{ "schemaVersion": "1.0", "item": { "slug": "earnings-calendar", "name": "Earnings Calendar", "source": "tencent", "type": "skill", "category": "效率提升", "sourceUrl": "https://clawhub.ai/Veeramanikandanr48/earnings-calendar", "canonicalUrl": "https://clawhub.ai/Veeramanikandanr48/earnings-calendar", "targetPlatform": "OpenClaw" }, "install": { "downloadMode": "redirect", "downloadUrl": "/downloads/earnings-calendar", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=earnings-calendar", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "installMethod": "Manual import", "extraction": "Extract archive", "prerequisites": [ "OpenClaw" ], "packageFormat": "ZIP package", "includedAssets": [ "SKILL.md", "assets/earnings_report_template.md", "earnings_calendar_2025-11-02.md", "references/fmp_api_guide.md", "scripts/fetch_earnings_fmp.py", "scripts/generate_report.py" ], "primaryDoc": "SKILL.md", "quickSetup": [ "Download the package from Yavira.", "Extract the archive and review SKILL.md first.", "Import or place the package into your OpenClaw setup." ], "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "Download the package from Yavira.", "Extract it into a folder your agent can access.", "Paste one of the prompts below and point your agent at the extracted folder." ], "prompts": [ { "label": "New install", "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete." }, { "label": "Upgrade existing", "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run." } ] }, "sourceHealth": { "source": "tencent", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-04-23T16:43:11.935Z", "expiresAt": "2026-04-30T16:43:11.935Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard", "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"", "redirectLocation": null, "bodySnippet": null }, "scope": "source", "summary": "Source download looks usable.", "detail": "Yavira can redirect you to the upstream package for this source.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/earnings-calendar" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] }, "downloadPageUrl": "https://openagent3.xyz/downloads/earnings-calendar", "agentPageUrl": "https://openagent3.xyz/skills/earnings-calendar/agent", "manifestUrl": "https://openagent3.xyz/skills/earnings-calendar/agent.json", "briefUrl": "https://openagent3.xyz/skills/earnings-calendar/agent.md" }, "agentAssist": { "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.", "steps": [ "Download the package from Yavira.", "Extract it into a folder your agent can access.", "Paste one of the prompts below and point your agent at the extracted folder." ], "prompts": [ { "label": "New install", "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete." }, { "label": "Upgrade existing", "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run." } ] }, "documentation": { "source": "clawhub", "primaryDoc": "SKILL.md", "sections": [ { "title": "Overview", "body": "This skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. It focuses on companies with significant market capitalization (mid-cap and above, over $2B) that are likely to impact market movements. The skill generates organized markdown reports showing which companies are reporting earnings over the next week, grouped by date and timing (before market open, after market close, or time not announced).\n\nKey Features:\n\nUses FMP API for reliable, structured earnings data\nFilters by market cap (>$2B) to focus on market-moving companies\nIncludes EPS and revenue estimates\nMulti-environment support (CLI, Desktop, Web)\nFlexible API key management\nOrganized by date, timing, and market cap" }, { "title": "FMP API Key", "body": "This skill requires a Financial Modeling Prep API key.\n\nGet Free API Key:\n\nVisit: https://site.financialmodelingprep.com/developer/docs\nSign up for free account\nReceive API key immediately\nFree tier: 250 API calls/day (sufficient for weekly earnings calendar)\n\nAPI Key Setup by Environment:\n\nClaude Code (CLI):\n\nexport FMP_API_KEY=\"your-api-key-here\"\n\nClaude Desktop:\nSet environment variable in system or configure MCP server.\n\nClaude Web:\nAPI key will be requested during skill execution (stored only for current session)." }, { "title": "Step 1: Get Current Date and Calculate Target Week", "body": "CRITICAL: Always start by obtaining the accurate current date.\n\nRetrieve the current date and time:\n\nUse system date/time to get today's date\nNote: \"Today's date\" is provided in the environment ( tag)\nCalculate the target week: Next 7 days from current date\n\nDate Range Calculation:\n\nCurrent Date: [e.g., November 2, 2025]\nTarget Week Start: [Current Date + 1 day, e.g., November 3, 2025]\nTarget Week End: [Current Date + 7 days, e.g., November 9, 2025]\n\nWhy This Matters:\n\nEarnings calendars are time-sensitive\n\"Next week\" must be calculated from the actual current date\nProvides accurate date range for API request\n\nFormat dates in YYYY-MM-DD for API compatibility." }, { "title": "Step 2: Load FMP API Guide", "body": "Before retrieving data, load the comprehensive FMP API guide:\n\nRead: references/fmp_api_guide.md\n\nThis guide contains:\n\nFMP API endpoint structure and parameters\nAuthentication requirements\nMarket cap filtering strategy (via Company Profile API)\nEarnings timing conventions (BMO, AMC, TAS)\nResponse format and field descriptions\nError handling strategies\nBest practices and optimization tips" }, { "title": "Step 3: API Key Detection and Configuration", "body": "Detect API key availability based on environment.\n\nMulti-Environment API Key Detection:\n\n3.1 Check Environment Variable (CLI/Desktop)\n\nif [ ! -z \"$FMP_API_KEY\" ]; then\n echo \"✓ API key found in environment\"\n API_KEY=$FMP_API_KEY\nfi\n\nIf environment variable is set, proceed to Step 4.\n\n3.2 Prompt User for API Key (Desktop/Web)\n\nIf environment variable not found, use AskUserQuestion tool:\n\nQuestion Configuration:\n\nQuestion: \"This skill requires an FMP API key to retrieve earnings data. Do you have an FMP API key?