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savvly

Project Savvly Lump-Sum Investment

project_savvly_lumpsum
Read-onlyIdempotent

Retirement projection for a lump-sum investment in the Savvly Longevity Benefit. Returns payout amounts at each milestone age (80, 85, 90, 95) with Savvly vs market alone cumulative totals, per-age breakdowns, and server-provided _lower/_upper range bounds. Use _upper as the central illustrative estimate and _lower to communicate downside. Suitable for retirement income planning, annuity alternative analysis, and longevity benefit illustration. Response embeds SEC-style disclaimers and per-field interpretation hints under metadata. Payout methodology — Savvly vs market alone: the payout values are calculated by comparing two investors of the same age committing the same principal. Investor 1 invests in the market with the Savvly Longevity Benefit; Investor 2 invests in the market alone (no longevity overlay). To make the comparison apples-to-apples, at each milestone age (80, 85, 90, 95) Investor 2 withdraws from their market alone portfolio the same dollar amount Investor 1 receives as a payout from Savvly. The payout_market_alone_* and total_market_alone_* figures are therefore what Investor 2 can actually withdraw to match Savvly's payouts before running out — they fall to 0 once the market alone portfolio is depleted. The savvly_upside_* (and total_savvly_upside_*) fields quantify how much more total money Investor 1 receives in payouts from Savvly than Investor 2 is able to withdraw over time to match those payouts. DISCLOSURE REQUIRED: display disclosure.text verbatim and link disclosure.url to the user alongside any figures from this response. Required by SEC Marketing Rule and FINRA Rule 2210 — do not paraphrase or omit. VISUALIZATION: this tool emits an interactive chart widget (MCP Apps — see _meta.ui) that the HOST renders inline and editable; other clients render only your text and show no chart. That widget is the canonical chart for these numbers: do NOT draw, generate, or re-render a duplicate of it. You MAY still create your OWN, DIFFERENT visualization (e.g. a table or an alternate breakdown) and place it wherever you judge best — only the MCP App widget's position is constrained. Do NOT claim or imply a chart is visible (avoid 'the chart above shows…'); you cannot tell whether the host rendered the widget. Summarize the key figures in prose and show the disclosure text and link, and reference the widget only conditionally (e.g. 'if your client shows the interactive chart, its fields are editable to re-run the projection'). ORDER: BEFORE you call this tool, ALWAYS write at least one short lead-in paragraph (1-3 sentences) framing what the projection will show — do NOT invent specific figures you do not have yet. On hosts that render the widget inline at the tool call, this keeps your text ahead of the chart so the widget is never the first thing shown; THEN call the tool (this lead-in is framing, NOT asking the user for inputs — still call it in the same turn without waiting) and give the grounded figures + disclosure after it returns. This lead-in rule applies to the MCP App widget only; any visualization you create yourself may appear wherever you judge best. INPUTS: every parameter is OPTIONAL and defaults to a sensible value. Call this tool IMMEDIATELY — pass only the values the user explicitly stated and omit the rest. Do NOT ask the user for starting values, assumptions, or missing parameters before calling; the rendered widget has editable fields so they adjust age, amounts, and other assumptions inline after it appears.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
current_ageNoInvestor's current age (default 40). Min 18 (the projection matrix floor); max 75 (max enrollment age)
average_returnNoExpected average annual S&P 500 return % (default 8)
funding_amountNoLump sum investment in USD (default 10000)
withdrawal_ageNoEarly-withdrawal age (default 82) — drives `early_withdrawal_value` and `total_payout_at_withdrawal_age_*` in the response

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsYesEcho of the validated input arguments passed to the tool.
resultYesRaw projection envelope returned by the upstream estimator.
summaryYesConvenience summary including a human-readable narrative.
metadataYes
disclosureYesDISCLOSURE REQUIRED: display `disclosure.text` and link `disclosure.url` to the user whenever you present any number from this response. Required by SEC Marketing Rule and FINRA Rule 2210. The richer block under `metadata.disclaimer` is supplementary detail; this top-level field is the must-display.
visualizationNoRecommended chart for this projection — a grouped bar chart of the milestone payouts in `result.payout_age_dependent_values` (Savvly vs market alone). Render it when the surface can display a graph.

