Borrowing it
Nothing to install: this file belongs to dducsw/vf-stock-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dducsw/vf-stock-agent/main/AGENTS.mdgit clone --depth 1 https://github.com/dducsw/vf-stock-agentWrote 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/instructions/dducsw/vf-stock-agent/agents-md)<a href="https://agentmods.dev/instructions/dducsw/vf-stock-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/dducsw/vf-stock-agent/agents-md/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/instructions/dducsw/vf-stock-agent/agents-md"><img src="https://agentmods.dev/badge/instructions/dducsw/vf-stock-agent/agents-md.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 | $0.01579 | $0.01579 |
| Opus 5.5 | $0.00632 | $0.00632 |
| Sonnet 5.5 | $0.00316 | $0.00316 |
| Haiku 4.5 | $0.00158 | $0.00158 |
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 2mo 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- **Failure Handling:** If Python is missing or outdated, STOP.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. 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
-
vf-stock-core(vf_stock_core):- Wraps
vnstocklibrary 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 ofpandas-ta. - Built-in TTL Caching for high-frequency financial ratio & metadata calls.
- Wraps
-
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, andagent_mcp. - Supports
stdio,sse, andstreamable-httptransports. - Includes optional API Key authentication for HTTP/SSE deployment.
- FastMCP Server mounting domain tools:
-
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.
- Intelligent tools:
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.
- 2mo ago First seen · 114 lines · 1,579 tokens per session scan A 6aac901adfc7
vf-stock-agent AGENTS.md is an instructions file published in the GitHub repository dducsw/vf-stock-agent (0 stars, last pushed 2mo ago), licensed MIT. It adds 1,579 tokens to every session, about $0.0063 per session on Opus 5.5. 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.
vf-stock-agent AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| vf-stock-agent AGENTS.mddducsw/vf-stock-agent | Instructions file | 0 | 2mo ago | MIT | A | 1,579 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |