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 yyordanov-tradu/stock-scanner-mcp --skill sector-rotationgit clone --depth 1 https://github.com/yyordanov-tradu/stock-scanner-mcpWrote 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/yyordanov-tradu/stock-scanner-mcp/sector-rotation)<a href="https://agentmods.dev/skills/yyordanov-tradu/stock-scanner-mcp/sector-rotation"><img src="https://agentmods.dev/badge/skills/yyordanov-tradu/stock-scanner-mcp/sector-rotation/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/yyordanov-tradu/stock-scanner-mcp/sector-rotation"><img src="https://agentmods.dev/badge/skills/yyordanov-tradu/stock-scanner-mcp/sector-rotation.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 | $0.00031 | $0.01202 |
| Opus 5 | $0.00015 | $0.00601 |
| Sonnet 5 | $0.00006 | $0.00240 |
| Haiku 4.5 | $0.00003 | $0.00120 |
Grade A, and why
sector-rotation 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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sector Rotation
Overview
Act as a sector strategist. Collect sector performance data across multiple timeframes, overlay market breadth and technical signals on leaders and laggards, and determine whether capital is rotating toward risk-on or risk-off sectors. Produce actionable sector allocation guidance.
Announce at start: "Running sector rotation analysis -- collecting sector performance, breadth, market indices, and technical signals."
Data Collection
Wave 1 -- ALL calls in parallel
| Tool | Parameters | Priority |
|---|---|---|
tradingview_sector_performance |
(default) | REQUIRED |
tradingview_market_indices |
(default) | REQUIRED |
market_breadth |
universe=major_us | ENRICHMENT |
sentiment_fear_greed |
(default) | ENRICHMENT |
fred_indicator |
series_id=treasury_10y | ENRICHMENT |
Wave 2 -- After Wave 1 completes
Rank sectors by 1-week performance for rotation analysis. Identify the top 3 and bottom 3 sectors by this ranking. Call technicals for their ETFs.
| Tool | Parameters | Priority |
|---|---|---|
tradingview_technicals |
tickers=[top 3 + bottom 3 sector ETFs] | REQUIRED |
Standard sector ETF mapping: XLK (Technology), XLF (Financials), XLV (Health Care), XLY (Consumer Discretionary), XLP (Consumer Staples), XLE (Energy), XLI (Industrials), XLRE (Real Estate), XLU (Utilities), XLB (Materials), XLC (Communication Services).
DO NOT proceed to analysis until ALL REQUIRED calls return. ENRICHMENT failures are acceptable.
Analysis
Cross-reference the collected data across four dimensions:
- Timeframe Divergence -- Compare 1-day vs 1-week vs 1-month vs YTD performance for each sector. Short-term moves diverging from longer-term trends signal emerging rotation.
- Risk Appetite -- Defensive sectors (XLU, XLP, XLV) outperforming cyclicals (XLY, XLI, XLF) = RISK-OFF. Cyclicals outperforming defensives = RISK-ON. Mixed leadership = no clear signal. Use breadth as confirmation: strong breadth confirms broad risk-on rotation; weak breadth implies narrow leadership.
- Rate Sensitivity -- Compare rate-sensitive sectors (XLU, XLRE) performance to 10Y yield direction. Rising yields should pressure these sectors. Outperformance despite rising yields is a strong signal.
- Technical Confirmation -- Use RSI and trend data from Wave 2 to confirm or contradict the rotation signal. Overbought leaders (RSI >70) may reverse. Oversold laggards (RSI <30) may bounce.
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.
- 12d ago First seen · 98 lines · 31 tokens per session scan A 75c54bbe6ad1
sector-rotation is a skill published in the GitHub repository yyordanov-tradu/stock-scanner-mcp (6 stars, last pushed 2d ago), licensed MIT. It adds 31 tokens to every session and 1,202 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 2026-08-31.
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