Alternative Asset Literacy — Advisor

Look up a financial term from the 351-term glossary spanning alternative assets, DeFi, ESG, behavioral economics, art, and gender lens investing.

{
  "type": "object",
  "properties": {
    "term": {
      "type": "string",
      "description": "The financial term to look up (e.g. 'carried interest', 'impermanent loss', 'TCFD', 'green bonds')"
    }
  },
  "required": [
    "term"
  ]
}

{
  "type": "object",
  "properties": {
    "term": {
      "type": "string",
      "description": "The matched financial term"
    },
    "category": {
      "type": "string",
      "description": "Glossary category (e.g. Alternative Assets, DeFi & Crypto, Art, ESG & Climate)"
    },
    "definition": {
      "type": "string",
      "description": "Full educational definition of the term"
    },
    "source": {
      "type": "string",
      "description": "Attribution and source URL"
    }
  },
  "required": [
    "term",
    "category",
    "definition"
  ]
}

Full-text search across all 351 financial terms and definitions — alternative assets, DeFi, behavioral economics, art, ESG, and gender lens investing.

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Keyword or phrase to search across term names and definitions (e.g. 'carbon credit', 'liquidity pool', 'loss aversion')"
    },
    "limit": {
      "type": "number",
      "description": "Max results to return (default 10, max 50)"
    }
  },
  "required": [
    "query"
  ]
}

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The search query"
    },
    "total_matches": {
      "type": "integer",
      "description": "Total number of matching terms found"
    },
    "terms": {
      "type": "array",
      "description": "Matching terms sorted by relevance",
      "items": {
        "type": "object",
        "properties": {
          "term": {
            "type": "string"
          },
          "definition": {
            "type": "string"
          },
          "category": {
            "type": "string"
          }
        },
        "required": [
          "term",
          "definition",
          "category"
        ]
      }
    },
    "glossary_url": {
      "type": "string",
      "description": "URL to full glossary"
    }
  },
  "required": [
    "query",
    "total_matches",
    "terms"
  ]
}

Browse all 351 glossary terms by category. Categories: Alternative Assets, Art, DeFi & Crypto, ESG & Climate, Behavioral Economics, Gender Lens Investing. Omit category to browse all terms.

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Category to browse — e.g. 'Art', 'DeFi & Crypto', 'ESG & Climate', 'Behavioral Economics', 'Alternative Assets', 'Gender Lens Investing'. Omit for all categories."
    },
    "limit": {
      "type": "number",
      "description": "Max terms to return (default 25, max 100)"
    }
  }
}

{
  "type": "object",
  "properties": {
    "total_terms": {
      "type": "integer",
      "description": "Total terms in the glossary"
    },
    "category_requested": {
      "type": "string",
      "description": "The category filter applied"
    },
    "terms_in_category": {
      "type": "integer",
      "description": "Number of terms matching the category"
    },
    "categories_available": {
      "type": "array",
      "description": "All available glossary categories",
      "items": {
        "type": "object",
        "properties": {
          "slug": {
            "type": "string"
          },
          "name": {
            "type": "string"
          },
          "count": {
            "type": "integer"
          }
        }
      }
    },
    "terms": {
      "type": "array",
      "description": "Terms in the requested category",
      "items": {
        "type": "object",
        "properties": {
          "term": {
            "type": "string"
          },
          "definition": {
            "type": "string"
          },
          "category": {
            "type": "string"
          }
        },
        "required": [
          "term",
          "definition",
          "category"
        ]
      }
    },
    "glossary_url": {
      "type": "string",
      "description": "URL to full glossary"
    }
  },
  "required": [
    "total_terms",
    "terms"
  ]
}

Returns institutional research papers by category — 43 papers from IMF, BIS, World Bank, FSB, UN, Federal Reserve, EU, IFC, OECD, and TCFD. The 'further research' destination other tools point to instead of an external product.

