openorder

openorder is a skill for Claude Code, Codex from realnaka/alphaloop. It costs 195 tokens per session (4,605 once invoked), scanned A, original, MIT.

An AI-maintained wiki for investment research, organised around stocks, companies, industries and themes.

In plain words
What is it for?
Use it to collect, combine and update information about investments, earnings and industry themes in a persistent research record.
Why use it?
It keeps research from being scattered across separate conversations and helps preserve earlier findings for later work.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/realnaka/alphaloop/openorder
Any agent
npx skills add realnaka/alphaloop --skill openorder
Clone the repo
git clone --depth 1 https://github.com/realnaka/alphaloop

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for openorder

README.md
[![agentmods](https://agentmods.dev/badge/skills/realnaka/alphaloop/openorder.svg)](https://agentmods.dev/skills/realnaka/alphaloop/openorder)
Your own site
<a href="https://agentmods.dev/skills/realnaka/alphaloop/openorder"><img src="https://agentmods.dev/badge/skills/realnaka/alphaloop/openorder.svg" alt="Measured on agentmods" height="20"></a>
Per session 195 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,605 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00195 $0.04605
Opus 5 $0.00097 $0.02302
Sonnet 5 $0.00039 $0.00921
Haiku 4.5 $0.00019 $0.00460

Measured 5d ago against content hash 65e418320253, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

openorder 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 5d 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.

skills/openorder/SKILL.md · 428 lines

How it starts

The opening of the file, as written. The whole thing — 428 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OpenOrder — Investment Research Wiki Skill

Order out of investment chaos. An open AI-maintained research wiki that compounds your edge across every conversation.

1. Core Mission

OpenOrder turns scattered investment research into a persistent, compounding wiki maintained by your AI agent.

Following the Karpathy LLM Wiki pattern:

  • The agent is the maintainer; you are the prompter + source curator
  • Knowledge is compiled once, kept fresh — not re-derived on every query
  • The wiki is a persistent, compounding artifact — every conversation makes it smarter

Every conversation that touches a ticker / industry / earnings / framework MUST execute:

READ → REASON → WRITE → LOG → (periodically) LINT
 ↓        ↓        ↓       ↓             ↓
look up  combine  archive  timeline    health-check
existing real-time new       append-only contradictions,
data     + history insights  record       gaps, staleness

2. Three-Layer Architecture

${OPENORDER_HOME}/
│
├── raw/                        ← Layer 1: Raw Sources (immutable, read-only)
│   ├── earnings/                  Earnings transcripts / 8-K filings
│   ├── articles/                  Articles, tweets, blog posts
│   ├── filings/                   SEC 10-K/10-Q PDFs
│   ├── research-notes/            Raw research notes from conversations
│   └── README.md
│
├── [Wiki Layer]                 ← Layer 2: Wiki (LLM-owned, continuously maintained)
│   ├── INDEX.md                   📌 Content index (always read first)
│   ├── log.md                     📌 Activity log (append-only timeline)
│   ├── README.md
│   ├── companies/{TICKER}.md      Company profiles
│   ├── industries/{NAME}/         Industry deep-dives
│   ├── frameworks/{NAME}.md       Investment frameworks
│   ├── earnings/{TICKER}-{Q}.md   Earnings deep-dives
│   ├── portfolios/{NAME}.md       Portfolio configurations
│   └── templates/                 Templates for new entries
│
└── [Schema Layer]               ← Layer 3: Schema (this file)
    ~/.claude/skills/openorder/SKILL.md (or equivalent for other agents)

Read the full file on GitHub · 428 lines

Changes

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.

  1. 5d ago First seen · 428 lines · 195 tokens per session scan A 65e418320253

Subscribe to this mod's changes

openorder is a skill published in the GitHub repository realnaka/alphaloop (19 stars, last pushed 2mo ago), licensed MIT. It adds 195 tokens to every session and 4,605 once invoked, about $0.0010 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 2026-08-30.

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