\"\nHeader: \"API Key\"\nOptions:\n 1. \"Yes, I'll provide it now\" → Proceed to 3.3\n 2. \"No, get free key\" → Show instructions (3.2.1)\n 3. \"Skip API, use manual entry\" → Jump to Step 8 (fallback mode)\n\n3.2.1 If user chooses \"No, get free key\":\n\nProvide instructions:\n\nTo get a free FMP API key:\n\n1. Visit: https://site.financialmodelingprep.com/developer/docs\n2. Click \"Get Free API Key\" or \"Sign Up\"\n3. Create account (email + password)\n4. Receive API key immediately\n5. Free tier includes 250 API calls/day (sufficient for daily use)\n\nOnce you have your API key, please select \"Yes, I'll provide it now\" to continue.\n\n3.3 Request API Key Input\n\nIf user has API key, request input:\n\nPrompt:\n\nPlease paste your FMP API key below:\n\n(Your API key will only be stored for this conversation session and will be forgotten when the session ends. For regular use, consider setting the FMP_API_KEY environment variable.)\n\nStore API key in session variable:\n\nAPI_KEY = [user_input]\n\nConfirm with user:\n\n✓ API key received and stored for this session.\n\nSecurity Note:\n- API key is stored only in current conversation context\n- Not saved to disk or persistent storage\n- Will be forgotten when session ends\n- Do not share this conversation if it contains your API key\n\nProceeding with earnings data retrieval..." }, { "title": "Step 4: Retrieve Earnings Data via FMP API", "body": "Use the Python script to fetch earnings data from FMP API.\n\nScript Location:\n\nscripts/fetch_earnings_fmp.py\n\nExecution:\n\nOption A: With Environment Variable (CLI):\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09\n\nOption B: With Session API Key (Desktop/Web):\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 \"${API_KEY}\"\n\nScript Workflow (automatic):\n\nValidates API key and date parameters\nCalls FMP Earnings Calendar API for date range\nFetches company profiles (market cap, sector, industry)\nFilters companies with market cap >$2B\nNormalizes timing (BMO/AMC/TAS)\nSorts by date → timing → market cap (descending)\nOutputs JSON to stdout\n\nExpected Output Format (JSON):\n\n[\n {\n \"symbol\": \"AAPL\",\n \"companyName\": \"Apple Inc.\",\n \"date\": \"2025-11-04\",\n \"timing\": \"AMC\",\n \"marketCap\": 3000000000000,\n \"marketCapFormatted\": \"$3.0T\",\n \"sector\": \"Technology\",\n \"industry\": \"Consumer Electronics\",\n \"epsEstimated\": 1.54,\n \"revenueEstimated\": 123400000000,\n \"fiscalDateEnding\": \"2025-09-30\",\n \"exchange\": \"NASDAQ\"\n },\n ...\n]\n\nSave to file (recommended for use with report generator):\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 \"${API_KEY}\" > earnings_data.json\n\nOr capture to variable:\n\nearnings_data=$(python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 \"${API_KEY}\")\n\nError Handling:\n\nIf script returns errors:\n\n401 Unauthorized: Invalid API key → Verify key or re-enter\n429 Rate Limit: Exceeded 250 calls/day → Wait or upgrade plan\nEmpty Result: No earnings in date range → Expand date range or note in report\nConnection Error: Network issue → Retry or use cached data if available" }, { "title": "Step 5: Process and Organize Data", "body": "Once earnings data is retrieved (JSON format), process and organize it:\n\n5.1 Parse JSON Data\n\nLoad JSON data from script output:\n\nimport json\nearnings_data = json.loads(earnings_json_string)\n\nOr if saved to file:\n\nwith open('earnings_data.json', 'r') as f:\n earnings_data = json.load(f)\n\n5.2 Verify Data Structure\n\nConfirm data includes required fields:\n\n✓ symbol\n✓ companyName\n✓ date\n✓ timing (BMO/AMC/TAS)\n✓ marketCap\n✓ sector\n\n5.3 Group by Date\n\nGroup all earnings announcements by date:\n\nSunday, [Full Date] (if applicable)\nMonday, [Full Date]\nTuesday, [Full Date]\nWednesday, [Full Date]\nThursday, [Full Date]\nFriday, [Full Date]\nSaturday, [Full Date] (if applicable)\n\n5.4 Sub-Group by Timing\n\nWithin each date, create three sub-sections:\n\nBefore Market Open (BMO)\nAfter Market Close (AMC)\nTime Not Announced (TAS)\n\nData is already sorted by timing from the script, so maintain this order.\n\n5.5 Within Each Timing Group\n\nCompanies are already sorted by market cap descending (script output):\n\nMega-cap (>$200B) first\nLarge-cap ($10B-$200B) second\nMid-cap ($2B-$10B) third\n\nThis prioritization ensures the most market-moving companies are listed first.\n\n5.6 Calculate Summary Statistics\n\nCompute:\n\nTotal Companies: Count of all companies in dataset\nMega/Large Cap Count: Count where marketCap >= $10B\nMid Cap Count: Count where marketCap between $2B and $10B\nPeak Day: Day of week with most earnings announcements\nSector Distribution: Count by sector (Technology, Healthcare, Financial, etc.)\nHighest Market Cap Companies: Top 5 companies by market cap" }, { "title": "Step 6: Generate Markdown Report", "body": "Use the report generation script to create a formatted markdown report from the JSON data.