{
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    "generatedAt": "2026-07-29T07:31:00Z",
    "recordCount": 27
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  "documents": [
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/catalyst-calendar",
      "slug": "catalyst-calendar",
      "name": "Catalyst Calendar",
      "description": "Build and maintain a calendar of upcoming catalysts across a coverage universe — earnings dates, conferences, product launches, regulatory decisions, and macro events.",
      "summary": "An equity research workflow for tracking upcoming catalysts across a coverage universe. It covers earnings dates, corporate events, industry conferences, regulatory decisions, and macro events, and produces a sortable calendar view with weekly previews and positioning implications.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/catalyst-calendar",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/catalyst-calendar",
      "tags": [
        "catalyst-calendar",
        "earnings",
        "events",
        "equity-research",
        "macro",
        "positioning"
      ],
      "tasks": [
        "catalyst-tracking",
        "earnings-monitoring"
      ],
      "domains": [
        "equity-research",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 56,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/earnings-analysis",
      "slug": "earnings-analysis",
      "name": "Earnings Analysis",
      "description": "Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage.",
      "summary": "An equity research workflow for producing institutional-grade earnings update reports. It covers beat/miss analysis, segment breakdowns, margin and guidance analysis, updated estimates, and revised investment thesis, following JPMorgan, Goldman Sachs, and Morgan Stanley format standards.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/earnings-analysis",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/earnings-analysis",
      "tags": [
        "earnings",
        "equity-research",
        "beat-miss",
        "quarterly-results",
        "estimate-revision",
        "institutional-research"
      ],
      "tasks": [
        "earnings-analysis",
        "earnings-monitoring"
      ],
      "domains": [
        "equity-research",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "sec-edgar",
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "networkAccess",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 76,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/earnings-preview",
      "slug": "earnings-preview",
      "name": "Earnings Preview",
      "description": "Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch before a company reports quarterly earnings.",
      "summary": "An equity research workflow for preparing pre-earnings analysis. It covers consensus estimate gathering, sector-specific key metrics frameworks, bull/base/bear scenario analysis with stock price implications, catalyst checklists, and trading setup with options-implied move.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/earnings-preview",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/earnings-preview",
      "tags": [
        "earnings",
        "pre-earnings",
        "scenario-analysis",
        "equity-research",
        "positioning",
        "catalyst"
      ],
      "tasks": [
        "earnings-preview",
        "earnings-monitoring"
      ],
      "domains": [
        "equity-research",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 56,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/idea-generation",
      "slug": "idea-generation",
      "name": "Idea Generation",
      "description": "Systematic stock screening and investment idea sourcing combining quantitative screens, thematic research, and pattern recognition to surface new long and short ideas.",
      "summary": "An equity research workflow for generating investment ideas through quantitative screens (value, growth, quality, short, special situation), thematic sweeps, and pattern recognition. It produces a prioritized shortlist with one-page summaries, comparison tables, and suggested next steps for diligence.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/idea-generation",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/idea-generation",
      "tags": [
        "idea-generation",
        "stock-screening",
        "long-short",
        "thematic-research",
        "value",
        "growth",
        "special-situations"
      ],
      "tasks": [
        "idea-generation"
      ],
      "domains": [
        "equity-research",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 56,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/initiating-coverage",
      "slug": "initiating-coverage",
      "name": "Initiating Coverage",
      "description": "Create comprehensive equity research initiation reports (30-50 pages, 10,000-15,000 words) for first-time coverage of a company, covering company research, financial modeling, valuation, chart generation, and report assembly.",
      "summary": "An equity research workflow for initiating coverage on a company. It spans five tasks: company research, three-statement financial modeling, DCF and comps valuation, chart generation, and institutional-grade report assembly. The final deliverable is a publication-ready DOCX report at JPMorgan/Goldman Sachs quality standards.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/initiating-coverage",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/initiating-coverage",
      "tags": [
        "initiating-coverage",
        "equity-research",
        "financial-modeling",
        "dcf-valuation",
        "comps-analysis",
        "institutional-research",
        "report-generation"
      ],
      "tasks": [
        "initiating-coverage",
        "dcf-valuation",
        "excel-financial-modeling"
      ],
      "domains": [
        "equity-research",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "sec-edgar",
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "networkAccess",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 80,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/model-update",
