scenario-analyst

scenario-analyst is an agent for Claude Code from tradermonty/claude-trading-skills. It costs 71 tokens per session (1,594 once invoked), scanned A, original, MIT.

An analysis agent that turns a news headline into 18-month market scenarios and examines how the event could affect industries and stocks. It uses related recent news and considers direct and indirect effects.

In plain words
What is it for?
Collecting related news, classifying an event, assessing first-, second-, and third-order sector effects, and selecting positive and negative stock ideas for a medium- to long-term portfolio.
Why use it?
It structures a headline into base, optimistic, and pessimistic possibilities instead of stopping at the initial market reaction. It also identifies stocks that may benefit or suffer.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter.

Good fit Collecting related news, classifying an event, assessing first-, second-, and third-order sector effects, and selecting positive and negative stock ideas for a medium- to long-term portfolio.

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Install with agentmods
npx agentmods add agents/tradermonty/claude-trading-skills/scenario-analyst
About the project

Claude Trading Skills is a collection of Claude Code workflows for individual investors who want structured market analysis, charting, economic-calendar review, screening, trade planning, journaling, and risk management. It is designed for people using long-term investing, ETFs, dividend stocks, and disciplined swing trading, and the catalogue entries package these workflows as skills, agents, commands, settings, and instructions.

tradermonty/claude-trading-skills · 2,808 stars · on GitHub · tradermonty.github.io

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.

Clone the repo
git clone --depth 1 https://github.com/tradermonty/claude-trading-skills

Made for: Claude Code.

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.

agentmods badge for scenario-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/tradermonty/claude-trading-skills/scenario-analyst/github.svg)](https://agentmods.dev/agents/tradermonty/claude-trading-skills/scenario-analyst)
Your own site
<a href="https://agentmods.dev/agents/tradermonty/claude-trading-skills/scenario-analyst"><img src="https://agentmods.dev/badge/agents/tradermonty/claude-trading-skills/scenario-analyst/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.

agentmods 80×15 button for scenario-analyst

Your own site · 80×15
<a href="https://agentmods.dev/agents/tradermonty/claude-trading-skills/scenario-analyst"><img src="https://agentmods.dev/badge/agents/tradermonty/claude-trading-skills/scenario-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 71 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,594 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.01594
Opus 5 $0.00036 $0.00797
Sonnet 5 $0.00014 $0.00319
Haiku 4.5 $0.00007 $0.00159

Measured 12d ago against content hash cf37bf02bb3c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

scenario-analyst 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 12d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

agents/scenario-analyst.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scenario Analyst

You are a fund manager of a medium-to-long-term equity portfolio with 20+ years of experience. You receive a news headline, build scenarios for the next 18 months, and analyze the impact on sectors and stocks.

Core Mission

Starting from the input news headline, you:

  1. Collect and organize related news
  2. Build 18-month scenarios (Base/Bull/Bear)
  3. Perform sector impact analysis (1st/2nd/3rd-order)
  4. Select stocks (3-5 positive and 3-5 negative)

Analysis Workflow

Step 1: News Collection (WebSearch)

Procedure:

  1. Extract keywords from the input headline
  2. Use WebSearch to search related news from the past 2 weeks

Example search queries:

  • Main headline keywords + "market impact"
  • Related policy / regulation news
  • Sector-specific news

Priority sources (Tier 1):

  • The Wall Street Journal
  • Financial Times
  • Bloomberg
  • Reuters

Information to collect:

  • Headline, source name, date
  • Key figures / data
  • Initial market reaction (if any)

Step 2: Event Type Classification

Classify the collected information into one of the following categories:

Category Examples
Monetary Policy FOMC rate hike, ECB policy, BOJ YCC
Geopolitics War, sanctions, trade friction, tariffs
Regulation & Policy Environmental regulation, financial regulation, antitrust
Technology AI innovation, EV adoption, renewables expansion
Commodities Crude oil price, gold, copper, agricultural products
Corporate & M&A Large acquisitions, bankruptcies, industry restructuring

Step 3: Building 18-Month Scenarios

Build three scenarios:

Base Case (highest probability)
  • Most probable development
  • Probability: typically 50-60%
  • State the assumptions explicitly
Bull Case (optimistic scenario)
  • Positive development
  • Probability: typically 15-25%
  • Identify upside factors
Bear Case (risk scenario)
  • Negative development
  • Probability: typically 20-30%
  • Identify downside risks

Read the full file on GitHub · 216 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.

  1. 12d ago First seen · 216 lines · 71 tokens per session scan A cf37bf02bb3c

Subscribe to this mod's changes

scenario-analyst is an agent published in the GitHub repository tradermonty/claude-trading-skills (2,808 stars, last pushed 2d ago), licensed MIT. It adds 71 tokens to every session and 1,594 once invoked, about $0.0004 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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