\n\nScript Location:\n\nscripts/generate_report.py\n\nExecution:\n\nOption A: Output to stdout:\n\npython scripts/generate_report.py earnings_data.json\n\nOption B: Save to file:\n\npython scripts/generate_report.py earnings_data.json earnings_calendar_2025-11-02.md\n\nWhat the script does:\n\nLoads earnings data from JSON file\nGroups by date and timing (BMO/AMC/TAS)\nSorts by market cap within each group\nCalculates summary statistics\nGenerates formatted markdown report\nOutputs to stdout or saves to file\n\nThe script automatically handles all formatting including:\n\nProper markdown table structure\nDate grouping and day names\nMarket cap sorting\nEPS and revenue formatting\nSummary statistics calculation\n\nReport Structure:\n\n# Upcoming Earnings Calendar - Week of [START_DATE] to [END_DATE]\n\n**Report Generated**: [Current Date]\n**Data Source**: FMP API (Mid-cap and above, >$2B market cap)\n**Coverage Period**: Next 7 days\n**Total Companies**: [COUNT]\n\n---\n\n## Executive Summary\n\n- **Total Companies Reporting**: [TOTAL_COUNT]\n- **Mega/Large Cap (>$10B)**: [LARGE_CAP_COUNT]\n- **Mid Cap ($2B-$10B)**: [MID_CAP_COUNT]\n- **Peak Day**: [DAY_WITH_MOST_EARNINGS]\n\n---\n\n## [Day Name], [Full Date]\n\n### Before Market Open (BMO)\n\n| Ticker | Company | Market Cap | Sector | EPS Est. | Revenue Est. |\n|--------|---------|------------|--------|----------|--------------|\n| [TICKER] | [COMPANY] | [MCAP] | [SECTOR] | [EPS] | [REV] |\n\n### After Market Close (AMC)\n\n| Ticker | Company | Market Cap | Sector | EPS Est. | Revenue Est. |\n|--------|---------|------------|--------|----------|--------------|\n| [TICKER] | [COMPANY] | [MCAP] | [SECTOR] | [EPS] | [REV] |\n\n### Time Not Announced (TAS)\n\n| Ticker | Company | Market Cap | Sector | EPS Est. | Revenue Est. |\n|--------|---------|------------|--------|----------|--------------|\n| [TICKER] | [COMPANY] | [MCAP] | [SECTOR] | [EPS] | [REV] |\n\n---\n\n[Repeat for each day of week]\n\n---\n\n## Key Observations\n\n### Highest Market Cap Companies This Week\n1. [COMPANY] ([TICKER]) - [MCAP] - [DATE] [TIME]\n2. [COMPANY] ([TICKER]) - [MCAP] - [DATE] [TIME]\n3. [COMPANY] ([TICKER]) - [MCAP] - [DATE] [TIME]\n\n### Sector Distribution\n- **Technology**: [COUNT] companies\n- **Healthcare**: [COUNT] companies\n- **Financial**: [COUNT] companies\n- **Consumer**: [COUNT] companies\n- **Other**: [COUNT] companies\n\n### Trading Considerations\n- **Days with Heavy Volume**: [DATES with multiple large-cap earnings]\n- **Pre-Market Focus**: [BMO companies that may move markets]\n- **After-Hours Focus**: [AMC companies that may move markets]\n\n---\n\n## Timing Reference\n\n- **BMO (Before Market Open)**: Announcements typically around 6:00-8:00 AM ET before market opens at 9:30 AM ET\n- **AMC (After Market Close)**: Announcements typically around 4:00-5:00 PM ET after market closes at 4:00 PM ET\n- **TAS (Time Not Announced)**: Specific time not yet disclosed - monitor company investor relations\n\n---\n\n## Data Notes\n\n- **Market Cap Categories**:\n - Mega Cap: >$200B\n - Large Cap: $10B-$200B\n - Mid Cap: $2B-$10B\n\n- **Filter Criteria**: This report includes companies with market cap $2B and above (mid-cap+) with earnings scheduled for the next week.\n\n- **Data Source**: Financial Modeling Prep (FMP) API\n\n- **Data Freshness**: Earnings dates and times can change. Verify critical dates through company investor relations websites for the most current information.\n\n- **EPS and Revenue Estimates**: Analyst consensus estimates from FMP API. Actual results will be reported on earnings date.\n\n---\n\n## Additional Resources\n\n- **FMP API Documentation**: https://site.financialmodelingprep.com/developer/docs\n- **Seeking Alpha Calendar**: https://seekingalpha.com/earnings/earnings-calendar\n- **Yahoo Finance Calendar**: https://finance.yahoo.com/calendar/earnings\n\n---\n\n*Report generated using FMP Earnings Calendar API with mid-cap+ filter (>$2B market cap). Data current as of report generation time. Always verify earnings dates through official company sources.*\n\nFormatting Best Practices:\n\nUse markdown tables for clean presentation\nBold important company names (mega-cap) if desired\nInclude market cap in human-readable format ($3.0T, $150B, $5.2B) - already formatted by script\nGroup logically by date then timing\nInclude summary section at top for quick overview\nAdd EPS and revenue estimates if available" }, { "title": "Step 7: Quality Assurance", "body": "Before finalizing the report, verify:\n\nData Quality Checks:\n\n✓ All dates fall within the target week (next 7 days)\n✓ Market cap values are present for all companies\n✓ Each company has timing specified (BMO/AMC/TAS)\n✓ Companies are sorted by market cap within each section\n✓ Summary statistics are accurate\n✓ Report generation date is clearly stated\n✓ EPS and revenue estimates included where available\n\nCompleteness Checks:\n\n✓ All days of the target week are included (even if no earnings)\n✓ Major known companies are not missing (verify against external sources if needed)\n✓ Sector information is included where available\n✓ Timing reference section is present\n✓ Data sources are credited (FMP API)\n\nFormat Checks:\n\n✓ Markdown tables are properly formatted\n✓ Dates are consistently formatted\n✓ Market caps use consistent units (B for billions, T for trillions)\n✓ All sections follow template structure\n✓ No placeholder text ([PLACEHOLDER]) remains\n✓ EPS and revenue estimates properly formatted" }, { "title": "Step 8: Save and Deliver Report", "body": "Save the generated report with an appropriate filename:\n\nFilename Convention:\n\nearnings_calendar_[YYYY-MM-DD].md\n\nExample: earnings_calendar_2025-11-02.md\n\nThe filename date represents the report generation date, not the earnings week.\n\nDelivery:\n\nSave the markdown file to the working directory\nInform the user that the report has been generated\nProvide a brief summary of key findings (e.g., \"45 companies reporting next week, with Apple and Microsoft on Monday\")\n\nExample Summary:\n\n✓ Earnings calendar report generated: earnings_calendar_2025-11-02.md\n\nSummary for week of November 3-9, 2025:\n- 45 companies reporting earnings\n- 28 large/mega-cap, 17 mid-cap\n- Peak day: Thursday (15 companies)\n- Notable: Apple (Mon AMC), Microsoft (Tue AMC), Tesla (Wed AMC)\n\nTop 5 by market cap:\n1. Apple - $3.0T (Mon AMC)\n2. Microsoft - $2.8T (Tue AMC)\n3. Alphabet - $1.8T (Thu AMC)\n4. Amazon - $1.6T (Fri AMC)\n5. Tesla - $800B (Wed AMC)" }, { "title": "Fallback Mode (Step 8 Alternative): Manual Data Entry", "body": "If API access is unavailable or user chooses to skip API:\n\nProvide Instructions for Manual Entry:\n\nSince FMP API is not available, you can manually gather earnings data:\n\n1. Visit Finviz: https://finviz.com/screener.ashx?v=111&f=cap_midover%2Cearningsdate_nextweek\n2. Or Yahoo Finance: https://finance.yahoo.com/calendar/earnings\n3. Note down companies reporting next week\n\nPlease provide the following information for each company:\n- Ticker symbol\n- Company name\n- Earnings date\n- Timing (BMO/AMC/TAS)\n- Market cap (approximate)\n- Sector\n\nI will format this into the standard earnings calendar report.