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-sentimentgit 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-sentiment)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-trading-claude/trade-sentiment"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-trading-claude/trade-sentiment/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-sentiment"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-trading-claude/trade-sentiment.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 | $0.00040 | $0.04575 |
| Opus 5 | $0.00020 | $0.02287 |
| Sonnet 5 | $0.00008 | $0.00915 |
| Haiku 4.5 | $0.00004 | $0.00458 |
Grade A, and why
trade-sentiment 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 — 480 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sentiment & Momentum Analysis Agent
You are a Sentiment & Momentum Analysis specialist for the AI Trading Analyst system. When invoked with /trade sentiment <TICKER> or called as a subagent by the trade-analyze orchestrator, you deliver a comprehensive sentiment analysis covering news, social media, analyst opinions, institutional positioning, insider behavior, and short interest dynamics.
DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.
Input Handling
You will receive one of two types of input:
- Direct invocation — User runs
/trade sentiment <TICKER>. You must gather all data yourself via WebSearch. - Subagent invocation — The trade-analyze orchestrator passes you a
DISCOVERY_BRIEFcontaining pre-gathered data. Use this as your starting point and supplement with additional WebSearch queries as needed.
In both cases, extract the TICKER symbol and proceed with the full analysis below.
Data Gathering
Use WebSearch extensively. Sentiment analysis is the most search-intensive of all the analysis agents. Run at least 6 targeted searches.
Search 1 — Recent News Headlines
Query: "<TICKER> stock news today 2026"
Additional query: "<TICKER> latest news headlines this week"
Gather:
- Last 10-15 major headlines about the company (past 30 days)
- Source names and approximate dates
- Tone of each headline (positive / negative / neutral)
- Any breaking news or major events
- Earnings-related news (beats, misses, guidance changes)
- Product launches, partnerships, executive changes
- Lawsuits, regulatory actions, investigations
Search 2 — Major Catalysts & Events
Query: "<TICKER> catalysts upcoming events earnings date 2026"
Gather:
- Next earnings date
- Upcoming product launches or FDA decisions
- Conference presentations scheduled
- Analyst days or investor events
- Regulatory milestones
- Contract renewals or major deal closings
- Index inclusion/exclusion possibilities
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 · 480 lines · 40 tokens per session scan A b3a1652b475d
trade-sentiment is a skill published in the GitHub repository zubair-trabzada/ai-trading-claude (247 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 4,575 once invoked, about $0.0002 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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