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Category: CBDC, Stablecoin, ESG, Behavioral Economics, Gender Lens, Fintech, Cross-Border Payments. Omit for all categories."
    }
  }
}

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string"
    },
    "papers": {
      "type": "array"
    },
    "all_categories": {
      "type": "object",
      "description": "Present instead of 'papers' when no category filter is given"
    }
  }
}

Batch version of client meeting prep: given a list of the day's meetings (client description + optional topic + optional time each), returns a compact prep briefing for every meeting in one call — matched topic, 2 key terms, one sourced opener fact, and a risk-alignment snapshot if a risk tolerance was mentioned. No calendar access — the advisor supplies the meeting list directly.

{
  "type": "object",
  "properties": {
    "meetings": {
      "type": "array",
      "description": "The day's meetings",
      "items": {
        "type": "object",
        "properties": {
          "client_description": {
            "type": "string",
            "description": "Client background, interests, or context for this meeting"
          },
          "topic": {
            "type": "string",
            "description": "Optional topic override (e.g. 'DeFi', 'ESG', 'art investing')"
          },
          "time": {
            "type": "string",
            "description": "Optional meeting time, for display/ordering only"
          }
        },
        "required": [
          "client_description"
        ]
      }
    }
  },
  "required": [
    "meetings"
  ]
}

{
  "type": "object",
  "properties": {
    "meeting_count": {
      "type": "integer"
    },
    "meetings": {
      "type": "array"
    }
  },
  "required": [
    "meetings"
  ]
}

For financial advisors: given a description of a client, returns a curated education bundle the advisor can share — a 3-module learning path, 3 key terms the client should know before their next meeting, a copy-paste suggested message to send the client, and toolkit highlights. Designed for the advisor → client gifting workflow. Works for HNW women, DeFi-curious clients, ESG-focused clients, art collectors, and general alternative asset education.

{
  "type": "object",
  "properties": {
    "client_description": {
      "type": "string",
      "description": "Description of the client — their background, wealth level, interests, upcoming meeting context, or knowledge gaps (e.g. 'HNW woman who just sold her biotech company, meeting with UBS next month', 'DeFi-curious client asking about yield farming', 'ESG-focused client worried about greenwashing in her portfolio')"
    },
    "topic": {
      "type": "string",
      "description": "Optional topic focus — overrides profile matching if provided (e.g. 'DeFi', 'ESG', 'art investing', 'alternative assets')"
    }
  },
  "required": [
    "client_description"
  ]
}

{
  "type": "object",
  "properties": {
    "gift_type": {
      "type": "string"
    },
    "client_profile_matched": {
      "type": "string",
      "description": "The investor profile matched to this client description"
    },
    "free_entry": {
      "type": "object",
      "description": "The free module and how to access it — no account required"
    },
    "learning_path": {
      "type": "array",
      "description": "3-module curated path with 'why this matters' for each module"
    },
    "terms_to_know_before_next_meeting": {
      "type": "array",
      "description": "3 key glossary terms the client should understand before their meeting"
    },
    "toolkit_highlights": {
      "type": "array",
      "description": "Relevant Toolkit features for this client"
    },
    "suggested_advisor_message": {
      "type": "string",
      "description": "Copy-paste message the advisor can send to the client"
    },
    "further_research": {
      "type": "string",
      "description": "Pointer to other plugin tools for deeper material — never an external product"
    }
  },
  "required": [
    "client_profile_matched",
    "free_entry",
    "learning_path",
    "suggested_advisor_message"
  ]
}

Returns the actual educational content (sections, citations, quiz preview) for one of the app's 9 live learning modules — Investing Primer, Alternative Investing, Behavioral Economics, Gender and Behavioral Investing, DeFi, Art as Investment, Climate/ESG & Real World Assets, DeFi Investing, and the Kahlo x Basquiat bonus module. Mirrors the app's own free-tier preview exactly: the Investing Primer module returns in full, every other module returns its first section(s) and first quiz in full with the remainder listed by title only. This is narrative educational content only, not priced intelligence data.