\n\nProcess Manual Input:\n\nParse user-provided earnings data\nOrganize by date, timing, and market cap\nGenerate report using same template\nNote in report: \"Data Source: Manual Entry\"" }, { "title": "Use Case 1: Weekly Review (Primary Use Case)", "body": "User Request: \"Get next week's earnings calendar\"\n\nWorkflow:\n\nGet current date (e.g., November 2, 2025)\nCalculate target week (November 3-9, 2025)\nLoad FMP API guide\nDetect/request API key\nFetch earnings data:\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 > earnings_data.json\n\n\nGenerate markdown report:\npython scripts/generate_report.py earnings_data.json earnings_calendar_2025-11-02.md\n\n\nNotify user with summary\n\nComplete One-Liner:\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 > earnings_data.json && \\\npython scripts/generate_report.py earnings_data.json earnings_calendar_2025-11-02.md" }, { "title": "Use Case 2: Focused on Specific Day", "body": "User Request: \"What earnings are coming out Monday?\"\n\nWorkflow:\n\nGet current date and identify next Monday (e.g., November 4, 2025)\nFetch full week data (same as Use Case 1)\nGenerate full report but highlight Monday section\nProvide verbal summary of Monday's earnings with emphasis" }, { "title": "Use Case 3: Mega-Cap Focus", "body": "User Request: \"Show me earnings for companies over $100B market cap next week\"\n\nWorkflow:\n\nFetch full earnings data (script already filters >$2B)\nProcess and organize as normal\nWhen generating report, add a \"Mega-Cap Focus\" section at top\nFilter tables to show only companies >$100B\nNote: Still include full data in appendix for reference" }, { "title": "Use Case 4: Sector-Specific", "body": "User Request: \"What tech companies have earnings next week?\"\n\nWorkflow:\n\nFetch full earnings data\nProcess and organize as normal\nFilter results by sector = \"Technology\"\nGenerate report with focus on technology sector\nNote: Template structure remains the same; content is filtered" }, { "title": "Problem: API key not working", "body": "Solutions:\n\nVerify API key is correct (copy-paste carefully)\nCheck if API key is active (login to FMP dashboard)\nEnsure no extra spaces before/after key\nTry generating new API key from FMP dashboard" }, { "title": "Problem: Script returns empty results", "body": "Solutions:\n\nVerify date range is in future (not past dates)\nCheck date format is YYYY-MM-DD\nTry wider date range (e.g., 14 days instead of 7)\nVerify companies actually have announced earnings dates for that week" }, { "title": "Problem: Missing major companies", "body": "Solutions:\n\nCompany may not have announced earnings date yet\nSome companies announce dates very late (1-2 days before)\nCross-reference with company investor relations website\nMarket cap may have dropped below $2B threshold" }, { "title": "Problem: Rate limit hit (429 error)", "body": "Solutions:\n\nFree tier: 250 calls/day\nEach weekly report uses ~3-5 API calls\nCheck if other tools/scripts are using same API key\nWait 24 hours for rate limit reset\nConsider upgrading to paid tier if needed frequently" }, { "title": "Problem: Script execution error", "body": "Solutions:\n\nVerify Python 3 is installed: python3 --version\nInstall requests library: pip install requests\nCheck script has execute permissions: chmod +x fetch_earnings_fmp.py\nRun with python3 explicitly: python3 fetch_earnings_fmp.py ..." }, { "title": "Do's", "body": "✓ Always get current date first before any data retrieval\n✓ Use FMP API as primary source for reliability\n✓ Store API key in environment variable for CLI usage\n✓ Sort by market cap to prioritize high-impact companies\n✓ Group by date then timing for logical organization\n✓ Include summary statistics for quick overview\n✓ Credit data sources in report footer\n✓ Use clean markdown tables for readability\n✓ Provide timing reference section for clarity\n✓ Note data freshness and potential for changes\n✓ Include EPS and revenue estimates when available" }, { "title": "Don'ts", "body": "✗ Don't assume \"next week\" without calculating from current date\n✗ Don't omit timing information (BMO/AMC/TAS)\n✗ Don't mix date formats within report (stay consistent)\n✗ Don't include micro/small-cap unless specifically requested\n✗ Don't forget to sort by market cap within sections\n✗ Don't share API key in conversations or reports\n✗ Don't include earnings from current week or past dates\n✗ Don't generate report without quality assurance checks\n✗ Don't commit API keys to version control" }, { "title": "API Key Security", "body": "Important Reminders:\n\n✓ Use free tier API keys for testing\n✓ Rotate keys regularly\n✓ Don't share conversations containing API keys\n✓ Set API key as environment variable for CLI\n✓ Keys provided in chat are session-only (forgotten after session ends)\n✗ Never commit API keys to Git repositories\n✗ Never use production API keys with sensitive data access\n\nBest Practice:\nFor Claude Code (CLI), always use environment variable:\n\n# Add to ~/.zshrc or ~/.bashrc\nexport FMP_API_KEY=\"your-key-here\"\n\nFor Claude Web, understand that:\n\nAPI key entered in chat is temporary\nStored only in conversation context\nNot saved to disk\nForgotten when session ends" }, { "title": "Resources", "body": "FMP API:\n\nMain Documentation: https://site.financialmodelingprep.com/developer/docs\nGet API Key: https://site.financialmodelingprep.com/developer/docs\nEarnings Calendar API: https://site.financialmodelingprep.com/developer/docs/earnings-calendar-api\nCompany