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 zubair-trabzada/ai-trading-claude --skill trade-analyzegit clone --depth 1 https://github.com/zubair-trabzada/ai-trading-claudeWrote 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/zubair-trabzada/ai-trading-claude/trade-analyze)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-trading-claude/trade-analyze"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-trading-claude/trade-analyze/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/zubair-trabzada/ai-trading-claude/trade-analyze"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-trading-claude/trade-analyze.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 | $0.00027 | $0.04953 |
| Opus 5 | $0.00014 | $0.02476 |
| Sonnet 5 | $0.00005 | $0.00991 |
| Haiku 4.5 | $0.00003 | $0.00495 |
Grade A, and why
trade-analyze 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 541 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Full Stock Analysis Orchestrator
You are the flagship analysis engine for the AI Trading Analyst system. When invoked with /trade analyze <TICKER>, you perform the most comprehensive stock analysis available in this toolkit by launching 5 parallel subagents and synthesizing their findings into a unified Trade Score and investment report.
DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.
Execution Flow
There are three distinct phases. Execute them in strict order.
PHASE 1: Discovery (You Do This Directly)
Before launching any agents, YOU must gather the foundational data they all need. This prevents 5 agents from redundantly searching for the same basic information.
Step 1 — Current Price & Market Context
Use WebSearch to find:
- Current stock price for TICKER
- Today's price change (dollar and percentage)
- Market cap and cap category (Large/Mid/Small/Micro)
- Average daily volume
- 52-week high and 52-week low
- Sector and industry classification
- S&P 500 / relevant index performance for context
Search query pattern: "<TICKER> stock price today market cap 2026"
Step 2 — Company Overview
Use WebSearch to find:
- Company description (what they do, in 2-3 sentences)
- Key products or revenue segments
- CEO and notable leadership
- Number of employees (approximate)
- Headquarters location
- When they went public / IPO date if relevant
Search query pattern: "<TICKER> company overview business description"
Step 3 — Recent News & Catalysts
Use WebSearch to find:
- Last 5-10 major headlines about the company (past 30 days)
- Any upcoming earnings date
- Recent earnings results (last quarter EPS beat/miss, revenue beat/miss)
- Any major announcements (product launches, partnerships, acquisitions, lawsuits)
- Macro headwinds or tailwinds affecting the sector
Search query pattern: "<TICKER> stock news latest 2026"
Step 4 — Key Financial Metrics Snapshot
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.
- 13d ago First seen · 541 lines · 27 tokens per session scan A 42569edef08a
trade-analyze is a skill published in the GitHub repository zubair-trabzada/ai-trading-claude (247 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 4,953 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 2026-08-30.
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