此 MCP 可以做什么
Supports alternative-asset advisor education with investment calculators, retirement and commitment models, financial research, glossary content, registration checks, and compliance reviews.
功能
工具
32
工具
advisor.commitment_pacing_model
Illiquidity Stress-Test / Commitment-Pacing Model
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.
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幂等
输入模式
{'type': 'object', 'required': ['annual_commitment'], 'properties': {'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'}, '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)'}, 'annual_commitment': {'type': 'number', 'description': 'Dollar amount committed to new private-fund vintages each year'}, '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"}, 'investment_period_years': {'type': 'number', 'description': 'Years each vintage actively calls capital before calls stop (default 5)'}}}
输出模式
{'type': 'object', 'required': ['scenarios'], 'properties': {'scenarios': {'type': 'array'}}}
advisor.competency_check
Get an Advisor Competency Check
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.
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输入模式
{'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."}}}
输出模式
{'type': 'object', 'required': ['sets'], 'properties': {'sets': {'type': 'array'}}}
advisor.compliance_scan
Scan a Draft Client Communication
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.
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输入模式
{'type': 'object', 'required': ['draft_text'], 'properties': {'draft_text': {'type': 'string', 'description': "The advisor's draft client communication to check"}}}
输出模式
{'type': 'object', 'required': ['flags', 'clean'], 'properties': {'clean': {'type': 'boolean'}, 'flags': {'type': 'array'}}}
advisor.daily_prep
Prep for a Day of Client Meetings
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.
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输入模式
{'type': 'object', 'required': ['meetings'], 'properties': {'meetings': {'type': 'array', 'items': {'type': 'object', 'required': ['client_description'], 'properties': {'time': {'type': 'string', 'description': 'Optional meeting time, for display/ordering only'}, 'topic': {'type': 'string', 'description': "Optional topic override (e.g. 'DeFi', 'ESG', 'art investing')"}, 'client_description': {'type': 'string', 'description': 'Client background, interests, or context for this meeting'}}}, 'description': "The day's meetings"}}}
输出模式
{'type': 'object', 'required': ['meetings'], 'properties': {'meetings': {'type': 'array'}, 'meeting_count': {'type': 'integer'}}}
advisor.explain_holding
Explain a Client's Holding
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.
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输入模式
{'type': 'object', 'required': ['holding_type'], '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'}}}
输出模式
{'type': 'object', 'required': ['plain_language_terms'], 'properties': {'behavioral_note': {'type': 'object'}, 'plain_language_terms': {'type': 'array'}, 'due_diligence_reference': {'type': 'object'}, 'suggested_talking_point': {'type': 'string'}}}
advisor.gift_bundle
Build Advisor Client Gift Bundle
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.
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输入模式
{'type': 'object', 'required': ['client_description'], 'properties': {'topic': {'type': 'string', 'description': "Optional topic focus — overrides profile matching if provided (e.g. 'DeFi', 'ESG', 'art investing', 'alternative assets')"}, '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')"}}}
输出模式
{'type': 'object', 'required': ['client_profile_matched', 'free_entry', 'learning_path', 'suggested_advisor_message'], 'properties': {'gift_type': {'type': 'string'}, '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"}, 'further_research': {'type': 'string', 'description': 'Pointer to other plugin tools for deeper material — never an external product'}, 'toolkit_highlights': {'type': 'array', 'description': 'Relevant Toolkit features for this client'}, 'client_profile_matched': {'type': 'string', 'description': 'The investor profile matched to this client description'}, 'suggested_advisor_message': {'type': 'string', 'description': 'Copy-paste message the advisor can send to the client'}, 'terms_to_know_before_next_meeting': {'type': 'array', 'description': '3 key glossary terms the client should understand before their meeting'}}}
advisor.meeting_icebreaker
Get a Meeting Icebreaker Kit
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.
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输入模式
{'type': 'object', 'properties': {'topic': {'enum': ['Women & Finance', 'Behavioral Economics', 'Alternative Investing', 'Art Market'], 'type': 'string', 'description': 'Optional topic to bias the opener toward. Omit for a surprise pick.'}}}
输出模式
{'type': 'object', 'required': ['fact'], 'properties': {'fact': {'type': 'object', 'description': 'The sourced statistic used'}, 'term': {'type': 'object', 'description': 'The related glossary term used'}}}
advisor.post_meeting_followup
Generate a Post-Meeting Education Follow-Up
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.