Profile API: https://site.financialmodelingprep.com/developer/docs/companies-key-metrics-api\nPricing/Rate Limits: https://site.financialmodelingprep.com/developer/docs/pricing\n\nSupplementary Sources (for verification):\n\nSeeking Alpha: https://seekingalpha.com/earnings/earnings-calendar\nYahoo Finance: https://finance.yahoo.com/calendar/earnings\nMarketWatch: https://www.marketwatch.com/tools/earnings-calendar\n\nSkill Resources:\n\nFMP API Guide: references/fmp_api_guide.md\nPython Script: scripts/fetch_earnings_fmp.py\nReport Template: assets/earnings_report_template.md" }, { "title": "Summary", "body": "This skill provides a reliable, API-driven approach to generating weekly earnings calendars for US stocks. By using FMP API, it ensures structured, accurate data with additional insights like EPS/revenue estimates. The multi-environment support makes it flexible for CLI, Desktop, and Web usage, while the fallback mode ensures functionality even without API access.\n\nKey Workflow: Date Calculation → API Key Setup → API Data Retrieval → Processing → Report Generation → QA → Delivery\n\nOutput: Clean, organized markdown report with earnings grouped by date/timing/market cap, including summary statistics and trading considerations." } ], "body": "Earnings Calendar\nOverview\n\nThis skill retrieves upcoming earnings announcements for US stocks using the Financial Modeling Prep (FMP) API. It focuses on companies with significant market capitalization (mid-cap and above, over $2B) that are likely to impact market movements. The skill generates organized markdown reports showing which companies are reporting earnings over the next week, grouped by date and timing (before market open, after market close, or time not announced).\n\nKey Features:\n\nUses FMP API for reliable, structured earnings data\nFilters by market cap (>$2B) to focus on market-moving companies\nIncludes EPS and revenue estimates\nMulti-environment support (CLI, Desktop, Web)\nFlexible API key management\nOrganized by date, timing, and market cap\nPrerequisites\nFMP API Key\n\nThis skill requires a Financial Modeling Prep API key.\n\nGet Free API Key:\n\nVisit: https://site.financialmodelingprep.com/developer/docs\nSign up for free account\nReceive API key immediately\nFree tier: 250 API calls/day (sufficient for weekly earnings calendar)\n\nAPI Key Setup by Environment:\n\nClaude Code (CLI):\n\nexport FMP_API_KEY=\"your-api-key-here\"\n\n\nClaude Desktop: Set environment variable in system or configure MCP server.\n\nClaude Web: API key will be requested during skill execution (stored only for current session).\n\nCore Workflow\nStep 1: Get Current Date and Calculate Target Week\n\nCRITICAL: Always start by obtaining the accurate current date.\n\nRetrieve the current date and time:\n\nUse system date/time to get today's date\nNote: \"Today's date\" is provided in the environment ( tag)\nCalculate the target week: Next 7 days from current date\n\nDate Range Calculation:\n\nCurrent Date: [e.g., November 2, 2025]\nTarget Week Start: [Current Date + 1 day, e.g., November 3, 2025]\nTarget Week End: [Current Date + 7 days, e.g., November 9, 2025]\n\n\nWhy This Matters:\n\nEarnings calendars are time-sensitive\n\"Next week\" must be calculated from the actual current date\nProvides accurate date range for API request\n\nFormat dates in YYYY-MM-DD for API compatibility.\n\nStep 2: Load FMP API Guide\n\nBefore retrieving data, load the comprehensive FMP API guide:\n\nRead: references/fmp_api_guide.md\n\n\nThis guide contains:\n\nFMP API endpoint structure and parameters\nAuthentication requirements\nMarket cap filtering strategy (via Company Profile API)\nEarnings timing conventions (BMO, AMC, TAS)\nResponse format and field descriptions\nError handling strategies\nBest practices and optimization tips\nStep 3: API Key Detection and Configuration\n\nDetect API key availability based on environment.\n\nMulti-Environment API Key Detection:\n\n3.1 Check Environment Variable (CLI/Desktop)\nif [ ! -z \"$FMP_API_KEY\" ]; then\n echo \"✓ API key found in environment\"\n API_KEY=$FMP_API_KEY\nfi\n\n\nIf environment variable is set, proceed to Step 4.\n\n3.2 Prompt User for API Key (Desktop/Web)\n\nIf environment variable not found, use AskUserQuestion tool:\n\nQuestion Configuration:\n\nQuestion: \"This skill requires an FMP API key to retrieve earnings data. Do you have an FMP API key?\"\nHeader: \"API Key\"\nOptions:\n 1. \"Yes, I'll provide it now\" → Proceed to 3.3\n 2. \"No, get free key\" → Show instructions (3.2.1)\n 3. \"Skip API, use manual entry\" → Jump to Step 8 (fallback mode)\n\n\n3.2.1 If user chooses \"No, get free key\":\n\nProvide instructions:\n\nTo get a free FMP API key:\n\n1. Visit: https://site.financialmodelingprep.com/developer/docs\n2. Click \"Get Free API Key\" or \"Sign Up\"\n3. Create account (email + password)\n4. Receive API key immediately\n5. Free tier includes 250 API calls/day (sufficient for daily use)\n\nOnce you have your API key, please select \"Yes, I'll provide it now\" to continue.\n\n3.3 Request API Key Input\n\nIf user has API key, request input:\n\nPrompt:\n\nPlease paste your FMP API key below:\n\n(Your API key will only be stored for this conversation session and will be forgotten when the session ends. For regular use, consider setting the FMP_API_KEY environment variable.)\n\n\nStore API key in session variable:\n\nAPI_KEY = [user_input]\n\n\nConfirm with user:\n\n✓ API key received and stored for this session.\n\nSecurity Note:\n- API key is stored only in current conversation context\n- Not saved to disk or persistent storage\n- Will be forgotten when session ends\n- Do not share this conversation if it contains your API key\n\nProceeding with earnings data retrieval...\n\nStep 4: Retrieve Earnings Data via FMP API\n\nUse the Python script to fetch earnings data from FMP API.