{
  "type": "object",
  "properties": {
    "module_id": {
      "type": "string",
      "description": "Module id or title (e.g. 'mod_art', 'Art as Investment', 'mod_defi_investing', 'DeFi Investing')"
    }
  },
  "required": [
    "module_id"
  ]
}

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string"
    },
    "title": {
      "type": "string"
    },
    "access_tier": {
      "type": "string",
      "description": "'full_free_module' or 'free_preview'"
    },
    "sections": {
      "type": "array"
    },
    "quizzes": {
      "type": "array"
    }
  },
  "required": [
    "id",
    "title",
    "sections"
  ]
}

Returns a short, sourced statistic about women & finance, behavioral economics, alternative investing, or the art market — e.g. for a daily fact, loading screen, or conversation starter. Each fact is attributed to its original source (McKinsey, Bloomberg, Preqin, academic research, etc.). Educational teaser content, not the priced AAL intelligence data.

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "enum": [
        "Women & Finance",
        "Behavioral Economics",
        "Alternative Investing",
        "Art Market"
      ],
      "description": "Optional category filter. Omit for any category."
    }
  }
}

{
  "type": "object",
  "properties": {
    "fact": {
      "type": "string"
    },
    "source": {
      "type": "string"
    },
    "category": {
      "type": "string"
    }
  },
  "required": [
    "fact",
    "source",
    "category"
  ]
}

The free flagship onboarding tool: a ready-to-use meeting opener combining one sourced statistic with one related glossary term and a suggested opening line — for an advisor to use in the first 60 seconds of a client call. Draws only from unconditionally free content (the fact bank and the full 351-term glossary), so there is never a 'subscribe to unlock' seam in the output — it's a complete, finished deliverable every time, not a locked preview.

{
  "type": "object",
  "properties": {
    "topic": {
      "type": "string",
      "enum": [
        "Women & Finance",
        "Behavioral Economics",
        "Alternative Investing",
        "Art Market"
      ],
      "description": "Optional topic to bias the opener toward. Omit for a surprise pick."
    }
  }
}

{
  "type": "object",
  "properties": {
    "fact": {
      "type": "object",
      "description": "The sourced statistic used"
    },
    "term": {
      "type": "object",
      "description": "The related glossary term used"
    }
  },
  "required": [
    "fact"
  ]
}

Maps a client's stated risk tolerance against the general risk characteristics of each alternative asset category (DeFi, private equity/VC, art & collectibles, ESG/climate, alternative investing/real estate) — for use alongside, never in place of, the advisor's own suitability review. Every category is always returned, each flagged with whether its general risk level aligns with what the client stated, so a mismatch is always a visible, explicit result rather than a silently omitted option. Also returns cross-cutting behavioral risk factors that apply regardless of category. This is educational risk categorization, not a recommendation or suitability determination.

{
  "type": "object",
  "properties": {
    "client_risk_tolerance": {
      "type": "string",
      "description": "The client's stated risk tolerance, in their own words or yours (e.g. 'conservative', 'moderate', 'aggressive, comfortable with volatility', 'capital preservation focused')"
    }
  },
  "required": [
    "client_risk_tolerance"
  ]
}

{
  "type": "object",
  "properties": {
    "band": {
      "type": "string",
      "description": "Classified tolerance band: conservative, moderate, aggressive, or unspecified"
    },
    "areas": {
      "type": "array",
      "description": "All investment areas, each with risk_level, key_risk_factors, liquidity_profile, further_research, and aligns_with_stated_tolerance"
    },
    "behavioral": {
      "type": "object",
      "description": "Cross-cutting behavioral risk factors that apply to every category"
    }
  },
  "required": [
    "band",
    "areas"
  ]
}

Returns asset-class-spanning advisor frameworks — due diligence checklists, red flags, risk assessment, position sizing, tax considerations, essential legal documents, advisor-team building, total-cost breakdowns, and market research databases. Optionally filter by category ('Research', 'Due Diligence', 'Professionals', 'Risk Management', 'Tax & Legal') or by asset class (e.g. 'Art', 'DeFi', 'Private Equity').

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Optional category or asset-class filter. Omit for all 12 frameworks."
    }
  }
}

{
  "type": "object",
  "properties": {
    "items": {
      "type": "array"
    }
  },
  "required": [
    "items"
  ]
}

Returns the neuroscience of investment decision-making — the prefrontal cortex, amygdala, nucleus accumbens, and anterior insula — each with its investing relevance, how it gets 'hijacked' into bad decisions, and concrete navigation strategies. Useful for explaining WHY a bias happens, not just naming it.

