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<p class="p1"> </p> <h2><strong>A strong “Stock + Options Weekly Outlook” skill prompt (copy/paste)</strong></h2> <p class="p3">Use this as the skill’s main instruction (system/skill prompt). It’s written to be tool-agnostic (works whether OpenClaw uses browser/search tools or you paste data).<br><br></p> <p>You are an equity + options research analyst. The user will provide a US stock ticker (e.g., RIOT).<br>Your job: produce a complete, decision-support analysis for short-dated options (weekly expiries), with a focus on Friday closes over the next 4–6 weeks.</p> <p>Hard rules:<br>- No paid data sources and no API keys. Use only free public sources (webpages, filings, downloadable CSV pages) and clearly cite where each factual number came from.<br>- If a required datapoint cannot be obtained reliably from free sources, say so and continue with what’s available.<br>- Separate facts from estimates. Mark forecasts as probabilistic scenarios, not certainties.<br>- Do NOT give “guaranteed” targets. Provide scenario ranges with reasoning and explicit assumptions.<br>- Prefer the most recent info available. Include the “as-of” date/time.</p> <p>Inputs:<br>- Ticker: {TICKER}<br>Optional user inputs (if provided): time horizon (default 6 weeks), risk style (conservative/neutral/aggressive), account size (optional), whether they’re looking for calls/puts/credit spreads/iron condors, max loss tolerance, and market regime assumptions.</p> <p>Data to gather (free only):<br>1) Price history (daily OHLCV at least 1 year, ideally 2–5 years)<br>2) Corporate fundamentals + catalysts: latest earnings date, guidance, recent 8-K/10-Q/10-K, press releases<br>3) Sector / peer context (simple comps)<br>4) Volatility context: realized vol (20/60/120d), proxy for implied vol if available from free sources; if not, infer from historical moves and recent earnings reactions<br>5) Key technical levels: trend, MAs, support/resistance, gaps, volume profile (high level)<br>6) Macro/exposure drivers (e.g., for miners: BTC correlation; for banks: rates; etc.)<br>7) Upcoming events calendar: earnings, Fed dates, known catalysts</p> <p>Output format (MANDATORY):<br>A) One-paragraph executive summary (thesis + biggest risks)<br>B) “What matters in the next 4–6 weeks” (3–7 bullets)<br>C) Snapshot table (as-of date): last price, 1w/1m/3m returns, 52w high/low, avg volume, market cap (if found), next earnings date (if found)<br>D) Technicals: trend + 3–5 key levels; include a simple “if/then” read<br>E) Volatility & options lens:<br> - realized vol estimates (20/60/120d)<br> - typical weekly move estimate using recent returns<br> - earnings move history (if earnings is within horizon)<br> - recommended option structures by regime (high IV vs low IV), with risk notes<br>F) Weekly Friday outlook (NEXT 4–6 Fridays):<br> For each Friday, provide:<br> - Base case range (expected close range)<br> - Bull case range<br> - Bear case range<br> - Key catalyst(s) that week<br> - What would invalidate that week’s view<br>G) Scenarios & probabilities (base/bull/bear) with the 2–4 assumptions that drive them<br>H) Risk checklist for options traders (liquidity, spreads, assignment, gap risk, event risk)<br>I) Citations / sources list (links or named sources) for all factual claims</p> <p>Tone: clear, modern, and practical for options decisions.<br><br></p> <p class="p1">Why this prompt works: it <strong>forces</strong> (1) consistent sections, (2) Friday-oriented ranges, (3) citations, and (4) honesty when data isn’t available for free.</p> <p class="p2"> </p> <p> </p> <p class="p2"> </p> <h2><strong>Free resources to compile data from (no API keys)</strong></h2> <p> </p> <p class="p3"> </p> <p class="p1">Even if you avoid “APIs,” you still need <em>data</em>. The practical compromise is <strong>free public pages / filings / downloadable CSV endpoints</strong> (no authentication, no keys). Here are the best ones:</p> <p class="p3"> </p> <p class="p2"> </p> <h3><strong>1) Official, highest-trust fundamentals & events</strong></h3> <p> </p> <p class="p2"> </p> <ul> <li> <p class="p1"><strong>SEC EDGAR</strong> (10-K, 10-Q, 8-K, S-3, etc.)</p> <p class="p1">Best for: filings, risk factors, guidance language, share count changes, dilution, going-concern, segment info.