Vibe-Trading is a personal trading agent that gives an AI system tools for market analysis, algorithmic trading, backtesting, and related workflows. It is for users who want an agent to research and evaluate trading strategies or manage simulated and other trading activities. The catalogue contains skills that expose these trading capabilities to compatible agents.
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.
npx skills add HKUDS/Vibe-Trading --skill social-media-intelligencegit clone --depth 1 https://github.com/HKUDS/Vibe-TradingWrote 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/skills/hkuds/vibe-trading/social-media-intelligence)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/social-media-intelligence"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/social-media-intelligence/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/skills/hkuds/vibe-trading/social-media-intelligence"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/social-media-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 1253 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00028 | $0.10163 |
| Opus 5 | $0.00014 | $0.05081 |
| Sonnet 5 | $0.00006 | $0.02033 |
| Haiku 4.5 | $0.00003 | $0.01016 |
Grade A, and why
social-media-intelligence 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- social-media-intelligence — 100% identical, 28 lines differ
How it starts
The opening of the file, as written. The whole thing — 1,306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Media Intelligence
This skill integrates financial-intelligence collection methods and quantitative applications across Twitter/X, Telegram, Discord, and Reddit. Inspired by
himself65/finance-skillsmodules such asdiscord-reader,telegram-reader, andtwitter-reader.
1. Overview of the Four Major Financial Social Platforms
1.1 Twitter/X — The FinTwit Ecosystem
Core roles
| Role Type | Representative Account Traits | Signal Value |
|---|---|---|
| Sell-side analyst | Institutional backing, dense posting around earnings | Medium, somewhat lagging |
| Fund manager | Holdings views, industry judgment | High, but mixed with subjective opinion |
| Macro commentator | Fed interpretation, macro-data reaction | High, a good sentiment barometer |
| Crypto KOL | On-chain interpretation, project endorsement | Highly volatile, high manipulation risk |
| Retail noise | Meme spread, herd sentiment | Contrarian signal value at extremes |
Core FinTwit circles
$TICKERcashtag system directly maps discussion to the asset- Earnings-season sentiment patterns before and after reports
- Real-time reaction speed to policy / macro events, often 15-60 minutes ahead of traditional media
1.2 Telegram — The Core Venue for Crypto Intelligence
Channel types
| Channel Type | Content Traits | How to Use |
|---|---|---|
| Signal channels | Specific buy/sell levels, stop-loss / take-profit | Use as a sentiment thermometer, not for blind copy-trading |
| Research push channels | Institutional PDF reports, on-chain data | Aggregate information and extract key numbers |
| Macro flash channels | Real-time interpretation of FOMC, CPI, etc. | Event-driven signals |
| Official project channels | Tokenomics updates, partnership announcements | Potential alpha, but requires filtering |
| Whale alert channels | Large on-chain transfer alerts | Capital-flow signal |
1.3 Discord — Quant Communities and Project Ecosystems
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.
- 2d ago Changed · +10 lines 0a6f4d9f48a0
- 8d ago First seen · 1,296 lines · 28 tokens per session scan A ef47bebc4872
social-media-intelligence is a skill published in the GitHub repository HKUDS/Vibe-Trading (33,177 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 10,163 once invoked, about $0.0001 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 2026-09-03.
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