{
  "type": "object",
  "properties": {
    "region": {
      "type": "string",
      "description": "Optional region name/id filter (e.g. 'amygdala', 'prefrontal'). Omit for all 4."
    }
  }
}

{
  "type": "object",
  "properties": {
    "regions": {
      "type": "array"
    }
  },
  "required": [
    "regions"
  ]
}

Returns the app's standalone Art Learning Track — 3 tracks, 9 lessons total: Art Concepts & Practices (value, market fundamentals, evaluation), Female Artists: An Overlooked Asset Class (the historical valuation gap and market opportunity), and The Art Investor's Toolkit (research resources, due diligence, working with professionals). Distinct from the main Art as Investment module.

{
  "type": "object",
  "properties": {
    "track": {
      "type": "string",
      "description": "Optional track id/title filter (e.g. 'female-artists-track'). Omit for all 3 tracks."
    }
  }
}

{
  "type": "object",
  "properties": {
    "tracks": {
      "type": "array"
    }
  },
  "required": [
    "tracks"
  ]
}

Searches the app's curated art library — books, podcasts, and academic papers on art history, markets, and investing — sourced live from the same Notion databases the app itself reads. Filter by category ('books', 'podcasts', 'papers') and/or a free-text query against title, author, and summary.

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Optional free-text search across title/author/summary"
    },
    "category": {
      "type": "string",
      "enum": [
        "books",
        "podcasts",
        "papers"
      ],
      "description": "Optional category filter. Omit for all."
    }
  }
}

{
  "type": "object",
  "properties": {
    "results": {
      "type": "array"
    },
    "total": {
      "type": "integer"
    }
  },
  "required": [
    "results"
  ]
}

Returns the app's curated reading list spanning behavioral economics, venture capital, economic history, and policy — each with author, year, summary, and an Apple Books link.

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "enum": [
        "Behavioral Economics",
        "Venture Capital",
        "Economic History",
        "Policy"
      ],
      "description": "Optional category filter."
    }
  }
}

{
  "type": "object",
  "properties": {
    "items": {
      "type": "array"
    }
  },
  "required": [
    "items"
  ]
}

Returns the app's 'Questions for Your Financial Advisor' question sets — 53 questions across 7 categories (DeFi/crypto, ESG/climate, alternative investing, art, behavioral finance, gender-lens investing, and general fiduciary/planning basics). Each question includes signs of an inadequate answer, signs of a competent answer, and why it matters — written from the client's side, but directly usable by an advisor prepping for exactly the questions a sophisticated client might ask. Use it to self-check fluency before a meeting, or to anticipate pushback on a specific topic.

{
  "type": "object",
  "properties": {
    "topic": {
      "type": "string",
      "description": "Optional topic filter: 'defi', 'esg', 'alt', 'art', 'behavioral', 'gender', or 'general' — or a free-text match against the set/category titles. Omit for all 7 sets."
    }
  }
}

{
  "type": "object",
  "properties": {
    "sets": {
      "type": "array"
    }
  },
  "required": [
    "sets"
  ]
}

Returns two distinct kinds of disclosure, plus the accredited investor definition and risk disclosure. 'regulatory' is for the advisor's own reading/records — what this plugin's content legally is/isn't. 'client_facing' is separate, deliberately un-branded boilerplate meant to be appended to any message the advisor actually sends a client (gift_bundle's suggested_advisor_message, post_meeting_followup's client_followup_message, or a compliance_scan-flagged draft) — never send 'regulatory' to a client, since it names this plugin's own company and a client has no relationship with it.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "regulatory": {
      "type": "string"
    },
    "client_facing": {
      "type": "string"
    },
    "accredited_investor": {
      "type": "string"
    },
    "risk": {
      "type": "string"
    }
  },
  "required": [
    "regulatory",
    "client_facing",
    "accredited_investor",
    "risk"
  ]
}

Complements data connectors that surface a client's actual holdings (e.g. iCapital's NAV/commitments, Addepar's portfolio data) but never explain what the holding IS. Given an asset type or structure label, returns a plain-language definition, the specific cognitive bias most likely to distort how a client perceives this asset class (from the investing brain map), a matching due-diligence framework reference, and one non-suitability-asserting talking point for the meeting.