\n\nScript Location:\n\nscripts/fetch_earnings_fmp.py\n\n\nExecution:\n\nOption A: With Environment Variable (CLI):\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09\n\n\nOption B: With Session API Key (Desktop/Web):\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 \"${API_KEY}\"\n\n\nScript Workflow (automatic):\n\nValidates API key and date parameters\nCalls FMP Earnings Calendar API for date range\nFetches company profiles (market cap, sector, industry)\nFilters companies with market cap >$2B\nNormalizes timing (BMO/AMC/TAS)\nSorts by date → timing → market cap (descending)\nOutputs JSON to stdout\n\nExpected Output Format (JSON):\n\n[\n {\n \"symbol\": \"AAPL\",\n \"companyName\": \"Apple Inc.\",\n \"date\": \"2025-11-04\",\n \"timing\": \"AMC\",\n \"marketCap\": 3000000000000,\n \"marketCapFormatted\": \"$3.0T\",\n \"sector\": \"Technology\",\n \"industry\": \"Consumer Electronics\",\n \"epsEstimated\": 1.54,\n \"revenueEstimated\": 123400000000,\n \"fiscalDateEnding\": \"2025-09-30\",\n \"exchange\": \"NASDAQ\"\n },\n ...\n]\n\n\nSave to file (recommended for use with report generator):\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 \"${API_KEY}\" > earnings_data.json\n\n\nOr capture to variable:\n\nearnings_data=$(python scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 \"${API_KEY}\")\n\n\nError Handling:\n\nIf script returns errors:\n\n401 Unauthorized: Invalid API key → Verify key or re-enter\n429 Rate Limit: Exceeded 250 calls/day → Wait or upgrade plan\nEmpty Result: No earnings in date range → Expand date range or note in report\nConnection Error: Network issue → Retry or use cached data if available\nStep 5: Process and Organize Data\n\nOnce earnings data is retrieved (JSON format), process and organize it:\n\n5.1 Parse JSON Data\n\nLoad JSON data from script output:\n\nimport json\nearnings_data = json.loads(earnings_json_string)\n\n\nOr if saved to file:\n\nwith open('earnings_data.json', 'r') as f:\n earnings_data = json.load(f)\n\n5.2 Verify Data Structure\n\nConfirm data includes required fields:\n\n✓ symbol\n✓ companyName\n✓ date\n✓ timing (BMO/AMC/TAS)\n✓ marketCap\n✓ sector\n5.3 Group by Date\n\nGroup all earnings announcements by date:\n\nSunday, [Full Date] (if applicable)\nMonday, [Full Date]\nTuesday, [Full Date]\nWednesday, [Full Date]\nThursday, [Full Date]\nFriday, [Full Date]\nSaturday, [Full Date] (if applicable)\n5.4 Sub-Group by Timing\n\nWithin each date, create three sub-sections:\n\nBefore Market Open (BMO)\nAfter Market Close (AMC)\nTime Not Announced (TAS)\n\nData is already sorted by timing from the script, so maintain this order.\n\n5.5 Within Each Timing Group\n\nCompanies are already sorted by market cap descending (script output):\n\nMega-cap (>$200B) first\nLarge-cap ($10B-$200B) second\nMid-cap ($2B-$10B) third\n\nThis prioritization ensures the most market-moving companies are listed first.\n\n5.6 Calculate Summary Statistics\n\nCompute:\n\nTotal Companies: Count of all companies in dataset\nMega/Large Cap Count: Count where marketCap >= $10B\nMid Cap Count: Count where marketCap between $2B and $10B\nPeak Day: Day of week with most earnings announcements\nSector Distribution: Count by sector (Technology, Healthcare, Financial, etc.)\nHighest Market Cap Companies: Top 5 companies by market cap\nStep 6: Generate Markdown Report\n\nUse the report generation script to create a formatted markdown report from the JSON data.\n\nScript Location:\n\nscripts/generate_report.py\n\n\nExecution:\n\nOption A: Output to stdout:\n\npython scripts/generate_report.py earnings_data.json\n\n\nOption B: Save to file:\n\npython scripts/generate_report.py earnings_data.json earnings_calendar_2025-11-02.md\n\n\nWhat the script does:\n\nLoads earnings data from JSON file\nGroups by date and timing (BMO/AMC/TAS)\nSorts by market cap within each group\nCalculates summary statistics\nGenerates formatted markdown report\nOutputs to stdout or saves to file\n\nThe script automatically handles all formatting including:\n\nProper markdown table structure\nDate grouping and day names\nMarket cap sorting\nEPS and revenue formatting\nSummary statistics calculation\n\nReport Structure:\n\n# Upcoming Earnings Calendar - Week of [START_DATE] to [END_DATE]\n\n**Report Generated**: [Current Date]\n**Data Source**: FMP API (Mid-cap and above, >$2B market cap)\n**Coverage Period**: Next 7 days\n**Total Companies**: [COUNT]\n\n---\n\n## Executive Summary\n\n- **Total Companies Reporting**: [TOTAL_COUNT]\n- **Mega/Large Cap (>$10B)**: [LARGE_CAP_COUNT]\n- **Mid Cap ($2B-$10B)**: [MID_CAP_COUNT]\n- **Peak Day**: [DAY_WITH_MOST_EARNINGS]\n\n---\n\n## [Day Name], [Full Date]\n\n### Before Market Open (BMO)\n\n| Ticker | Company | Market Cap | Sector | EPS Est. | Revenue Est. |\n|--------|---------|------------|--------|----------|--------------|\n| [TICKER] | [COMPANY] | [MCAP] | [SECTOR] | [EPS] | [REV] |\n\n### After Market Close (AMC)\n\n| Ticker | Company | Market Cap | Sector | EPS Est. | Revenue Est. |\n|--------|---------|------------|--------|----------|--------------|\n| [TICKER] | [COMPANY] | [MCAP] | [SECTOR] | [EPS] | [REV] |\n\n### Time Not Announced (TAS)\n\n| Ticker | Company | Market Cap | Sector | EPS Est. | Revenue Est. |\n|--------|---------|------------|--------|----------|--------------|\n| [TICKER] | [COMPANY] | [MCAP] | [SECTOR] | [EPS] | [REV] |\n\n---\n\n[Repeat for each day of week]\n\n---\n\n## Key Observations\n\n### Highest Market Cap Companies This Week\n1. [COMPANY] ([TICKER]) - [MCAP] - [DATE] [TIME]\n2. [COMPANY] ([TICKER]) - [MCAP] - [DATE] [TIME]\n3. [COMPANY] ([TICKER]) - [MCAP] - [DATE] [TIME]\n\n### Sector Distribution\n- **Technology**: [COUNT] companies\n- **Healthcare**: [COUNT] companies\n- **Financial**: [COUNT] companies\n- **Consumer**: [COUNT] companies\n- **Other**: [COUNT] companies\n\n### Trading Considerations\n- **Days with Heavy Volume**: [DATES with multiple large-cap earnings]\n- **Pre-Market Focus**: [BMO companies that may move markets]\n- **After-Hours Focus**: [AMC companies that may move markets]\n\n---\n\n## Timing Reference\n\n- **BMO (Before Market Open)**: Announcements typically around 6:00-8:00 AM ET before market opens at 9:30 AM ET\n- **AMC (After Market Close)**: Announcements typically around 4:00-5:00 PM ET after market closes at 4:00 PM ET\n- **TAS (Time Not Announced)**: Specific time not yet disclosed - monitor company investor relations\n\n---\n\n## Data Notes\n\n- **Market Cap Categories**:\n - Mega Cap: >$200B\n - Large Cap: $10B-$200B\n - Mid Cap: $2B-$10B\n\n- **Filter Criteria**: This report includes companies with market cap $2B and above (mid-cap+) with earnings scheduled for the next week.