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输入模式
{'type': 'object', 'required': ['topics_discussed'], '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'}}}
输出模式
{'type': 'object', 'required': ['client_followup_message', 'compliance_self_check'], 'properties': {'advisor_coaching_note': {'type': 'object'}, 'compliance_self_check': {'type': 'object'}, 'suggested_next_module': {'type': 'object'}, 'client_followup_message': {'type': 'string'}}}
advisor.registration_check
Check a Firm or Individual's Public Registration
Live lookup against the public SEC Investment Adviser Public Disclosure (IAPD) and FINRA BrokerCheck registries — no seat required. 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.
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可访问外部资源
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输入模式
{'type': 'object', 'required': ['query', 'search_type'], 'properties': {'query': {'type': 'string', 'description': 'The advisor or firm name to search for'}, 'search_type': {'enum': ['individual', 'firm'], 'type': 'string', 'description': 'Whether to search for a person or a firm'}}}
输出模式
{'type': 'object', 'required': ['results'], 'properties': {'results': {'type': 'array'}}}
advisor.retirement_monte_carlo_estimator
Retirement Cash-Flow Monte Carlo Estimator
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.
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输入模式
{'type': 'object', 'required': ['current_age', 'retirement_age', 'current_savings', 'annual_contribution', 'desired_annual_retirement_income'], 'properties': {'scenario': {'type': 'string', 'description': 'A single scenario id to run one scenario only — omit to run the default set and see the range'}, 'current_age': {'type': 'number', 'description': "The client's current age in years"}, 'equity_weight': {'type': 'number', 'description': 'Fraction of the portfolio in equity-like assets, 0-1 (default 0.6)'}, 'retirement_age': {'type': 'number', 'description': 'The age the client plans to retire and begin withdrawals'}, 'current_savings': {'type': 'number', 'description': "Current portfolio balance in today's (real) dollars"}, 'life_expectancy': {'type': 'number', 'description': 'Planning horizon age (default 90)'}, '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"}}}
输出模式
{'type': 'object', 'required': ['scenarios'], 'properties': {'scenarios': {'type': 'array'}}}
advisor.risk_conversation_guide
Get a Risk Conversation Guide
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.
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输入模式
{'type': 'object', 'required': ['client_risk_tolerance'], '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')"}}}
输出模式
{'type': 'object', 'required': ['band', 'areas'], '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'}}}
art.deep_dive_track
Art Market Deep Dive Track
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).
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
art.learning_track
Get the Art Investor Learning Track
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.
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输入模式
{'type': 'object', 'properties': {'track': {'type': 'string', 'description': "Optional track id/title filter (e.g. 'female-artists-track'). Omit for all 3 tracks."}}}
输出模式
{'type': 'object', 'required': ['tracks'], 'properties': {'tracks': {'type': 'array'}}}
art.library
Search the Art Library
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.
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输入模式
{'type': 'object', 'properties': {'query': {'type': 'string', 'description': 'Optional free-text search across title/author/summary'}, 'category': {'enum': ['books', 'podcasts', 'papers'], 'type': 'string', 'description': 'Optional category filter. Omit for all.'}}}
输出模式
{'type': 'object', 'required': ['results'], 'properties': {'total': {'type': 'integer'}, 'results': {'type': 'array'}}}
behavioral.brain_map
Get the Investing Brain Map
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.
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输入模式
{'type': 'object', 'properties': {'region': {'type': 'string', 'description': "Optional region name/id filter (e.g. 'amygdala', 'prefrontal'). Omit for all 4."}}}
输出模式
{'type': 'object', 'required': ['regions'], 'properties': {'regions': {'type': 'array'}}}
behavioral.deep_dive_track
Behavioral Economics Deep Dive Track
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).
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
defi.deep_dive_track
DeFi Deep Dive Track
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.
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
disclosures.get
Get Legal Disclosures
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.
