Direct answer
The Investor Transition Decision Mapper organizes the educational questions that commonly arise after an inheritance, windfall, job change, retirement transition, business sale, household change or other major financial event. The tool is educational. It organizes information, exposes relationships, or performs deterministic logic from the inputs shown on the page. It does not recommend an investment, predict an outcome, or substitute for individualized financial, tax, legal, or regulatory advice.
The problem this tool solves
Major transitions combine several problem types at once: ownership, taxes, deadlines, account rules, liquidity and portfolio policy. The tool’s purpose is to separate immediate verification tasks from later investment-policy work so a reader does not treat every decision as equally urgent.
What you enter or select
Select a transition category:
- inheritance;
- windfall;
- approaching retirement;
- job change;
- business sale;
- marriage/household combination;
- divorce/separation;
- caregiving or health change;
- other major financial transition.
Then select which categories are present: retirement accounts, taxable investments, concentrated stock/business equity, real estate, debt, near-term cash needs, beneficiary/title questions, known deadline, or uncertain tax treatment.
All selections are categorical. Do not request account numbers, legal documents, exact assets, SSNs, passwords or private keys.
The interface should explain each input next to the control. If an input is optional, say what happens when it is omitted. If the tool uses a registry or external data source, show the source and freshness metadata separately from user-entered information.
What the tool returns
Return four columns:
Verify first: ownership, documents, account classification, deadlines and primary sources.
Protect liquidity: questions about taxes, near-term obligations and cash needs.
Rebuild the long-term policy: portfolio allocation, diversification, concentration and account-location topics that can usually wait until the facts are known.
Get case-specific help when needed: categories where a legal, tax or other qualified professional may be appropriate because the result depends on documents or personal facts.
Also return the relevant Investor Transition Guide and Life Stage hub.
Results should be grouped into observed/selected facts, Swoopr-calculated or matched output, and next educational steps. A result label must never look like a personalized recommendation. If the tool cannot resolve the inputs confidently, it should return an explicit “needs review” or “insufficient information” state.
Methodology
The mapper uses a rules matrix. Each selected transition maps to issue categories and source types. The result is not a recommendation; it is a checklist of educational topics.
Example rule:
inheritance + retirement_account -> account classification + beneficiary/distribution rules + IRS source + inherited-account guide
business_sale + concentrated_equity -> transaction/tax verification + liquidity reserve question + concentration/diversification education + business-sale transition guide
approaching_retirement + taxable + traditional_retirement -> income timeline + sequence risk + account tax treatment + IRS rules + retirement learning path
The tool should never calculate a tax result from these categorical inputs.
The methodology must be visible from the tool page and available without opening a modal that requires JavaScript. Deterministic rules should be documented in plain English and, where helpful, as readable pseudocode. Data-driven outputs should include the registry revision or data timestamp used.
Worked examples
Inheritance with an IRA and brokerage account: the tool puts account classification and beneficiary/distribution rules in “Verify first,” cost-basis and tax questions under source verification, and portfolio allocation under “Rebuild policy.”
Job change with a workplace plan: the tool surfaces plan documents, rollover-choice education, vesting/equity compensation if selected, liquidity/income stability and the Job Change guide.
Windfall with no deadline: the tool emphasizes inventory, tax reserve questions and a decision buffer before long-term allocation.
Examples should use hypothetical or clearly educational inputs unless the tool is explicitly designed to read public, current source data. Examples are demonstrations of method, not suggested actions.
Accessibility requirements
The tool must be usable with keyboard, screen reader, zoom, high contrast and reduced motion.
Every form control needs:
- a persistent programmatic label;
- units where relevant;
- inline help that does not depend on hover;
- errors associated with the field;
- a clear reset path.
Results must be announced appropriately without forcing focus unexpectedly. If the tool uses cards, a graph, chips or color-coded categories, the same information must be available in text. Do not use color as the only indicator of category, severity or status.
The tool should remain understandable if charts fail to load. Tables should use real table semantics. Controls that behave like buttons must be real buttons.
Privacy and data handling
Prefer browser-local computation for this tool when practical. Do not request account credentials, passwords, private keys, seed phrases, brokerage tokens or other secrets.
If a backend lookup is required, transmit only the information necessary for that lookup. Do not persist user inputs unless the product explicitly provides a save function and explains the storage behavior.
Limitations
The mapper cannot determine legal ownership, tax liability, beneficiary rights, eligibility, plan rules or suitability. It cannot read court orders, trusts, beneficiary forms or plan documents. Its output is a study and verification checklist only.
A useful limitation statement explains what the tool does not know. Avoid generic disclaimers that hide the actual uncertainty.
Interlinking plan
Link to Investor Life Stages, Investor Transition Guides, Investment Accounts, Investment Taxes, Portfolio Construction, Retirement Investing, Primary Financial Sources, and the relevant transition-specific guide.