      "slug": "model-update",
      "name": "Model Update",
      "description": "Update financial models with new data — quarterly earnings, management guidance, macro changes, or revised assumptions. Adjusts estimates, recalculates valuation, and flags material changes.",
      "summary": "An equity research workflow for updating financial models after earnings, guidance changes, or assumption revisions. It covers plugging actuals, revising forward estimates, recalculating DCF and multiples-based valuation, and producing an estimate change summary with updated price targets.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/model-update",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/model-update",
      "tags": [
        "model-update",
        "earnings",
        "estimate-revision",
        "valuation",
        "price-target",
        "equity-research"
      ],
      "tasks": [
        "model-update",
        "excel-financial-modeling"
      ],
      "domains": [
        "equity-research",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemRead",
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 56,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/morning-note",
      "slug": "morning-note",
      "name": "Morning Note",
      "description": "Draft concise morning meeting notes summarizing overnight developments, trade ideas, and key events for coverage stocks. Tight, opinionated, actionable — designed for the 7am morning meeting format.",
      "summary": "An equity research workflow for producing one-page morning meeting notes. It covers scanning overnight developments (earnings, news, market context), formatting a tight opinionated note with top call and trade ideas, and providing quick earnings reactions with rating and price target actions.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/morning-note",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/morning-note",
      "tags": [
        "morning-note",
        "morning-meeting",
        "overnight-developments",
        "trade-ideas",
        "earnings-reaction",
        "equity-research"
      ],
      "tasks": [
        "morning-note",
        "earnings-monitoring"
      ],
      "domains": [
        "equity-research"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 56,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/sector-overview",
      "slug": "sector-overview",
      "name": "Sector Overview",
      "description": "Create comprehensive industry and sector landscape reports covering market dynamics, competitive positioning, key players, and thematic trends. Use for client requests, sector initiations, thematic research, or internal knowledge building.",
      "summary": "An equity research workflow for producing sector and industry landscape reports. It covers market sizing and growth, industry structure, competitive landscape with company profiles and valuation, investment implications, and chart-rich deliverables in Word, PowerPoint, and Excel formats.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/sector-overview",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/sector-overview",
      "tags": [
        "sector-overview",
        "industry-report",
        "market-landscape",
        "competitive-analysis",
        "thematic-research",
        "equity-research"
      ],
      "tasks": [
        "sector-overview"
      ],
      "domains": [
        "equity-research"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 59,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/equity-research/skills/thesis-tracker",
      "slug": "thesis-tracker",
      "name": "Thesis Tracker",
      "description": "Maintain and update investment theses for portfolio positions and watchlist names. Track key data points, catalysts, and thesis milestones over time. Use when updating a thesis with new information, reviewing position rationale, or checking if a thesis is still intact.",
      "summary": "An equity research workflow for maintaining and updating investment theses. It covers defining thesis statements with pillars, risks, catalysts, and target prices, maintaining a running scorecard with conviction levels, tracking disconfirming evidence, and producing thesis summaries for portfolio review or risk committee.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/thesis-tracker",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/equity-research/skills/thesis-tracker",
      "tags": [
        "thesis-tracker",
        "investment-thesis",
        "portfolio-management",
        "catalyst-tracking",
        "conviction-tracking",
        "equity-research"
      ],
      "tasks": [
        "thesis-tracker",
        "catalyst-tracking"
      ],
      "domains": [
        "equity-research"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemRead",
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 56,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/3-statement-model",
      "slug": "3-statement-model",
      "name": "3-Statement Model",
      "description": "Complete and populate integrated 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement) with proper linkages, formulas, and validation checks.",
      "summary": "A 3-statement financial modeling workflow for completing integrated Income Statement, Balance Sheet, and Cash Flow Statement templates. It covers template structure analysis, formula integrity, cross-statement validation, scenario analysis, credit metrics, SEC filings data extraction, and staged user review at each statement.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/3-statement-model",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/3-statement-model",
      "tags": [
        "3-statement-model",
        "income-statement",
        "balance-sheet",
        "cash-flow",
        "financial-modeling",
        "excel"
      ],
      "tasks": [
        "cash-flow-forecasting",
        "excel-financial-modeling"
      ],
      "domains": [
        "financial-modeling",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "sec-edgar",