{
  "type": "object",
  "properties": {
    "holding_type": {
      "type": "string",
      "description": "The asset type or structure, e.g. 'private equity fund', 'DeFi position', 'hedge fund', 'art fund', 'ESG fund'"
    },
    "client_risk_tolerance": {
      "type": "string",
      "description": "Optional, for context only — this tool does not make a suitability determination"
    }
  },
  "required": [
    "holding_type"
  ]
}

{
  "type": "object",
  "properties": {
    "plain_language_terms": {
      "type": "array"
    },
    "behavioral_note": {
      "type": "object"
    },
    "due_diligence_reference": {
      "type": "object"
    },
    "suggested_talking_point": {
      "type": "string"
    }
  },
  "required": [
    "plain_language_terms"
  ]
}

Complements meeting-intelligence tools (e.g. Zocks, Wealthbox) that capture WHAT was discussed but don't generate client-facing educational content. Given a description of the topics discussed, returns three things: a private coaching note for the advisor (which cognitive bias the client's language suggests, and how to navigate it — never sent to the client), a separate ready-to-send client follow-up message with a term, a sourced fact, and a suggested next module, and a pre-send compliance self-check run automatically against that message (same pattern scan as advisor.compliance_scan) so a flag surfaces before you have to think to ask for one.

{
  "type": "object",
  "properties": {
    "topics_discussed": {
      "type": "string",
      "description": "Free-text description of what came up in the meeting, in the advisor's own words"
    },
    "client_description": {
      "type": "string",
      "description": "Optional client context"
    }
  },
  "required": [
    "topics_discussed"
  ]
}

{
  "type": "object",
  "properties": {
    "advisor_coaching_note": {
      "type": "object"
    },
    "client_followup_message": {
      "type": "string"
    },
    "compliance_self_check": {
      "type": "object"
    },
    "suggested_next_module": {
      "type": "object"
    }
  },
  "required": [
    "client_followup_message",
    "compliance_self_check"
  ]
}

Complements Anthropic's general AI-policy compliance skill with a narrower check scoped specifically to alternative-asset client communications, using the same suitability-neutral and anti-anecdotal rules this plugin enforces on its own output: anecdotal/FOMO framing, suitability-assertion language, and missing accredited-investor/risk disclosure when the draft discusses PE, VC, hedge funds, DeFi, or art funds. Returns flagged passages with severity and a concrete suggested fix — for the missing-disclosure case, pointing to disclosures.get for the exact language to insert.

{
  "type": "object",
  "properties": {
    "draft_text": {
      "type": "string",
      "description": "The advisor's draft client communication to check"
    }
  },
  "required": [
    "draft_text"
  ]
}

{
  "type": "object",
  "properties": {
    "flags": {
      "type": "array"
    },
    "clean": {
      "type": "boolean"
    }
  },
  "required": [
    "flags",
    "clean"
  ]
}

A real computation, not templated text: models what a multi-year program of private-fund commitments (PE, VC, private credit, etc.) actually does to a client's cash flow over its life — capital calls, distributions, unrealized NAV, and the single worst year for net cash flow — using a simplified, transparent adaptation of the Takahashi-Alexander pacing framework. Every rate (contribution pace, distribution pace, fund life) is a visible input, not a black box. Runs against multiple named forward-looking growth scenarios by default (not just a historical-average assumption) so the result is shown as a range, not one confident number — set scenario to a single id to see just one. Pass annual_liquidity_budget to flag exactly which years a stated liquidity budget would be breached. This is the practice-level version of alts.illiquidity_pacing_stress_test in the retail plugin — same engine, framed for a client conversation and due-diligence file note rather than the investor's own planning.

