app-trading-engine AGENTS.md

app-trading-engine AGENTS.md is an instructions file for Codex, OpenCode from jsohi/app-trading-engine. It costs 3,887 tokens per session, scanned A, original, Apache-2.0.

A set of instructions for using coding agents to build a trading engine from a planned list of 66 work items. It assigns separate agents to implement changes, review pull requests, and run tests in isolated Git worktrees, which are separate working copies of the code.

In plain words
What is it for?
Use it to plan implementation waves, assign coding and review roles, run verification, and coordinate work on the trading engine.
Why use it?
It provides a defined way to divide a large greenfield project—one with no existing implementation—among agents while checking the work before merging it.

Instructions file for CodexOpenCode

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 instructions/jsohi/app-trading-engine/agents-md
Clone the repo
git clone --depth 1 https://github.com/jsohi/app-trading-engine

Made for: Codex, OpenCode.

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README.md
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Per session 3,887 This file is loaded in full into every session.
When invoked 3,887 The same file — it is already loaded in full.
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 $0.03887 $0.03887
Opus 5 $0.01944 $0.01944
Sonnet 5 $0.00777 $0.00777
Haiku 4.5 $0.00389 $0.00389

Measured 4d ago against content hash 8b0f443999e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

app-trading-engine AGENTS.md 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 4d 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.

AGENTS.md · 342 lines

How it starts

The opening of the file, as written. The whole thing — 342 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Multi-Agent Implementation Plan — Trading Engine

Context

Plan the sequence, agent roles, and verification strategy for implementing 66 Linear issues (APP-5 through APP-70, non-contiguous) using AI coding agents. The project is greenfield (no code exists). The goal is to maximize parallelism, ensure quality via review/test agents, and deliver a working trading engine end-to-end.

Note: See docs/wave-plan.md for the authoritative wave-by-wave issue list (13 waves, 66 issues). This file focuses on agent roles, prompts, and operational protocol.


Agent Roles

1. Implementer Agent

  • Writes code for a single issue
  • Runs in an isolated worktree (git branch per issue)
  • Has full context: issue description, CLAUDE.md, dependency code from merged branches
  • Creates a PR when done

2. Reviewer Agent

  • Reviews PRs created by Implementer agents
  • Checks: correctness, patterns consistency, CLAUDE.md conventions, security, performance
  • Posts review comments or approves
  • Flags: allocation in hot path, non-deterministic code in cluster, floating-point instead of fixed-point

3. Test Agent

  • Runs after Implementer completes, before PR merge
  • Executes: ./gradlew build, ./gradlew test, type-checks
  • For integration test issues: spins up the full stack and runs the test suite
  • Reports pass/fail with logs

4. Orchestrator (You / Human)

  • Manages the wave sequence below
  • Merges approved PRs in dependency order
  • Triggers next wave when current wave's PRs are merged
  • Resolves conflicts between parallel branches

Implementation Waves

Wave 1 — Foundation (1 issue, serial)

Must complete first. Everything depends on this.

Issue Title Agent Config
APP-5 Scaffold Gradle multi-module project Implementer → Reviewer → Test (./gradlew projects && ./gradlew build)

Verification: ./gradlew projects shows all 14 subprojects, ./gradlew build succeeds, CLAUDE.md exists.

Read the full file on GitHub · 342 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. 4d ago First seen · 342 lines · 3,887 tokens per session scan A 8b0f443999e1

Subscribe to this mod's changes

app-trading-engine AGENTS.md is an instructions file published in the GitHub repository jsohi/app-trading-engine (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 3,887 tokens to every session, about $0.0194 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.

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