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "networkAccess",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 78,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/audit-xls",
      "slug": "audit-xls",
      "name": "Audit Spreadsheet",
      "description": "Audit a spreadsheet for formula accuracy, errors, and common mistakes. Scopes to a selected range, a single sheet, or the entire model including financial-model integrity checks like BS balance, cash tie-out, and logic sanity.",
      "summary": "A financial analysis workflow for auditing Excel spreadsheets. It covers formula-level checks (errors, hardcodes, inconsistent formulas, circular references), model-integrity checks (BS balance, cash tie-out, roll-forwards), and model-type-specific bugs for DCF, LBO, merger, and 3-statement models. Outputs a severity-ranked findings table.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/audit-xls",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/audit-xls",
      "tags": [
        "audit-xls",
        "spreadsheet-audit",
        "formula-check",
        "model-integrity",
        "qa",
        "financial-analysis"
      ],
      "tasks": [
        "audit-xls",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemRead"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 65,
        "riskLevel": "low",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/clean-data-xls",
      "slug": "clean-data-xls",
      "name": "Clean Spreadsheet Data",
      "description": "Clean up messy spreadsheet data — trim whitespace, fix inconsistent casing, convert numbers-stored-as-text, standardize dates, remove duplicates, and flag mixed-type columns. Use when data is messy, inconsistent, or needs prep before analysis.",
      "summary": "A financial analysis workflow for cleaning messy Excel spreadsheet data. It covers whitespace trimming, casing normalization, number-as-text conversion, date standardization, deduplication, encoding repair, and error flagging. Prefers transparent helper-column formulas over hardcoded values and requires user confirmation for destructive operations.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/clean-data-xls",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/clean-data-xls",
      "tags": [
        "clean-data-xls",
        "data-cleaning",
        "spreadsheet-prep",
        "normalization",
        "deduplication",
        "financial-analysis"
      ],
      "tasks": [
        "clean-data-xls",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemRead",
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 80,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/competitive-analysis",
      "slug": "competitive-analysis",
      "name": "Competitive Landscape Mapping",
      "description": "Framework for building competitive landscape decks — market positioning, competitor deep-dives, comparative analysis, strategic synthesis. Use when the user asks for a competitive landscape, competitor analysis, peer comparison, market positioning assessment, strategic review, or investment memo deck.",
      "summary": "A financial analysis workflow for building competitive landscape decks. It covers industry-defining metrics, market context, industry economics, target company profiles, competitor mapping, positioning visualization, competitor deep-dives, comparative analysis, strategic context, and synthesis with moat assessment and optional bull/base/bear scenarios. Includes reference files for 2x2 matrix frameworks and table schemas.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/competitive-analysis",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/competitive-analysis",
      "tags": [
        "competitive-analysis",
        "market-positioning",
        "competitor-mapping",
        "moat-assessment",
        "peer-comparison",
        "financial-analysis"
      ],
      "tasks": [
        "competitive-analysis",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data",
        "sec-edgar",
        "web-market-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemRead",
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 69,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/comps-analysis",
      "slug": "comps-analysis",
      "name": "Comparable Company Analysis",
      "description": "Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. Perfect for public company valuation, benchmarking performance, pricing IPOs, and supporting investment committee presentations.",
      "summary": "A financial analysis workflow for building institutional-grade comparable company analyses (comps) in Excel. It covers document structure, operating statistics (revenue, growth, margins, EBITDA), valuation multiples (EV/Revenue, EV/EBITDA, P/E), statistical benchmarking with quartiles, industry-specific metric selection, data source hierarchy (MCP first), formula transparency, and quality control with sanity checks and output checklists.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/comps-analysis",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/comps-analysis",
      "tags": [
        "comps-analysis",
        "comparable-company-analysis",
        "valuation-multiples",
        "peer-benchmarking",
        "ev-ebitda",
        "financial-analysis"
      ],
      "tasks": [
        "comps-analysis",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "daloopa",
        "sec-edgar",
        "user-provided-data",
        "web-market-data",
        "bloomberg",
        "factset"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "filesystemRead",
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 74,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/dcf-model",
      "slug": "dcf-model",
      "name": "DCF Model",
      "description": "Build an Excel discounted cash flow valuation with WACC, scenario analysis, formula checks, and source notes.",
      "summary": "A detailed DCF modeling workflow for public company valuation. It covers financial data collection, cash flow forecasts, WACC, terminal value, sensitivity tables, workbook checks, and staged user review.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/dcf-model",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/dcf-model",
