Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add frankxai/claude-code-oracle-skills --skill oracle-adkgit clone --depth 1 https://github.com/frankxai/claude-code-oracle-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/frankxai/claude-code-oracle-skills/oracle-adk)<a href="https://agentmods.dev/skills/frankxai/claude-code-oracle-skills/oracle-adk"><img src="https://agentmods.dev/badge/skills/frankxai/claude-code-oracle-skills/oracle-adk/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/frankxai/claude-code-oracle-skills/oracle-adk"><img src="https://agentmods.dev/badge/skills/frankxai/claude-code-oracle-skills/oracle-adk.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.02588 |
| Opus 5 | $0.00015 | $0.01294 |
| Sonnet 5 | $0.00006 | $0.00518 |
| Haiku 4.5 | $0.00003 | $0.00259 |
Grade A, and why
Oracle ADK Expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 453 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oracle ADK Expert Skill
When to Use This Skill
Activate this skill when:
- Building AI agents on Oracle Cloud Infrastructure
- Creating multi-agent orchestration systems
- Integrating agents with Oracle Fusion, Autonomous Database, or OCI services
- Need code-first (not no-code) agent development
- Deploying enterprise-grade agents with OCI security
Use /adk-agent command to scaffold a new agent project.
Don't use when:
- Not on Oracle Cloud (use Claude SDK or OpenAI AgentKit instead)
- Need visual/no-code builder (use Oracle AI Agent Studio instead)
- Want framework-agnostic specs (use
oracle-agent-specskill instead)
Purpose
Master Oracle's Agent Development Kit (ADK) for building enterprise-grade agentic applications on OCI Generative AI Agents Service with code-first approach and advanced orchestration patterns.
Platform Overview
OCI Agent Development Kit (Released May 22, 2025)
Client-side library that simplifies building agentic applications on top of OCI Generative AI Agents Service.
Key Value: Code-first approach for embedding agents in applications (web apps, Slackbots, enterprise systems).
Requirements: Python 3.10 or later
Core Capabilities
1. Multi-Turn Conversations
Build agents that maintain context across multiple interactions.
Pattern:
from oci_adk import Agent
agent = Agent(
name="customer_support",
model="cohere.command-r-plus",
system_prompt="You are a helpful customer support agent"
)
# Multi-turn conversation
conversation = agent.create_conversation()
response1 = conversation.send("I need help with my order")
response2 = conversation.send("It's order #12345")
# Agent remembers context from previous messages
2. Multi-Agent Orchestration
Routing Pattern:
# Route requests to specialized agents
def orchestrator(user_query):
if requires_technical_support(user_query):
return technical_agent.handle(user_query)
elif requires_billing(user_query):
return billing_agent.handle(user_query)
else:
return general_agent.handle(user_query)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 453 lines · 29 tokens per session scan A 286bae622ce2
Oracle ADK Expert is a skill published in the GitHub repository frankxai/claude-code-oracle-skills (2 stars, last pushed 14d ago), licensed Apache-2.0. It adds 29 tokens to every session and 2,588 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
flow-nexus-swarm
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform.
agent-framework-py-release
Use when cutting a Python release for the microsoft/agent-framework monorepo. Triggers on "bump py versions", "cut a python release", "prepare release PR for python", "release py packages", "bump python to X.Y.Z", or similar requests to bump Python package versions and prepare a release PR. Handles all four lifecycle…
crewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies…
python-package-management
Guide for managing packages in the Agent Framework Python monorepo, including creating new connector packages, versioning, and the lazy-loading pattern. Use this when adding, modifying, or releasing packages.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
verify-samples-tool
How to use the verify-samples tool to run, verify, and manage sample definitions in the Agent Framework repository. Use this when adding, updating, or running sample verification.