oracle-work-mode
claudeOracle consulting work mode with confidentiality protocols, daily capture, and research workflows
3 commands · 3 agents
Deep technical implementations: Vector Search, Select AI, NVIDIA NIM
Plugin oracle-ai-architect from marketplace oracle-ai-architect-skills in oci-ai-architects/claude-code-oci-ai-architect-skills. Commands read from the repo's manifest — 3 days ago.
Oracle AI ArchitectExtended reference material for Oracle AI architecture with deep technical implementations
/oracle-ai-architect:vector-searchGenerate Oracle Database 23ai Vector Search implementation
Oracle consulting work mode with confidentiality protocols, daily capture, and research workflows
3 commands · 3 agents
Multi-agent coordination patterns for enterprise AI on Oracle Cloud
1 skill · 1 command
Expert guidance on OCI services, architecture patterns, and cost optimization
1 skill · 1 command
Build production agentic applications on OCI using Oracle Agent Development Kit
1 skill · 1 command
Design framework-agnostic AI agents using Oracle's Open Agent Specification
1 skill · 1 command
Generate professional OCI architecture diagrams with Oracle styling
1 skill · 1 command
AI-powered codebase understanding — analyze, visualize, and explain any project
9 skills · 10 agents · hooks
Open-source AI job search that runs locally in your AI coding CLI: scan job portals, evaluate listings into a structured A-H report with a 1-5 score, tailor your CV, track applications
5 skills · hooks
Rewrite AI-sounding text so it reads like the writer without changing what it says.
1 skill
AI memory system — mine projects and conversations into a searchable palace. 47 MCP tools, auto-save hooks, guided setup.
3 skills · 6 commands · 1 MCP server · hooks
Perform AI code review on Git diffs — supports workspace changes, branch ranges, and single commits with concurrent per-file analysis, codebase search, and deep context-aware review.
2 commands
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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