{
  "type": "object",
  "properties": {
    "annual_commitment": {
      "type": "number",
      "description": "Dollar amount committed to new private-fund vintages each year"
    },
    "vintage_years": {
      "type": "number",
      "description": "How many consecutive years the client keeps making new commitments (default 5)"
    },
    "fund_life_years": {
      "type": "number",
      "description": "Assumed life of each fund vintage in years (default 12)"
    },
    "investment_period_years": {
      "type": "number",
      "description": "Years each vintage actively calls capital before calls stop (default 5)"
    },
    "rate_of_contribution": {
      "type": "number",
      "description": "Fraction of a vintage's uncalled capital called per year during its investment period (default 0.30)"
    },
    "rate_of_distribution": {
      "type": "number",
      "description": "Base annual distribution rate applied to NAV, back-loaded via a bow curve (default 0.20)"
    },
    "annual_liquidity_budget": {
      "type": "number",
      "description": "Optional — the client's actual annual liquidity budget for capital calls, to flag years it would be breached"
    },
    "scenario": {
      "type": "string",
      "description": "A single market-assumptions.js scenario id (historical_baseline, regime_transition, ai_productivity_acceleration, structural_stagnation) to run one scenario only — omit to run the default set and see the range"
    }
  },
  "required": [
    "annual_commitment"
  ]
}

{
  "type": "object",
  "properties": {
    "scenarios": {
      "type": "array"
    }
  },
  "required": [
    "scenarios"
  ]
}

A real Monte Carlo simulation — thousands of trials, not one deterministic projection — estimating the odds a client's savings and contributions support their stated retirement income target. Deliberately does NOT assume a fixed withdrawal rule like the '4% rule,' since that figure is itself an output of one specific historical regime, not a law; the client (or you, on their behalf) states the target income, and the tool reports the odds under each named forward-looking scenario. Runs across multiple market-assumptions.js scenarios by default so you can show a client how sensitive their plan actually is to an assumption most off-the-shelf calculators bake in silently. Pair with advisor.commitment_pacing_model to show how an alternative-asset allocation affects overall retirement success odds. This is an educational planning-conversation aid, not a substitute for your firm's own planning software or a specific recommendation.

{
  "type": "object",
  "properties": {
    "current_age": {
      "type": "number",
      "description": "The client's current age in years"
    },
    "retirement_age": {
      "type": "number",
      "description": "The age the client plans to retire and begin withdrawals"
    },
    "life_expectancy": {
      "type": "number",
      "description": "Planning horizon age (default 90)"
    },
    "current_savings": {
      "type": "number",
      "description": "Current portfolio balance in today's (real) dollars"
    },
    "annual_contribution": {
      "type": "number",
      "description": "Amount contributed per year, in today's (real) dollars, during the years between current_age and retirement_age"
    },
    "desired_annual_retirement_income": {
      "type": "number",
      "description": "The client's own target annual retirement income in today's (real) dollars — required; this tool will not assume a withdrawal rate"
    },
    "equity_weight": {
      "type": "number",
      "description": "Fraction of the portfolio in equity-like assets, 0-1 (default 0.6)"
    },
    "scenario": {
      "type": "string",
      "description": "A single scenario id to run one scenario only — omit to run the default set and see the range"
    }
  },
  "required": [
    "current_age",
    "retirement_age",
    "current_savings",
    "annual_contribution",
    "desired_annual_retirement_income"
  ]
}

{
  "type": "object",
  "properties": {
    "scenarios": {
      "type": "array"
    }
  },
  "required": [
    "scenarios"
  ]
}

Free, live lookup against the public, unauthenticated SEC Investment Adviser Public Disclosure (IAPD) and FINRA BrokerCheck registries. Useful for centers-of-influence due diligence — a referral partner, a co-sourcing firm, a peer practice — not just for clients. Returns registration scope (active/inactive, broker-dealer and/or investment-adviser) and whether the public record has any disclosure event on file, merged from both sources since each surfaces a different half of the disclosure picture. Always a starting point for due diligence, never a substitute for reading the full public record.