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['regulatory', 'client_facing', 'accredited_investor', 'risk'], 'properties': {'risk': {'type': 'string'}, 'regulatory': {'type': 'string'}, 'client_facing': {'type': 'string'}, 'accredited_investor': {'type': 'string'}}}
esg.deep_dive_track
ESG Deep Dive Track
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.
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
facts.random
Get a Random Investing Fact
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.
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输入模式
{'type': 'object', 'properties': {'category': {'enum': ['Women & Finance', 'Behavioral Economics', 'Alternative Investing', 'Art Market'], 'type': 'string', 'description': 'Optional category filter. Omit for any category.'}}}
输出模式
{'type': 'object', 'required': ['fact', 'source', 'category'], 'properties': {'fact': {'type': 'string'}, 'source': {'type': 'string'}, 'category': {'type': 'string'}}}
gdr.deep_dive_track
Gross Domestic Regeneration (GDR) — An Emerging Economic Model
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.
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
gender_lens.advisor_practice_track
Gender Lens Investing — Advisor Practice Guide
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.
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
glossary.browse
Browse Glossary by Category
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.
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输入模式
{'type': 'object', 'properties': {'limit': {'type': 'number', 'description': 'Max terms to return (default 25, max 100)'}, '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."}}}
输出模式
{'type': 'object', 'required': ['total_terms', 'terms'], 'properties': {'terms': {'type': 'array', 'items': {'type': 'object', 'required': ['term', 'definition', 'category'], 'properties': {'term': {'type': 'string'}, 'category': {'type': 'string'}, 'definition': {'type': 'string'}}}, 'description': 'Terms in the requested category'}, 'total_terms': {'type': 'integer', 'description': 'Total terms in the glossary'}, 'glossary_url': {'type': 'string', 'description': 'URL to full glossary'}, 'terms_in_category': {'type': 'integer', 'description': 'Number of terms matching the category'}, 'category_requested': {'type': 'string', 'description': 'The category filter applied'}, 'categories_available': {'type': 'array', 'items': {'type': 'object', 'properties': {'name': {'type': 'string'}, 'slug': {'type': 'string'}, 'count': {'type': 'integer'}}}, 'description': 'All available glossary categories'}}}
glossary.lookup
Look Up Financial Term
Look up a financial term from the 351-term glossary spanning alternative assets, DeFi, ESG, behavioral economics, art, and gender lens investing.
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输入模式
{'type': 'object', 'required': ['term'], 'properties': {'term': {'type': 'string', 'description': "The financial term to look up (e.g. 'carried interest', 'impermanent loss', 'TCFD', 'green bonds')"}}}
输出模式
{'type': 'object', 'required': ['term', 'category', 'definition'], 'properties': {'term': {'type': 'string', 'description': 'The matched financial term'}, 'source': {'type': 'string', 'description': 'Attribution and source URL'}, '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'}}}
glossary.search
Search Financial Glossary
Full-text search across all 351 financial terms and definitions — alternative assets, DeFi, behavioral economics, art, ESG, and gender lens investing.
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输入模式
{'type': 'object', 'required': ['query'], 'properties': {'limit': {'type': 'number', 'description': 'Max results to return (default 10, max 50)'}, 'query': {'type': 'string', 'description': "Keyword or phrase to search across term names and definitions (e.g. 'carbon credit', 'liquidity pool', 'loss aversion')"}}}
输出模式
{'type': 'object', 'required': ['query', 'total_matches', 'terms'], 'properties': {'query': {'type': 'string', 'description': 'The search query'}, 'terms': {'type': 'array', 'items': {'type': 'object', 'required': ['term', 'definition', 'category'], 'properties': {'term': {'type': 'string'}, 'category': {'type': 'string'}, 'definition': {'type': 'string'}}}, 'description': 'Matching terms sorted by relevance'}, 'glossary_url': {'type': 'string', 'description': 'URL to full glossary'}, 'total_matches': {'type': 'integer', 'description': 'Total number of matching terms found'}}}
modules.get_content
Get Module Content Preview
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.