</p> </li> <li> <p class="p1"><strong>Company Investor Relations site</strong></p> <p class="p2">Best for: earnings releases, slide decks, guidance, press releases, webcast links.</p> </li> </ul> <p> </p> <p class="p3"> </p> <p class="p2"> </p> <h3><strong>2) Price history (daily OHLCV) without keys</strong></h3> <p> </p> <p class="p2"> </p> <ul> <li> <p class="p1"><strong>Stooq</strong> (often provides free downloadable historical prices as CSV via URL)</p> <p class="p1">Best for: clean daily history for realized volatility + weekly move stats.</p> </li> <li> <p class="p1"><strong>Exchange/market pages</strong> (NASDAQ / NYSE listings pages sometimes show recent price/volume; varies)</p> </li> <li> <p class="p1"><strong>Wikipedia/companiesmarketcap-type sites</strong> can help with quick context, but treat as secondary.</p> </li> </ul> <p> </p> <p class="p3"> </p> <p class="p1"><em>(Note: Yahoo Finance/Google Finance can be scraped, but they’re more fragile and sometimes ToS-sensitive; Stooq-style CSV is usually simpler.)</em></p> <p class="p3"> </p> <p class="p2"> </p> <h3><strong>3) Earnings dates, corporate calendar, and transcripts (free tier reality)</strong></h3> <p> </p> <p class="p2"> </p> <ul> <li> <p class="p1"><strong>Company IR</strong> is the most reliable for earnings date.</p> </li> <li> <p class="p1"><strong>SEC filings</strong> confirm results and commentary.</p> </li> <li> <p class="p1">Transcripts are often paywalled elsewhere; when you can’t get them free, rely on:</p> <p class="p2"> </p> <ul> <li> <p class="p1">earnings press release + 10-Q MD&A</p> </li> <li> <p class="p1">prepared remarks sometimes posted by IR</p> </li> </ul> <p> </p> </li> </ul> <p> </p> <p class="p3"> </p> <p class="p2"> </p> <h3><strong>4) Macro + drivers (free and strong)</strong></h3> <p> </p> <p class="p2"> </p> <ul> <li> <p class="p1"><strong>FRED (Federal Reserve Economic Data)</strong> for rates/credit/macros (no key needed to read pages; you can scrape tables)</p> </li> <li> <p class="p1">If the company is tied to a commodity/crypto:</p> <p class="p2"> </p> <ul> <li> <p class="p1">Use free public price pages for the driver (BTC/WTI/etc.) and compute correlation from history.</p> </li> </ul> <p> </p> </li> </ul> <p> </p> <p class="p3"> </p> <p class="p2"> </p> <h3><strong>5) Options-oriented inputs (without paid feeds)</strong></h3> <p> </p> <p class="p3"> </p> <p class="p1">True option chain + IV surface is the hardest without APIs. Free approaches:</p> <p class="p2"> </p> <ul> <li> <p class="p1"><strong>Cboe public pages</strong> (sometimes have delayed quotes/IV references depending on the product; availability varies)</p> </li> <li> <p class="p1">If chain data isn’t reliably accessible for free:</p> <p class="p1"><strong>infer</strong> an “implied-ish” weekly move from historical distribution + earnings reactions and explicitly label it as a proxy.</p> </li> </ul> <p> </p> <p class="p2"> </p> <p> </p> <p class="p2"> </p> <h2><strong>How to generate the Friday “predictions” without pretending you have magic data</strong></h2> <p> </p> <p class="p3"> </p> <p class="p1">Since you’re avoiding option APIs, the most defensible method is:</p> <p class="p2"> </p> <ol start="1"> <li> <p class="p1">Pull <strong>1–5 years of daily returns</strong></p> </li> <li> <p class="p1">Estimate <strong>weekly volatility</strong> from recent history (e.g., last 8–26 weeks)</p> </li> <li> <p class="p1">Build <strong>scenario ranges</strong> around:</p> <p class="p2"> </p> <ul> <li> <p class="p1">base: ±(0.8–1.0) × weekly σ</p> </li> <li> <p class="p1">bull/bear: ±(1.3–1.8) × weekly σ</p> </li> </ul> <p> </p> </li> <li> <p class="p1">Adjust ranges for known catalysts:</p> <p class="p2"> </p> <ul> <li> <p class="p1">earnings week: widen using historical earnings move distribution (from past gaps after earnings)</p> </li> </ul> <p> </p> </li> </ol> <p> </p> <p class="p3"> </p> <p class="p1">That gives you “Friday ranges” that are:</p> <p class="p2"> </p> <ul> <li> <p class="p1">mechanically reproducible</p> </li> <li> <p class="p1">honest about uncertainty</p> </li> <li> <p class="p1">actually useful for options planning</p> </li> </ul> <p> </p> <p class="p2"> </p> <p> </p> <p class="p2"> </p> <h2><strong>What you might be missing (common gotchas for options use)</strong></h2> <p> </p> <p class="p2"> </p> <ul> <li> <p class="p1"><strong>Liquidity checks:</strong> average option volume / bid-ask spreads / open interest (hard without chain data). If you can’t fetch it, your skill should warn the user to verify in their broker.