\n\n- **Data Source**: Financial Modeling Prep (FMP) API\n\n- **Data Freshness**: Earnings dates and times can change. Verify critical dates through company investor relations websites for the most current information.\n\n- **EPS and Revenue Estimates**: Analyst consensus estimates from FMP API. Actual results will be reported on earnings date.\n\n---\n\n## Additional Resources\n\n- **FMP API Documentation**: https://site.financialmodelingprep.com/developer/docs\n- **Seeking Alpha Calendar**: https://seekingalpha.com/earnings/earnings-calendar\n- **Yahoo Finance Calendar**: https://finance.yahoo.com/calendar/earnings\n\n---\n\n*Report generated using FMP Earnings Calendar API with mid-cap+ filter (>$2B market cap). Data current as of report generation time. Always verify earnings dates through official company sources.*\n\n\nFormatting Best Practices:\n\nUse markdown tables for clean presentation\nBold important company names (mega-cap) if desired\nInclude market cap in human-readable format ($3.0T, $150B, $5.2B) - already formatted by script\nGroup logically by date then timing\nInclude summary section at top for quick overview\nAdd EPS and revenue estimates if available\nStep 7: Quality Assurance\n\nBefore finalizing the report, verify:\n\nData Quality Checks:\n\n✓ All dates fall within the target week (next 7 days)\n✓ Market cap values are present for all companies\n✓ Each company has timing specified (BMO/AMC/TAS)\n✓ Companies are sorted by market cap within each section\n✓ Summary statistics are accurate\n✓ Report generation date is clearly stated\n✓ EPS and revenue estimates included where available\n\nCompleteness Checks:\n\n✓ All days of the target week are included (even if no earnings)\n✓ Major known companies are not missing (verify against external sources if needed)\n✓ Sector information is included where available\n✓ Timing reference section is present\n✓ Data sources are credited (FMP API)\n\nFormat Checks:\n\n✓ Markdown tables are properly formatted\n✓ Dates are consistently formatted\n✓ Market caps use consistent units (B for billions, T for trillions)\n✓ All sections follow template structure\n✓ No placeholder text ([PLACEHOLDER]) remains\n✓ EPS and revenue estimates properly formatted\nStep 8: Save and Deliver Report\n\nSave the generated report with an appropriate filename:\n\nFilename Convention:\n\nearnings_calendar_[YYYY-MM-DD].md\n\n\nExample: earnings_calendar_2025-11-02.md\n\nThe filename date represents the report generation date, not the earnings week.\n\nDelivery:\n\nSave the markdown file to the working directory\nInform the user that the report has been generated\nProvide a brief summary of key findings (e.g., \"45 companies reporting next week, with Apple and Microsoft on Monday\")\n\nExample Summary:\n\n✓ Earnings calendar report generated: earnings_calendar_2025-11-02.md\n\nSummary for week of November 3-9, 2025:\n- 45 companies reporting earnings\n- 28 large/mega-cap, 17 mid-cap\n- Peak day: Thursday (15 companies)\n- Notable: Apple (Mon AMC), Microsoft (Tue AMC), Tesla (Wed AMC)\n\nTop 5 by market cap:\n1. Apple - $3.0T (Mon AMC)\n2. Microsoft - $2.8T (Tue AMC)\n3. Alphabet - $1.8T (Thu AMC)\n4. Amazon - $1.6T (Fri AMC)\n5. Tesla - $800B (Wed AMC)\n\nFallback Mode (Step 8 Alternative): Manual Data Entry\n\nIf API access is unavailable or user chooses to skip API:\n\nProvide Instructions for Manual Entry:\n\nSince FMP API is not available, you can manually gather earnings data:\n\n1. Visit Finviz: https://finviz.com/screener.ashx?v=111&f=cap_midover%2Cearningsdate_nextweek\n2. Or Yahoo Finance: https://finance.yahoo.com/calendar/earnings\n3. Note down companies reporting next week\n\nPlease provide the following information for each company:\n- Ticker symbol\n- Company name\n- Earnings date\n- Timing (BMO/AMC/TAS)\n- Market cap (approximate)\n- Sector\n\nI will format this into the standard earnings calendar report.\n\n\nProcess Manual Input:\n\nParse user-provided earnings data\nOrganize by date, timing, and market cap\nGenerate report using same template\nNote in report: \"Data Source: Manual Entry\"\nUse Cases and Examples\nUse Case 1: Weekly Review (Primary Use Case)\n\nUser Request: \"Get next week's earnings calendar\"\n\nWorkflow:\n\nGet current date (e.g., November 2, 2025)\nCalculate target week (November 3-9, 2025)\nLoad FMP API guide\nDetect/request API key\nFetch earnings data:\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 > earnings_data.json\n\nGenerate markdown report:\npython scripts/generate_report.py earnings_data.json earnings_calendar_2025-11-02.md\n\nNotify user with summary\n\nComplete One-Liner:\n\npython scripts/fetch_earnings_fmp.py 2025-11-03 2025-11-09 > earnings_data.json && \\\npython scripts/generate_report.py earnings_data.json earnings_calendar_2025-11-02.md\n\nUse Case 2: Focused on Specific Day\n\nUser Request: \"What earnings are coming out Monday?