quant-strategies: Skill for Codex

.agents/skills/manage-joinquant-strategy/SKILL.md

manage-joinquant-strategy is a skill for Codex from chess99/quant-strategies. It costs 61 tokens per session (645 once invoked), scanned A, original, no licence file.

A workflow for managing JoinQuant quantitative trading strategies in a repository. JoinQuant is a platform for writing and backtesting investment strategies in Python.

In plain words
What is it for?
It is for creating, modifying, testing, organising, archiving, importing backtest results for, and reviewing JoinQuant-compatible Python strategies.
Why use it?
It keeps related strategy versions and their supporting results organised while allowing changes and tests to follow repository rules.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents).

This is chess99/quant-strategies's own configuration. It tells Codex how to work on quant-strategies itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything quant-strategies configures →

Reuse

Borrowing it

Nothing to install: this file belongs to chess99/quant-strategies. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/chess99/quant-strategies/main/.agents/skills/manage-joinquant-strategy/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/chess99/quant-strategies

Made for: 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 manage-joinquant-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/chess99/quant-strategies/manage-joinquant-strategy/github.svg)](https://agentmods.dev/skills/chess99/quant-strategies/manage-joinquant-strategy)
Your own site
<a href="https://agentmods.dev/skills/chess99/quant-strategies/manage-joinquant-strategy"><img src="https://agentmods.dev/badge/skills/chess99/quant-strategies/manage-joinquant-strategy/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.

agentmods 80×15 button for manage-joinquant-strategy

Your own site · 80×15
<a href="https://agentmods.dev/skills/chess99/quant-strategies/manage-joinquant-strategy"><img src="https://agentmods.dev/badge/skills/chess99/quant-strategies/manage-joinquant-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 645 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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 5.1 $0.00061 $0.00645
Opus 5 $0.00030 $0.00322
Sonnet 5 $0.00012 $0.00129
Haiku 4.5 $0.00006 $0.00064

Measured 11d ago against content hash bdd22deeb0d0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

manage-joinquant-strategy 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.

.agents/skills/manage-joinquant-strategy/SKILL.md · 59 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 11d ago First seen · 59 lines · 61 tokens per session scan A bdd22deeb0d0

Subscribe to this mod's changes

manage-joinquant-strategy is a skill published in the GitHub repository chess99/quant-strategies (6 stars, last pushed 7d ago), with no licence file. It adds 61 tokens to every session and 645 once invoked, about $0.0003 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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