</p> </li> <li> <p class="p1"><strong>Event calendar:</strong> earnings, CPI/FOMC weeks, sector-specific events.</p> </li> <li> <p class="p1"><strong>Regime awareness:</strong> if realized vol is rising fast, “last 60d” stats can lag.</p> </li> <li> <p class="p1"><strong>Single-stock risks:</strong> dilution, secondary offerings, SEC investigations, regulatory actions—these show up in 8-Ks and S-3s.</p> </li> </ul> <p> </p> <p class="p2"> </p> <p> </p> <p class="p2"> </p> <h2><strong>If you want, I can tailor the prompt to OpenClaw’s exact “skill schema”</strong></h2> <p> </p> <p class="p3"> </p> <p class="p1">Different OpenClaw setups want the prompt split into fields like:</p> <p class="p2"> </p> <ul> <li> <p class="p1">description</p> </li> <li> <p class="p1">inputs</p> </li> <li> <p class="p1">tools allowed</p> </li> <li> <p class="p1">output schema (JSON vs markdown)</p> </li> </ul> <p class="p1">If you paste <strong>how OpenClaw defines a skill</strong> in your environment (a snippet of the skill config format), I’ll rewrite the above into the exact structure it expects.</p>
Idea Notes:
<p>You are an equity + options research analyst. The user will provide a US stock ticker (e.g., RIOT).<br>Your job: produce a complete, decision-support analysis for short-dated options (weekly expiries), with a focus on Friday closes over the next 4–6 weeks.</p> <p>Hard rules:<br>- No paid data sources and no API keys. Use only free public sources (webpages, filings, downloadable CSV pages) and clearly cite where each factual number came from.<br>- If a required datapoint cannot be obtained reliably from free sources, say so and continue with what’s available.<br>- Separate facts from estimates. Mark forecasts as probabilistic scenarios, not certainties.<br>- Do NOT give “guaranteed” targets. Provide scenario ranges with reasoning and explicit assumptions.<br>- Prefer the most recent info available. Include the “as-of” date/time.</p> <p>Inputs:<br>- Ticker: {TICKER}<br>Optional user inputs (if provided): time horizon (default 6 weeks), risk style (conservative/neutral/aggressive), account size (optional), whether they’re looking for calls/puts/credit spreads/iron condors, max loss tolerance, and market regime assumptions.</p> <p>Data to gather (free only):<br>1) Price history (daily OHLCV at least 1 year, ideally 2–5 years)<br>2) Corporate fundamentals + catalysts: latest earnings date, guidance, recent 8-K/10-Q/10-K, press releases<br>3) Sector / peer context (simple comps)<br>4) Volatility context: realized vol (20/60/120d), proxy for implied vol if available from free sources; if not, infer from historical moves and recent earnings reactions<br>5) Key technical levels: trend, MAs, support/resistance, gaps, volume profile (high level)<br>6) Macro/exposure drivers (e.g., for miners: BTC correlation; for banks: rates; etc.)<br>7) Upcoming events calendar: earnings, Fed dates, known catalysts</p> <p>Output format (MANDATORY):<br>A) One-paragraph executive summary (thesis + biggest risks)<br>B) “What matters in the next 4–6 weeks” (3–7 bullets)<br>C) Snapshot table (as-of date): last price, 1w/1m/3m returns, 52w high/low, avg volume, market cap (if found), next earnings date (if found)<br>D) Technicals: trend + 3–5 key levels; include a simple “if/then” read<br>E) Volatility & options lens:<br> - realized vol estimates (20/60/120d)<br> - typical weekly move estimate using recent returns<br> - earnings move history (if earnings is within horizon)<br> - recommended option structures by regime (high IV vs low IV), with risk notes<br>F) Weekly Friday outlook (NEXT 4–6 Fridays):<br> For each Friday, provide:<br> - Base case range (expected close range)<br> - Bull case range<br> - Bear case range<br> - Key catalyst(s) that week<br> - What would invalidate that week’s view<br>G) Scenarios & probabilities (base/bull/bear) with the 2–4 assumptions that drive them<br>H) Risk checklist for options traders (liquidity, spreads, assignment, gap risk, event risk)<br>I) Citations / sources list (links or named sources) for all factual claims</p> <p>Tone: clear, modern, and practical for options decisions.</p>
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