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输入模式
{'type': 'object', 'required': ['module_id'], 'properties': {'module_id': {'type': 'string', 'description': "Module id or title (e.g. 'mod_art', 'Art as Investment', 'mod_defi_investing', 'DeFi Investing')"}}}
输出模式
{'type': 'object', 'required': ['id', 'title', 'sections'], 'properties': {'id': {'type': 'string'}, 'title': {'type': 'string'}, 'quizzes': {'type': 'array'}, 'sections': {'type': 'array'}, 'access_tier': {'type': 'string', 'description': "'full_free_module' or 'free_preview'"}}}
pe_secondaries.deep_dive_track
PE/VC Secondaries & Continuation Funds — What the Advisor of Record Needs to Ask
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.
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输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
reading.list
Get the Curated Reading List
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {'category': {'enum': ['Behavioral Economics', 'Venture Capital', 'Economic History', 'Policy'], 'type': 'string', 'description': 'Optional category filter.'}}}
输出模式
{'type': 'object', 'required': ['items'], 'properties': {'items': {'type': 'array'}}}
research.papers
Get Institutional Research Papers
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {'category': {'type': 'string', 'description': 'Category: CBDC, Stablecoin, ESG, Behavioral Economics, Gender Lens, Fintech, Cross-Border Payments. Omit for all categories.'}}}
输出模式
{'type': 'object', 'properties': {'papers': {'type': 'array'}, 'category': {'type': 'string'}, 'all_categories': {'type': 'object', 'description': "Present instead of 'papers' when no category filter is given"}}}
rwa.deep_dive_track
Tokenized Real-World Assets — What the Advisor of Record Actually Needs to Know
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
toolkit.frameworks
Get a Due Diligence / Risk / Tax Framework
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').
只读
幂等
输入模式
{'type': 'object', 'properties': {'category': {'type': 'string', 'description': 'Optional category or asset-class filter. Omit for all 12 frameworks.'}}}
输出模式
{'type': 'object', 'required': ['items'], 'properties': {'items': {'type': 'array'}}}
vc_pe.deep_dive_track
Venture Capital & Private Equity — Access, Verification, and the Family Office Question
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.
只读
幂等
输入模式
{'type': 'object', 'properties': {}}
输出模式
{'type': 'object', 'required': ['title', 'lessons'], 'properties': {'title': {'type': 'string'}, 'lessons': {'type': 'array'}}}
历史
近期工具变更
已更改
rwa.deep_dive_track
2026年10月1日 02:42
已更改
pe_secondaries.deep_dive_track
2026年10月1日 02:42
已更改
vc_pe.deep_dive_track
2026年10月1日 02:42
已更改
gdr.deep_dive_track
2026年10月1日 02:42
已更改
gender_lens.advisor_practice_track
2026年10月1日 02:42
已更改
behavioral.deep_dive_track
2026年10月1日 02:42
已更改
art.deep_dive_track
2026年10月1日 02:42
已更改
esg.deep_dive_track
2026年10月1日 02:42
已更改
defi.deep_dive_track
2026年10月1日 02:42
已更改
advisor.registration_check
2026年10月1日 02:42
已更改
advisor.retirement_monte_carlo_estimator
2026年10月1日 02:42
已更改
advisor.commitment_pacing_model
2026年10月1日 02:42
已更改
advisor.compliance_scan
2026年10月1日 02:42
已更改
advisor.post_meeting_followup
2026年10月1日 02:42
已更改
advisor.explain_holding
2026年10月1日 02:42
已更改
disclosures.get
2026年10月1日 02:42
已更改
advisor.competency_check
2026年10月1日 02:42
已更改
reading.list
2026年10月1日 02:42
已更改
art.library
2026年10月1日 02:42
已更改
art.learning_track
2026年10月1日 02:42
已更改
behavioral.brain_map
2026年10月1日 02:42
已更改
toolkit.frameworks
2026年10月1日 02:42
已更改
advisor.risk_conversation_guide
2026年10月1日 02:42
已更改
advisor.meeting_icebreaker
2026年10月1日 02:42
已更改
facts.random
2026年10月1日 02:42
已更改
modules.get_content
2026年10月1日 02:42
已更改
advisor.gift_bundle
2026年10月1日 02:42
已更改
advisor.daily_prep
2026年10月1日 02:42
已更改
research.papers
2026年10月1日 02:42
已更改
advisor.registration_check
2026年9月29日 02:48
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