      "tags": [
        "dcf",
        "valuation",
        "wacc",
        "free-cash-flow",
        "sensitivity-analysis",
        "excel"
      ],
      "tasks": [
        "dcf-valuation",
        "wacc-analysis",
        "cash-flow-forecasting",
        "sensitivity-analysis",
        "excel-financial-modeling"
      ],
      "domains": [
        "equity-valuation",
        "financial-modeling",
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "daloopa",
        "sec-edgar",
        "user-provided-data",
        "web-market-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "unknown",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "networkAccess",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 88,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/deck-refresh",
      "slug": "deck-refresh",
      "name": "Deck Refresh",
      "description": "Updates a presentation with new numbers — quarterly refreshes, earnings updates, comp rolls, rebased market data. Use whenever the user asks to update the deck with new figures, refresh comps, roll forward, or swap values across an existing deck without rebuilding it.",
      "summary": "A financial analysis workflow for updating numbers across existing presentation decks. It covers four phases: getting new data from user mappings or uploaded files, reading every slide to find all number variants, presenting a change plan for approval, and executing with formatting preservation. Handles scale variants, precision variants, unit style variants, embedded numbers in charts and footnotes, and flags derived numbers that may become stale.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/deck-refresh",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/deck-refresh",
      "tags": [
        "deck-refresh",
        "presentation-update",
        "quarterly-refresh",
        "earnings-update",
        "comp-roll",
        "financial-analysis"
      ],
      "tasks": [
        "deck-refresh",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemRead",
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 69,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/ib-check-deck",
      "slug": "ib-check-deck",
      "name": "IB Deck Checker",
      "description": "Investment banking presentation quality checker. Reviews a pitch deck or client-ready presentation for number consistency, data-narrative alignment, language polish against IB standards, and visual and formatting QC. Use whenever the user asks to review, check, QC, proof, or do a final pass on a deck or client materials.",
      "summary": "A financial analysis workflow for quality-checking investment banking presentations. It covers four QC dimensions: number consistency (with an automated Python extraction script that normalizes units and flags conflicts), data-narrative alignment (verifying claims against supporting data), language polish (IB terminology standards with replacement patterns), and visual formatting QC. Output is a structured report with severity classification (critical, important, minor). Includes reference files for IB terminology and report format.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/ib-check-deck",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/ib-check-deck",
      "tags": [
        "ib-check-deck",
        "presentation-qc",
        "number-consistency",
        "data-narrative-alignment",
        "ib-terminology",
        "financial-analysis"
      ],
      "tasks": [
        "ib-check-deck",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 79,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/financial-analysis/skills/lbo-model",
      "slug": "lbo-model",
      "name": "LBO Model",
      "description": "Completes LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. Fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.",
      "summary": "A financial analysis workflow for building institutional-grade LBO models in Excel. It covers template analysis, section-by-section formula filling (Sources & Uses, Operating Model, Debt Schedule, Returns Analysis, Sensitivity Tables), formula color conventions (blue/black/purple/green), fill color palette, circular reference handling with beginning balances, debt paydown waterfalls, IRR/MOIC returns with correct signs, odd-dimension sensitivity tables, section-by-section user checkpoints, and a comprehensive verification checklist.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/lbo-model",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/financial-analysis/skills/lbo-model",
      "tags": [
        "lbo-model",
        "leveraged-buyout",
        "private-equity",
        "sources-and-uses",
        "debt-schedule",
        "irr-moic",
        "financial-analysis"
      ],
      "tasks": [
        "lbo-model",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 77,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/buyer-list",
      "slug": "buyer-list",
      "name": "Buyer List",
      "description": "Build and organize a universe of potential acquirers for sell-side M&A processes. Identifies strategic and financial buyers, assesses fit, and prioritizes outreach. Use when preparing for a sell-side mandate, building a buyer universe, or evaluating potential partners.",
      "summary": "An investment banking workflow for building buyer universes in sell-side M&A. It covers six steps: understanding the target, identifying strategic buyers (direct competitors, adjacent players, vertical integrators, platform builders), identifying financial sponsors (platform investors, add-on buyers, growth equity), tiered prioritization, contact mapping for Tier 1, and producing an Excel workbook with buyer tabs, contact mapping, and summary statistics.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/buyer-list",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/buyer-list",
      "tags": [
        "buyer-list",
        "sell-side-ma",
        "strategic-buyers",
        "financial-sponsors",
        "acquirer-screening",
        "investment-banking"
      ],