\"\n\nWorkflow:\n\nGet current date and identify next Monday (e.g., November 4, 2025)\nFetch full week data (same as Use Case 1)\nGenerate full report but highlight Monday section\nProvide verbal summary of Monday's earnings with emphasis\nUse Case 3: Mega-Cap Focus\n\nUser Request: \"Show me earnings for companies over $100B market cap next week\"\n\nWorkflow:\n\nFetch full earnings data (script already filters >$2B)\nProcess and organize as normal\nWhen generating report, add a \"Mega-Cap Focus\" section at top\nFilter tables to show only companies >$100B\nNote: Still include full data in appendix for reference\nUse Case 4: Sector-Specific\n\nUser Request: \"What tech companies have earnings next week?\"\n\nWorkflow:\n\nFetch full earnings data\nProcess and organize as normal\nFilter results by sector = \"Technology\"\nGenerate report with focus on technology sector\nNote: Template structure remains the same; content is filtered\nTroubleshooting\nProblem: API key not working\n\nSolutions:\n\nVerify API key is correct (copy-paste carefully)\nCheck if API key is active (login to FMP dashboard)\nEnsure no extra spaces before/after key\nTry generating new API key from FMP dashboard\nProblem: Script returns empty results\n\nSolutions:\n\nVerify date range is in future (not past dates)\nCheck date format is YYYY-MM-DD\nTry wider date range (e.g., 14 days instead of 7)\nVerify companies actually have announced earnings dates for that week\nProblem: Missing major companies\n\nSolutions:\n\nCompany may not have announced earnings date yet\nSome companies announce dates very late (1-2 days before)\nCross-reference with company investor relations website\nMarket cap may have dropped below $2B threshold\nProblem: Rate limit hit (429 error)\n\nSolutions:\n\nFree tier: 250 calls/day\nEach weekly report uses ~3-5 API calls\nCheck if other tools/scripts are using same API key\nWait 24 hours for rate limit reset\nConsider upgrading to paid tier if needed frequently\nProblem: Script execution error\n\nSolutions:\n\nVerify Python 3 is installed: python3 --version\nInstall requests library: pip install requests\nCheck script has execute permissions: chmod +x fetch_earnings_fmp.py\nRun with python3 explicitly: python3 fetch_earnings_fmp.py ...\nBest Practices\nDo's\n\n✓ Always get current date first before any data retrieval ✓ Use FMP API as primary source for reliability ✓ Store API key in environment variable for CLI usage ✓ Sort by market cap to prioritize high-impact companies ✓ Group by date then timing for logical organization ✓ Include summary statistics for quick overview ✓ Credit data sources in report footer ✓ Use clean markdown tables for readability ✓ Provide timing reference section for clarity ✓ Note data freshness and potential for changes ✓ Include EPS and revenue estimates when available\n\nDon'ts\n\n✗ Don't assume \"next week\" without calculating from current date ✗ Don't omit timing information (BMO/AMC/TAS) ✗ Don't mix date formats within report (stay consistent) ✗ Don't include micro/small-cap unless specifically requested ✗ Don't forget to sort by market cap within sections ✗ Don't share API key in conversations or reports ✗ Don't include earnings from current week or past dates ✗ Don't generate report without quality assurance checks ✗ Don't commit API keys to version control\n\nSecurity Notes\nAPI Key Security\n\nImportant Reminders:\n\n✓ Use free tier API keys for testing\n✓ Rotate keys regularly\n✓ Don't share conversations containing API keys\n✓ Set API key as environment variable for CLI\n✓ Keys provided in chat are session-only (forgotten after session ends)\n✗ Never commit API keys to Git repositories\n✗ Never use production API keys with sensitive data access\n\nBest Practice: For Claude Code (CLI), always use environment variable:\n\n# Add to ~/.zshrc or ~/.bashrc\nexport FMP_API_KEY=\"your-key-here\"\n\n\nFor Claude Web, understand that:\n\nAPI key entered in chat is temporary\nStored only in conversation context\nNot saved to disk\nForgotten when session ends\nResources\n\nFMP API:\n\nMain Documentation: https://site.financialmodelingprep.com/developer/docs\nGet API Key: https://site.financialmodelingprep.com/developer/docs\nEarnings Calendar API: https://site.financialmodelingprep.com/developer/docs/earnings-calendar-api\nCompany Profile API: https://site.financialmodelingprep.com/developer/docs/companies-key-metrics-api\nPricing/Rate Limits: https://site.financialmodelingprep.com/developer/docs/pricing\n\nSupplementary Sources (for verification):\n\nSeeking Alpha: https://seekingalpha.com/earnings/earnings-calendar\nYahoo Finance: https://finance.yahoo.com/calendar/earnings\nMarketWatch: https://www.marketwatch.com/tools/earnings-calendar\n\nSkill Resources:\n\nFMP API Guide: references/fmp_api_guide.md\nPython Script: scripts/fetch_earnings_fmp.py\nReport Template: assets/earnings_report_template.md\nSummary\n\nThis skill provides a reliable, API-driven approach to generating weekly earnings calendars for US stocks. By using FMP API, it ensures structured, accurate data with additional insights like EPS/revenue estimates. The multi-environment support makes it flexible for CLI, Desktop, and Web usage, while the fallback mode ensures functionality even without API access.\n\nKey Workflow: Date Calculation → API Key Setup → API Data Retrieval → Processing → Report Generation → QA → Delivery\n\nOutput: Clean, organized markdown report with earnings grouped by date/timing/market cap, including summary statistics and trading considerations." }, "trust": { "sourceLabel": "tencent", "provenanceUrl": "https://clawhub.ai/Veeramanikandanr48/earnings-calendar", "publisherUrl": "https://clawhub.ai/Veeramanikandanr48/earnings-calendar", "owner": "Veeramanikandanr48", "version": "0.1.0", "license": null, "verificationStatus": "Indexed source record" }, "links": { "detailUrl": "https://openagent3.xyz/skills/earnings-calendar", "downloadUrl": "https://openagent3.xyz/downloads/earnings-calendar", "agentUrl": "https://openagent3.xyz/skills/earnings-calendar/agent", "manifestUrl": "https://openagent3.xyz/skills/earnings-calendar/agent.json", "briefUrl": "https://openagent3.xyz/skills/earnings-calendar/agent.md" } }