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vf-stock-agent AGENTS.md

vf-stock-agent AGENTS.md is an instructions file for Codex, OpenCode from dducsw/vf-stock-agent. It costs 1,579 tokens per session, scanned A, original, MIT.

Project instructions for VF Stock Agent, a Python monorepo for investment analysis and learning tools focused on Vietnam's stock market. A monorepo keeps several related packages in one repository.

In plain words
What is it for?
Use them when working on the shared data layer, FastMCP server, AI workflows, command-line interface, deployment files, or tests in VF Stock Agent.
Why use it?
They give a coding agent the project's structure, package responsibilities, development conventions, and onboarding context before it changes code.

Instructions file for CodexOpenCode

not rated 0 26d ago A scan 1,579 tokens original MIT
View the source file dducsw/vf-stock-agent
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/dducsw/vf-stock-agent/agents-md
Clone the repo
git clone --depth 1 https://github.com/dducsw/vf-stock-agent

Made for: Codex, OpenCode.

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README.md
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Per session 1,579 This file is loaded in full into every session.
When invoked 1,579 The same file — it is already loaded in full.
Security scan A 1 finding. 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 $0.01579 $0.01579
Opus 5 $0.00790 $0.00790
Sonnet 5 $0.00316 $0.00316
Haiku 4.5 $0.00158 $0.00158

Measured 4d ago against content hash 6aac901adfc7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

vf-stock-agent AGENTS.md scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- **Failure Handling:** If Python is missing or outdated, STOP. Instruct the user on how to install it natively. Do not blindly `curl` or `wget` installers.
AGENTS.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

VF Stock Agent — AI Context & Project Guidelines

Welcome to VF Stock Agent, a modern monorepo platform designed for AI-driven investment analysis, FastMCP tools, and learning workflows for the Vietnam Stock Market.

Architecture & Monorepo Structure (uv workspace)

The project is structured as a Python monorepo using uv:

vf-stock-agent/
├── pyproject.toml              # Root uv workspace configuration
├── docker-compose.yml          # FastMCP SSE service deployment
├── Dockerfile                  # Production container image
├── packages/
│   ├── vf-stock-core/          # Shared Data Access Layer & 144+ TA Engine
│   ├── vf-stock-mcp/           # FastMCP Server (35+ tools for Claude / Cursor / Cline)
│   ├── vf-stock-agent/         # AI Decision Tools & LangGraph Workflows
│   └── vf-stock-cli/           # Command-Line Interface (`vf-stock`)
└── tests/                      # Pytest suite

Component Responsibilities

  1. vf-stock-core (vf_stock_core):

    • Wraps vnstock library for historical quote data, company overview, financial ratios, balance sheets, income statements, listing symbols, and trading board data.
    • Built-in 144+ Technical Analysis (TA) Engine (vf_stock_core.ta) built on top of pandas-ta.
    • Built-in TTL Caching for high-frequency financial ratio & metadata calls.

  2. vf-stock-mcp (vf_stock_mcp):

    • FastMCP Server mounting domain tools: quote_mcp, company_mcp, finance_mcp, listing_mcp, trading_mcp, global_mcp, fund_mcp, ta_mcp, and agent_mcp.
    • Supports stdio, sse, and streamable-http transports.
    • Includes optional API Key authentication for HTTP/SSE deployment.

  3. vf-stock-agent (vf_stock_agent):

    • Intelligent tools: explain_indicator, compare_stocks, analyze_financials, screen_stocks.
    • LangGraph Workflows: Multi-step parallel research execution graphs (fetch_quote, fetch_financials, calculate_ta -> synthesize_report).
    • LLM integration supporting Groq (GROQ_API_KEY), OpenAI, Anthropic, and Gemini.

Read the full file on GitHub · 114 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 · 114 lines · 1,579 tokens per session scan A 6aac901adfc7

Subscribe to this mod's changes

vf-stock-agent AGENTS.md is an instructions file published in the GitHub repository dducsw/vf-stock-agent (0 stars, last pushed 26d ago), licensed MIT. It adds 1,579 tokens to every session, about $0.0079 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Finance and fintechLanguagesPython
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