      "tasks": [
        "buyer-list",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 61,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/cim-builder",
      "slug": "cim-builder",
      "name": "CIM Builder",
      "description": "Structure and draft a Confidential Information Memorandum for sell-side M&A processes. Organizes company information into a professional, investor-ready document with consistent formatting and narrative flow. Use when preparing sell-side materials, drafting a CIM, or organizing company data for a sale process.",
      "summary": "An investment banking workflow for building Confidential Information Memoranda in sell-side M&A. It covers four steps: gathering source materials, structuring the CIM across 8 sections (Executive Summary, Company Overview, Industry Overview, Growth Opportunities, Customers & Sales, Operations, Financial Overview, Appendix), applying drafting guidelines (professional tone, data-driven claims, 40-60 pages), and producing a Word document with Excel appendix and embedded charts.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/cim-builder",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/cim-builder",
      "tags": [
        "cim-builder",
        "confidential-information-memorandum",
        "sell-side-ma",
        "offering-memorandum",
        "investment-banking"
      ],
      "tasks": [
        "cim-builder",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 65,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/datapack-builder",
      "slug": "datapack-builder",
      "name": "Data Pack Builder",
      "description": "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.",
      "summary": "An investment banking workflow for building standardized financial data packs from CIMs, SEC filings, web search, and MCP servers. It covers six phases: document processing and data extraction, data normalization (restructuring charges, SBC, acquisition costs, legal settlements, related party adjustments), Excel workbook building (8-tab structure), scenario building (management/base/downside cases), quality control (5 check categories), and final delivery. Includes industry-specific adaptations for SaaS, manufacturing, real estate, and healthcare.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/datapack-builder",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/datapack-builder",
      "tags": [
        "datapack-builder",
        "financial-data-pack",
        "ma-due-diligence",
        "private-equity",
        "investment-committee",
        "investment-banking"
      ],
      "tasks": [
        "datapack-builder",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "sec-edgar",
        "user-provided-data",
        "web-market-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "networkAccess"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 76,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/deal-tracker",
      "slug": "deal-tracker",
      "name": "Deal Tracker",
      "description": "Track multiple live deals with milestones, deadlines, action items, and status updates. Maintains a deal pipeline view and surfaces upcoming deadlines and overdue items. Use when managing a book of business, tracking process milestones, or preparing for weekly deal reviews.",
      "summary": "An investment banking workflow for tracking M&A deal pipelines. It covers five steps: deal setup (name, client, type, role, size, stage, team, key dates), milestone tracking (18 milestones from engagement to close with status), action items (running list with owner, due date, priority), weekly deal review (per-deal status and pipeline summary), and producing an Excel workbook with pipeline overview, milestone tracker tabs, action item list, and weekly review summary.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/deal-tracker",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/deal-tracker",
      "tags": [
        "deal-tracker",
        "deal-pipeline",
        "ma-process-tracking",
        "milestone-tracking",
        "investment-banking"
      ],
      "tasks": [
        "deal-tracker",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 61,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/merger-model",
      "slug": "merger-model",
      "name": "Merger Model",
      "description": "Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms.",
      "summary": "An investment banking workflow for building M&A accretion/dilution models. It covers seven steps: gathering acquirer/target/deal term inputs, purchase price analysis (premium, EV/EBITDA, P/E implied), sources & uses, pro forma EPS calculation (year 1-3 with synergies, foregone interest, new debt interest, intangible amortization), sensitivity analysis (synergies vs premium, cash/stock mix), breakeven synergies, and producing an Excel workbook with one-page merger consequences summary.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/merger-model",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/merger-model",
      "tags": [
        "merger-model",
        "accretion-dilution",
        "pro-forma-eps",
        "ma-modeling",
        "synergy-analysis",
        "investment-banking"
      ],
      "tasks": [
        "merger-model",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 57,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/pitch-deck",
      "slug": "pitch-deck",
      "name": "Pitch Deck",
      "description": "Populate investment banking pitch deck templates with data from source files. Use when user provides a PowerPoint template to fill in, has source data (Excel/CSV) to populate into slides, mentions populating or filling a pitch deck template, or needs to transfer data into existing slide layouts. Not for creating presentations from scratch.",
