What is trade-sentiment?

A stock sentiment and momentum analysis workflow that examines news, social media discussion, analyst opinions, institutional activity, insider trading, and short interest. Momentum describes the direction and strength of recent price movement.

Use it to research a publicly traded company by its ticker symbol and produce a sentiment analysis with a score from 0 to 100.

It gathers several kinds of market opinion and activity in one analysis instead of requiring separate research for each source.

trade-sentiment — Skill for Claude Code and Codex by zubair-trabzada

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.

Any agent

npx skills add zubair-trabzada/ai-trading-claude --skill trade-sentiment

Clone the repo

git clone --depth 1 https://github.com/zubair-trabzada/ai-trading-claude

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/zubair-trabzada/ai-trading-claude/trade-sentiment/github.svg)](https://agentmods.dev/skills/zubair-trabzada/ai-trading-claude/trade-sentiment)

Your own site

<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.

Your own site · 80×15

<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>

Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,575 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00040	$0.04575
Opus 5.5	$0.00016	$0.01830
Sonnet 5.5	$0.00008	$0.00915
Haiku 4.5	$0.00004	$0.00458

Measured 2mo ago against content hash b3a1652b475d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

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.

skills/trade-sentiment/SKILL.md · 480 lines

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_BRIEF containing 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

Read the full file on GitHub · 480 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.

2mo ago First seen · 480 lines · 40 tokens per session scan A b3a1652b475d

Subscribe to this mod's changes

trade-sentiment is a skill published in the GitHub repository zubair-trabzada/ai-trading-claude (319 stars, last pushed 7mo ago), licensed MIT. It adds 40 tokens to every session and 4,575 once invoked, about $0.0002 per session on Opus 5.5. 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.

trade-sentiment next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
trade-sentimentzubair-trabzada/ai-trading-claude	Skill	319	7mo ago	MIT	A	40	Claude Code, Codex
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	today	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	today	MIT	A	103	Claude Code