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-agent-specgit 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-agent-spec)<a href="https://agentmods.dev/skills/frankxai/claude-code-oracle-skills/oracle-agent-spec"><img src="https://agentmods.dev/badge/skills/frankxai/claude-code-oracle-skills/oracle-agent-spec/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-agent-spec"><img src="https://agentmods.dev/badge/skills/frankxai/claude-code-oracle-skills/oracle-agent-spec.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 | $0.00031 | $0.02800 |
| Opus 5.5 | $0.00012 | $0.01120 |
| Sonnet 5.5 | $0.00006 | $0.00560 |
| Haiku 4.5 | $0.00003 | $0.00280 |
Grade A, and why
Oracle Agent Spec 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 1mo 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.
This is a copy
88% identical to oracle-agent-spec — 945 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 488 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Oracle Agent Spec Expert Skill
Purpose
Master Oracle's Open Agent Specification (Agent Spec) to design framework-agnostic, declarative AI agents that can be authored once and deployed across multiple frameworks and runtimes.
What is Agent Spec?
Open Agent Specification
Framework-agnostic declarative language for defining agentic systems, building blocks for standalone agents and structured workflows, plus composition patterns for multi-agent systems.
Key Innovation: Decouple design from execution - write agents once, run anywhere.
Release: Technical report published October 2025 (arXiv:2510.04173)
Core Philosophy
The Problem: Fragmented agent development - each framework requires different implementation.
The Solution: Unified representation - Agent Spec defines structure and behavior in JSON/YAML that any compatible runtime can execute.
Benefit: Author agents once → Deploy across frameworks → Reduce redundant development.
Architecture
Component Model
Agent Spec defines conceptual building blocks (components) that make up agent-based systems.
Key Property: All components are trivially serializable to JSON/YAML.
Core Components
1. LLMNode
Purpose: Text generation via LLM
Definition:
type: LLMNode
name: "text_generator"
model: "claude-sonnet-4-5"
system_prompt: "You are a helpful assistant"
temperature: 0.7
max_tokens: 2000
2. APINode
Purpose: External API calls
Definition:
type: APINode
name: "weather_api"
endpoint: "https://api.weather.com/v1/current"
method: "GET"
parameters:
location: "{input.location}"
headers:
Authorization: "Bearer {env.API_KEY}"
3. AgentNode
Purpose: Multi-round conversational agent
Definition:
type: AgentNode
name: "support_agent"
model: "gpt-4"
system_prompt: "You are a customer support specialist"
tools:
- type: function
name: "lookup_order"
- type: function
name: "process_refund"
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.
- 1mo ago First seen · 488 lines · 31 tokens per session scan A a241e6679a23
Oracle Agent Spec Expert is a skill published in the GitHub repository frankxai/claude-code-oracle-skills (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 31 tokens to every session and 2,800 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to oracle-agent-spec, differing in 945 lines, and is treated as a copy.
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