      "summary": "An investment banking workflow for populating pitch deck PowerPoint templates with financial data. It covers five phases: data extraction (backup, identify sources, validate numbers, standardize units), content mapping (analyze template, map data to sections), template population (remove placeholder boxes, populate content, apply formatting, create table objects), validate-fix-repeat (visual validation via LibreOffice, 9-point checklist, 3-cycle fix protocol), and final verification. Includes four reference files for formatting standards, slide templates, XML patterns, and calculation standards.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/pitch-deck",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/pitch-deck",
      "tags": [
        "pitch-deck",
        "presentation-templates",
        "powerpoint-population",
        "ib-pitch-book",
        "investment-banking"
      ],
      "tasks": [
        "pitch-deck",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "codeExecution",
        "filesystemRead",
        "filesystemWrite",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 86,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/process-letter",
      "slug": "process-letter",
      "name": "Process Letter",
      "description": "Draft process letters and bid instructions for sell-side M&A processes. Covers initial indication of interest (IOI) instructions, final bid procedures, and management meeting logistics.",
      "summary": "An investment banking workflow for drafting sell-side M&A process letters. It covers five steps: determining letter type (initial, IOI, final bid, management meeting), initial process letter/IOI instructions (6 sections including IOI requirements with valuation, consideration, financing, diligence, timeline, and strategic rationale), final bid/second round letter (8 additional requirements including SPA markup, committed financing, exclusivity, regulatory, and evaluation criteria), management meeting invitation (logistics, attendees, agenda, ground rules, materials, follow-up), and producing a Word document with track changes for client review.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/process-letter",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/process-letter",
      "tags": [
        "process-letter",
        "bid-instructions",
        "ioi-letter",
        "sell-side-ma",
        "investment-banking"
      ],
      "tasks": [
        "process-letter",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 61,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/strip-profile",
      "slug": "strip-profile",
      "name": "Strip Profile",
      "description": "Create professional investment banking strip profiles (company profiles) for pitch books, deal materials, and client presentations. Generates 1-4 information-dense slides with quadrant layouts, charts, and tables.",
      "summary": "An investment banking workflow for creating professional company strip profiles. It covers three steps: clarifying requirements (single vs multi-slide, focus areas), research and planning (SEC filings, Bloomberg, FactSet, CapIQ for financials, valuation, growth, ownership, segments), and slide-by-slide creation with PptxGenJS (4:3 format, quadrant layouts, charts, tables, mandatory visual review via soffice/pdftoppm, per-slide user approval gates). Includes detailed formatting standards, font sizes, chart code examples, and a quality checklist at IB standard.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/strip-profile",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/strip-profile",
      "tags": [
        "strip-profile",
        "company-profile",
        "pitch-book",
        "powerpoint-generation",
        "investment-banking"
      ],
      "tasks": [
        "strip-profile",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "sec-edgar",
        "bloomberg",
        "factset",
        "web-market-data",
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "yes",
      "permissions": [
        "codeExecution",
        "externalCredentials",
        "filesystemWrite",
        "networkAccess",
        "shellExecution"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 74,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    },
    {
      "id": "github:anthropics/financial-services:plugins/vertical-plugins/investment-banking/skills/teaser",
      "slug": "teaser",
      "name": "Teaser",
      "description": "Draft anonymous one-page company teasers for sell-side M&A processes. Creates a compelling summary without revealing the company identity, designed to gauge buyer interest before NDA execution.",
      "summary": "An investment banking workflow for drafting anonymous one-page company teasers for sell-side M&A processes. It covers four steps: gathering inputs (company description, sector, financial metrics, geography, selling points, anonymization guidance, target buyer audience), teaser structure (header with deal code name, company description, investment highlights, financial summary table, transaction overview), anonymization check (no company name, brand names, specific cities, named customers, identifiable imagery), and output (Word, PDF, optional PowerPoint). Designed to generate buyer interest before NDA execution.",
      "status": "indexed",
      "reviewStatus": "automated-review",
      "pagePath": "/finance-skills-hub/skills/anthropics/financial-services/teaser",
      "currentSourceUrl": "https://github.com/anthropics/financial-services/tree/main/plugins/vertical-plugins/investment-banking/skills/teaser",
      "tags": [
        "teaser",
        "blind-teaser",
        "anonymous-profile",
        "sell-side-ma",
        "investment-banking"
      ],
      "tasks": [
        "teaser",
        "excel-financial-modeling"
      ],
      "domains": [
        "fundamental-analysis"
      ],
      "assetClasses": [
        "public-equities"
      ],
      "markets": [
        "global-public-markets"
      ],
      "dataProviders": [
        "user-provided-data"
      ],
      "agents": [
        "Claude Code",
        "Claude Cowork"
      ],
      "repository": "anthropics/financial-services",
      "license": "Apache-2.0",
      "apiKey": "no",
      "permissions": [
        "filesystemWrite"
      ],
      "snapshot": {
        "assessedAt": "2026-07-29T07:31:00Z",
        "qualityScore": 65,
        "riskLevel": "medium",
        "auditConclusion": "needs-review"
      }
    }
  ]
}