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The advisor or firm name to search for"
    },
    "search_type": {
      "type": "string",
      "enum": [
        "individual",
        "firm"
      ],
      "description": "Whether to search for a person or a firm"
    }
  },
  "required": [
    "query",
    "search_type"
  ]
}

{
  "type": "object",
  "properties": {
    "results": {
      "type": "array"
    }
  },
  "required": [
    "results"
  ]
}

A rigorous look at decentralized finance as an asset class — protocol-level revenue mechanics (Aave, Uniswap), real failure modes (Terra/Luna, smart contract exploits), sizing/custody/tax discipline, and an honest account of how thin the peer-reviewed DeFi literature still is relative to industry commentary.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

ESG investing evaluated on the Triple Bottom Line it's actually built on (People, Planet, Profit — Elkington, 1994), not financial return alone — why ratings diverge across providers, real fee/cost/performance data (including a genuinely improving financial-return trend since 2019), systematic greenwashing detection, and a balanced, two-sided account of what the peer-reviewed literature does and doesn't yet settle.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

The financial and legal mechanics of the art market — advisor conflicts of interest, provenance/authentication risk, primary-vs-secondary market signals, current market data (2023-2025 Artprice100 index performance), and older academic return studies (Mei & Moses; Renneboog & Spaenjers) presented as historical context, not current conditions — the two studies also reach genuinely different conclusions from each other. Distinct from art.learning_track (art history/appreciation).

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

The decision-making layer underneath every asset class — advisor self-awareness (not just client bias), structural tools that manage client behavior better than reassurance, framing effects, mental accounting, and the peer-reviewed foundations (Kahneman & Tversky, De Bondt & Thaler) that are still producing new findings. Distinct from behavioral.brain_map (neuroscience of 4 brain regions).

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

The advice gap and gender-lens investing gap treated as practice risks an advisor actively manages — auditing your own recommendation patterns, couples/continuity dynamics most practices haven't built a process for, facilitating a client's gender-lens request with real screening and due diligence, and peer-reviewed research for having the conversation credibly. Distinct from advisor.competency_check's gender-lens questions (client-side pushback) and from the retail plugin's gender-lens track (investor education) — this is specifically about what an advisor does differently in their own practice.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

A recently proposed (2026), NOT institutionally adopted alternative to GDP — measuring an economy by what it regenerates (ecological, social, and capital dimensions, treated as interdependent) rather than what it produces. Explicitly caveated throughout as an unvalidated, single-thought-leader framework, grounded against decades of real, verified 'beyond GDP' precedent (Bhutan's Gross National Happiness Index, the UN's SEEA Ecosystem Accounting standard, state-level Genuine Progress Indicators, Doughnut Economics) so the advisor can distinguish the well-established whole-systems critique from GDR's own current, unvalidated status. Relevant due-diligence context when a client raises whole-systems or beyond-GDP investment theses.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

Why VC and PE exist as their own asset classes, what verifying a client's accredited investor status actually requires of the advisor of record (506(b) self-certification vs. 506(c) mandatory verification), and how to recognize and navigate the family-office conversation — including the SEC's 2011 Family Office Rule and real 2026 SFO/MFO cost and AUM-threshold data. Written from the advisor's own practice/compliance perspective, distinct from the retail plugin's investor-facing version of this same subject.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

How to evaluate a client's roll-or-cash-out decision in a GP-led continuation fund — the specific governance questions (fairness opinion provenance, LPAC engagement) that separate a well-run transaction from a rubber stamp, the fee-clock incentive and behavioral-framing dynamics pulling on both the client and the GP, and how to frame the triple-bottom-line and gender-lens angles honestly, as hypotheses, rather than as advocacy. Written from the advisor's own practice/compliance perspective, distinct from the retail plugin's investor-facing version of this same subject.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}

How to talk about tokenized Treasuries, money-market funds, and other on-chain-wrapped assets with a client without conflating them with speculative crypto — the due-diligence questions that actually matter (structural model, redemption cap, custodian concentration), suitability framing centered on the liquidity mismatch rather than the technology, and where SEC regulatory guidance actually stands as of January 2026. Written from the advisor's own practice/compliance perspective, distinct from the retail plugin's investor-facing version of this same subject.

{
  "type": "object",
  "properties": {}
}

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    }
  },
  "required": [
    "title",
    "lessons"
  ]
}