Each internal link should represent a typed relationship: EXPLAINS, IMPLEMENTS, REQUIRES_KNOWLEDGE_OF, SUPPORTED_BY, COMPARES_WITH, NEXT_TOPIC, or another documented predicate. Do not create a block of loosely related links for SEO.
Structured data and graph identity
Create one stable PublicTool entity ID and one page resource.
The page should be ABOUT the tool. The tool should connect to every concept it implements or explains. If a methodology page exists, use EXPLAINED_BY or the equivalent Swoopr predicate.
Do not expose backend function names as separate public tools.
QA and validation
Before release, test:
- empty and incomplete input;
- boundary cases;
- invalid combinations;
- keyboard-only operation;
- screen-reader labels and live-region behavior;
- browser zoom at 200% and 400%;
- no-JavaScript fallback content;
- deterministic repeatability;
- registry/data-source freshness;
- internal-link resolution.
Automated tests should compare known fixtures with expected output. Any rules stored in code and copy must be generated from one source or validated against each other so the methodology cannot drift from the implementation.
Design deep dive 1: Urgency classification
The mapper should classify educational questions by whether they are potentially time-sensitive, structurally important but deferrable, or part of the later investment-policy rebuild. This is not a legal deadline engine.
Implementation exercise: For inheritance, job change and business sale fixtures, check that account/title/deadline questions appear before portfolio-allocation questions.
Release check: The tool must state that actual legal or tax deadlines require source or professional verification.
This design note belongs in the public methodology because it explains how the tool avoids a specific failure mode. The interface copy can be shorter, but the underlying behavior should remain testable. Where the behavior depends on registry data, include the registry revision in the diagnostic output so a stale configuration can be distinguished from a logic defect.
Design deep dive 2: Sensitive-data boundary
Transition tools can tempt users to enter documents, account numbers or family details. The component should deliberately use categorical inputs and reject pasted secrets.
Implementation exercise: Test strings resembling account numbers, SSNs, seed phrases and private keys if a free-text notes field exists; preferably avoid such a field entirely.
Release check: The tool should solve the routing problem without collecting sensitive information.
This design note belongs in the public methodology because it explains how the tool avoids a specific failure mode. The interface copy can be shorter, but the underlying behavior should remain testable. Where the behavior depends on registry data, include the registry revision in the diagnostic output so a stale configuration can be distinguished from a logic defect.
Design deep dive 3: Primary-source handoff
Each transition category should map to source classes. Retirement-account rules can route to IRS resources; public-company equity can route to SEC/issuer sources; plan-specific decisions should route to plan documents.
Implementation exercise: Review every source relationship in the rules file and validate approved domains.
Release check: A source is shown because it establishes a fact, not because it endorses Swoopr.
This design note belongs in the public methodology because it explains how the tool avoids a specific failure mode. The interface copy can be shorter, but the underlying behavior should remain testable. Where the behavior depends on registry data, include the registry revision in the diagnostic output so a stale configuration can be distinguished from a logic defect.
Design deep dive 4: Reversible versus irreversible
One of the tool’s most useful outputs is a distinction between decisions that can wait and decisions that can create hard-to-reverse consequences.
Implementation exercise: Design examples where “invest the cash” is deliberately placed after “verify tax/ownership/deadline facts.”
Release check: The output should slow down irreversible mistakes without telling the user what asset allocation to choose.
This design note belongs in the public methodology because it explains how the tool avoids a specific failure mode. The interface copy can be shorter, but the underlying behavior should remain testable. Where the behavior depends on registry data, include the registry revision in the diagnostic output so a stale configuration can be distinguished from a logic defect.
Design deep dive 5: Exportable checklist
Allow a user to export the educational checklist as text or Markdown without exporting sensitive inputs. The export should include the selected transition, issue categories, source links and next learning pages.
Implementation exercise: Verify that exports contain no hidden analytics identifiers or secrets.
Release check: The export should be readable without the Swoopr interface.
This design note belongs in the public methodology because it explains how the tool avoids a specific failure mode. The interface copy can be shorter, but the underlying behavior should remain testable. Where the behavior depends on registry data, include the registry revision in the diagnostic output so a stale configuration can be distinguished from a logic defect.
Additional test scenario: Primary-source handoff
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.
Additional test scenario: Sensitive-data boundary
Create a fixture that deliberately violates one assumption of the tool, run it through the core logic, and record the expected safe failure state. The user-facing result should explain what could not be resolved without inventing missing information. The diagnostic output should identify the input category, registry revision and rule that caused the stop.
Then repeat the fixture with the missing information supplied from a reviewed registry entry. The result should become deterministic without changing any unrelated output. This paired test demonstrates that the tool is driven by explicit evidence rather than hidden scoring or broad text generation.
Document the scenario in the component test suite and link the relevant methodology section from the test name. That keeps implementation, public explanation and QA synchronized.