| Skill that analyzes 18-month scenarios from a news headline. Runs the primary analysis with the scenario-analyst agent and obtains a second opinion with the strategy-reviewer agent. Generates a comprehensive English report covering 1st/2nd/3rd-order impacts, recommended stocks, and a critical review. medium-to-long-term investment strategy
npx skills add https://github.com/BaggaT236/AI-Trading-Skills --skill scenario-analyzer
This skill analyzes medium-to-long-term (18-month) investment scenarios
starting from a news headline. It invokes two specialized agents in sequence
(scenario-analyst and strategy-reviewer) and integrates multi-angle
analysis with a critical review into a comprehensive report.
Use this skill when:
Examples:
/scenario-analyzer "Fed raises interest rates by 50bp, signals more hikes ahead"
/scenario-analyzer "China announces new tariffs on US semiconductors"
/scenario-analyzer "OPEC+ agrees to cut oil production by 2 million barrels per day"
┌─────────────────────────────────────────────────────────────────────┐
│ Skill (orchestrator) │
│ │
│ Phase 1: Preparation │
│ ├─ Headline parsing │
│ ├─ Event type classification │
│ └─ Reference loading │
│ │
│ Phase 2: Agent invocation │
│ ├─ scenario-analyst (primary analysis) │
│ └─ strategy-reviewer (second opinion) │
│ │
│ Phase 3: Integration & report generation │
│ └─ reports/scenario_analysis_<topic>_YYYYMMDD.md │
└─────────────────────────────────────────────────────────────────────┘
Parse the headline provided by the user.
Classify the headline into one of the following categories:
| Category | Examples |
|----------|----------|
| Monetary Policy | FOMC, ECB, BOJ, rate hike, rate cut, QE/QT |
| Geopolitics | War, sanctions, tariffs, trade friction |
| Regulation & Policy | Environmental regulation, financial regulation, antitrust |
| Technology | AI, EV, renewables, semiconductors |
| Commodities | Crude oil, gold, copper, agricultural products |
| Corporate & M&A | Acquisitions, bankruptcies, earnings, industry restructuring |
Based on the event type, load the relevant references:
Read references/headline_event_patterns.md
Read references/sector_sensitivity_matrix.md
Read references/scenario_playbooks.md
Reference contents:
headline_event_patterns.md: Historical event patterns and market reactionssector_sensitivity_matrix.md: Event × sector impact-magnitude matrixscenario_playbooks.md: Scenario-construction templates and best practicesUse the Agent tool to invoke the primary analysis agent.
Agent tool:
- subagent_type: "scenario-analyst"
- prompt: |
Perform an 18-month scenario analysis for the following headline.
## Target Headline
[the input headline]
## Event Type
[classification result]
## Reference Information
[summary of the loaded references]
## Analysis Requirements
1. Use WebSearch to collect related news from the past 2 weeks
2. Construct 3 scenarios — Base/Bull/Bear (probabilities sum to 100%)
3. Analyze 1st/2nd/3rd-order impacts by sector
4. Select 3-5 positive- and 3-5 negative-impact stocks (US market only)
5. Output everything in English
Expected output:
Using the scenario-analyst's results, invoke the review agent.
Agent tool:
- subagent_type: "strategy-reviewer"
- prompt: |
Review the following scenario analysis.
## Target Headline
[the input headline]
## Analysis Result
[the full scenario-analyst output]
## Review Requirements
Review from the following angles:
1. Overlooked sectors/stocks
2. Validity of the scenario probability allocation
3. Logical consistency of the impact analysis
4. Detection of optimism/pessimism bias
5. Proposal of alternative scenarios
6. Realism of the timeline
Output constructive and specific feedback in English.
Expected output:
Integrate the output of both agents to produce the final investment judgment.
Integration points:
Generate the final report in the following format and save it to a file.
Save location: reports/scenario_analysis_<topic>_YYYYMMDD.md
# Headline Scenario Analysis Report
**Analyzed at**: YYYY-MM-DD HH:MM
**Target headline**: [the input headline]
**Event type**: [classification category]
---
## 1. Related News Articles
[news list collected by scenario-analyst]
## 2. Scenario Overview (through 18 months out)
### Base Case (XX% probability)
[scenario details]
### Bull Case (XX% probability)
[scenario details]
### Bear Case (XX% probability)
[scenario details]
## 3. Sector / Industry Impact
### 1st-Order Impact (direct)
[impact table]
### 2nd-Order Impact (value chain / related industries)
[impact table]
### 3rd-Order Impact (macro / regulation / technology)
[impact table]
## 4. Stocks Expected to Benefit (3-5 tickers)
[stock table]
## 5. Stocks Expected to Be Hurt (3-5 tickers)
[stock table]
## 6. Second Opinion / Review
[strategy-reviewer output]
## 7. Final Investment Judgment & Implications
### Recommended Actions
[concrete actions informed by the review]
### Risk Factors
[list of key risks]
### Monitoring Points
[indicators / events to follow]
---
**Generated by**: scenario-analyzer skill
**Agents**: scenario-analyst, strategy-reviewer
reports/ directory if it does not existscenario_analysis_<topic>_YYYYMMDD.md (e.g., scenario_analysis_venezuela_20260104.md)This skill generates the following file:
| File | Format | Description |
|------|--------|-------------|
| reports/scenario_analysis_<topic>_YYYYMMDD.md | Markdown | Comprehensive scenario analysis report |
Output contents:
references/headline_event_patterns.md - Event patterns and market reactionsreferences/sector_sensitivity_matrix.md - Sector sensitivity matrixreferences/scenario_playbooks.md - Scenario-construction templatesscenario-analyst - Primary scenario analysisstrategy-reviewer - Second opinion / reviewreports/ directoryreports/scenario_analysis_<topic>_YYYYMMDD.mdreports/scenario_analysis_fed_rate_hike_20260104.mdreports/ directory if it does not existConfirm the following before finalizing the report:
Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations or working with already-completed data packs.