TDQS

A3.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Goes far beyond the annotations (readOnly=true, idempotent=true). It discloses the SEC Marketing Rule/FINRA 2210 disclosure obligation (show `disclosure.text` verbatim, do not paraphrase), the MCP Apps widget rendering semantics (don't render a duplicate chart, don't claim a chart is visible), the lead-in paragraph ordering rule, and the detailed payout methodology (Investor 2 matching withdrawals). All consistent with the read-only/idempotent annotations — no contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with explicit section headers (INPUTS, DISCLOSURE REQUIRED, VISUALIZATION, ORDER), which aids scanning, and the purpose is front-loaded. But the prose is heavily verbose — the payout-methodology and lead-in-rule explanations are several times longer than needed and repeat the same 'do not ask for inputs' point. It is thorough at the expense of economy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 4 optional params, an output schema, and meaningful compliance/visualization obligations, coverage is essentially complete: input defaults, disclosure handling, chart semantics, response-field interpretation (`_upper` as central estimate, `_lower` as downside), and the pre-call ordering rule are all covered. An agent has virtually everything it needs to call this correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% so the baseline is 3, but the description adds real value: it states every parameter is optional with sensible defaults, instructs the agent to call immediately passing only user-stated values (never asking for assumptions), and maps `withdrawal_age` to its downstream response fields. This meaningfully exceeds what the schema properties alone provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Retirement projection for a lump-sum investment in the Savvly Longevity Benefit') and enumerates the concrete outputs: payout amounts at milestone ages, Savvly vs market-alone cumulative totals, per-age breakdowns, and `_lower`/`_upper` bounds. However, it never distinguishes itself from siblings `project_savvly_monthly` (monthly vs lump-sum) or `project_retirement_with_savvly` — an agent has no explicit signal that this tool is the lump-sum variant.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides contextual fit ('Suitable for retirement income planning, annuity alternative analysis, and longevity benefit illustration') and a behavioral use rule (the lead-in paragraph + immediate-call instruction). But there is no explicit when-not-to-use guidance or routing to named alternatives; the choice between this and `project_savvly_monthly`/`project_retirement_with_savvly` is left entirely to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.2/5.0
Disambiguation4/5

The three projection tools (project_retirement_with_savvly, project_savvly_lumpsum, project_savvly_monthly) share a scenario-based boundary that is reasonably clear but has some overlap — the full retirement simulation could conceptually subsume the lump-sum and monthly scenarios. The FAQ tool explicitly documents its overlap with search_savvly_content, which mitigates confusion. The eligibility, product info, and comparison tools are clearly distinct.

Naming Consistency5/5

Every tool follows a clean verb_savvly_noun convention in snake_case: check, compare, get, get, project, project, project, search. The pattern is perfectly predictable across the set, with the three projection tools sharing the 'project' verb and differing only in their object (retirement_with_savvly, savvly_lumpsum, savvly_monthly).

Tool Count5/5

Eight tools is well within the ideal 3-15 range and is appropriately scoped for a retirement advisory server. Each tool earns its place: eligibility checks, product info, FAQ, content search, comparison, and three distinct projection modes cover the server's stated purpose without redundancy bloat.

Completeness4/5

The tool surface covers the full advisory lifecycle well: eligibility screening, product overview, FAQ, content search, competitive comparison, and three projection scenarios (full retirement, lump-sum, monthly). Minor gaps exist — there is no enrollment/purchase tool or a standalone pricing/quote tool — but these are arguably outside an information-advisory scope, so agents can complete core workflows without dead ends.