
data-modelingAnalyzes schemas, data dictionaries, DDLs, queries, and sample data to design auditable dimensional models using Kimball principles. Use when defining fact tables, dimensions, grain, SCD strategies, bus matrices, ETL/ELT rules, or validation controls for analytical data platforms.
Local-first persistent memory plugin for Codex: a vault with transaction-reviewed writes, source/claim provenance ledgers, and onboarding/assistant skills that propose content instead of writing on their own.
11 skills · hooks
Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data
9 skills · 9 commands · 11 agents · 1 MCP server
Automates browser interactions for web testing, form filling, screenshots, and data extraction
12 skills
Install the "AAS Data Analytics & Business Intelligence" workflow plugin from Agentic Awesome Skills.
16 skills
Databricks skills for the CLI, Apps, Lakebase, Model Serving, Lakeflow Jobs, Spark Declarative Pipelines, Declarative Automation Bundles (DABs), and classic-to-serverless migration.
37 skills · 2 commands · hooks
The official CCXT MCP server plus the ccxt-mcp usage skill — market data, balances and opt-in trading across 100+ crypto exchanges and prediction markets, with keys kept local.
1 MCP server
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
10 skills · 2 commands · 3 agents
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