Give the AI agent its own EVM wallet with admin-controlled policies the agent CANNOT bypass even under prompt injection. Encrypted keystore (AES-256-GCM, scrypt KDF), policy file the agent has no tool to write, deterministic policy gate on every signing operation, optional local HTTP dashboard. Triggers: agent wallet, give the agent a wallet, agent address, fund the agent, agent autonomy, policy gate, kill switch, agent permissions, bounded autonomy, ERC-4337 alternative, session-key alternative.
BNB Chain MCP server connection and tool usage. Covers npx @bnb-chain/mcp@latest, PRIVATE_KEY and RPC, and every MCP tool — blocks, transactions, contracts, ERC20/NFT transfers, wallet, ERC-8004 agent registration, Greenfield. Use when connecting to bnbchain-mcp, querying or transacting on BNB Chain/opBNB/EVM, registering as ERC-8004 agent, or using Greenfield.
Entry point for Internet Court — the trust layer for agent-to-agent commerce. Use whenever an agent needs to transact with another agent or a paid service, or a user mentions agent payments, paid APIs (HTTP 402/x402), wallet custody or trust concerns, spending mandates, delegated permissions (ERC-7710/7715), escrow, agent identity or reputation (ERC-8004), negotiation between agents (A2A), agent jobs (ERC-8183), machine payments (MPP, AP2), supervision of agent behavior, revocation, verification, or dispute resolution (GenLayer) — even if they never say "Internet Court". Routes to the vendored protocol skills and connector skills in this package.
Upload files to IPFS through the Kleros x402 payment gateway in exchange for $0.01 USDC on Base mainnet. Use this skill **specifically** when the user is uploading content destined for the Kleros ecosystem — dispute evidence, meta-evidence JSON, court / dispute / arbitrator policies, Curate item metadata, juror justifications, or any artifact a Kleros smart contract or subgraph will reference by IPFS CID. Trigger when the request mentions Kleros, a court / arbitrator / dispute / juror / curate / proof-of-humanity context, or any of the conventional Kleros operation tags (evidence, meta-evidence, justification). Do NOT trigger for generic 'upload to IPFS' / 'get me a CID' requests with no Kleros context — point those users at Pinata, web3.storage, or any general-purpose pinning service instead. Exception: if the user explicitly names this gateway (kleros-ipfs-gateway.fly.dev / kleros-api.netlify.app/.netlify/functions/upload-to-ipfs), explicitly requests this skill, or asks the agent to test / validate / sanity-check this gateway or skill, trigger regardless of topical context — a deliberate end-to-end test is a valid trigger.
Use when an agent hits HTTP 402 / payment-required, or the user mentions x402, x402Version, X-PAYMENT, PAYMENT-REQUIRED, PAYMENT-SIGNATURE, WWW-Authenticate: Payment, permit2, upto, metered billing, a payment channel / voucher / session, channelId / channel_id, opening / closing / topping up / settling / refunding a channel, a paymentId or a2a_ link, creating / checking a payment link, A2MCP / an A2MCP endpoint, or sending a request to / calling an Agent's endpoint with a concrete endpoint URL. Covers x402 (exact, exact+Permit2, upto, aggr_deferred), MPP (charge / session), and a2a-pay paymentId flows. Any close / topup / settle / voucher / refund near a channel_id or session is an MPP mid-session op. The full bilingual trigger list (including Chinese) lives in the skill body.
Onchain OS onboarding & guide hub — the single entry for first-time, 'what is this / how do I use it', OKX.AI, and customer-support intents; classifies the intent and routes to the right sub-flow via its Intent Routing table. Covers: (1) Onchain OS onboarding + welcome banner — 'what is onchainos', 'what is onchain os', 'what can it do', 'what can onchainos do', 'what does onchainos do', 'how do I use this', 'how do I play', 'how to use onchainos', 'how to play onchainos', 'how does onchainos work', 'how do I start', 'getting started', 'tutorial', 'onboarding', 'first time', 'I just installed', 'now what', 'what do I do now', 'where do I start', 'who are you', 'what are you', 'introduce onchainos', 'tell me about onchainos', 'I'm new'; (2) OKX.AI intro & role-registration routing (the Agent economic system — roles User / ASP / Evaluator) — 'what is OKX.AI', 'OKX.AI 是什么', 'how to use OKX.AI', 'OKX.AI 快速开始', and any spelling / spacing / casing / typo variant (OKXAI, okx ai, okx-ai, lowercase okx.ai, 啥是okxai); (3) customer support / Help Center — 'contact support', 'talk to a human', 'customer service', 'file a complaint', 'give feedback', 'report a bug / system error', 'help center', 'FAQ', 'user guide', 'something is broken'. NOT for: direct on-chain actions (swap / wallet / balance / token) or Agent task lifecycle (publish / accept / deliver / dispute) — those have their own skills.
Create and manage Starknet wallets for AI agents. Transfer tokens, check balances, manage session keys, deploy accounts, and interact with smart contracts using native Account Abstraction.
Take baggat236/scenario-analyzer from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.