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DealAnalyzer — full deal underwriting in one call

dealanalyzer_analyze
Idempotent

DealAnalyzer (x402-paid, $2.00): the flagship. Deterministic full deal underwrite in a single call — DCF valuation (EV, equity value, implied share price), fund returns (IRR/MOIC), and the LP/GP distribution waterfall, plus sensitivity. Combines what CashflowLens + WaterfallLens do, cross-checked.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dcfYesRequired. DCF valuation inputs.
payerNoOptional wallet/account identifier; stored only as a hash
apiKeyNoFree-tier / plan API key (hp_free_… or a pass key). Forwarded as X-API-Key so paid tools serve from your monthly quota with NO x402 wallet. Get a free key (250 calls/mo) at https://hermesplant.com/pricing.
channelNoDiscovery channel or source tag
returnsNoOptional fund/deal return inputs (IRR, MOIC, NPV).
campaignNoCampaign tag for downstream telemetry
xPaymentNoRaw X-PAYMENT proof from an x402-compatible wallet/client
actorTypeNoCaller type for analytics: agent, human, synthetic, system, or unknown
syntheticNoMark this paid retry as an internal test/probe for analytics exclusion
waterfallNoOptional LP/GP distribution waterfall inputs.
paymentSignatureNox402 payment proof to forward as PAYMENT-SIGNATURE and X-PAYMENT on retry
paymentIdentifierNoOptional x402 payment identifier for idempotency/retry correlation

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesTrue when the upstream storefront call returned a 2xx response
httpStatusYesUpstream HTTP status code
paymentRequiredNoTrue when the response is an x402 HTTP 402 payment challenge

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true and destructiveHint=false. The description adds meaningful context: it's x402-paid ($2.00), deterministic (reinforcing idempotency), and cross-checks results by combining two lenses. This goes beyond the annotations without contradicting them.

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

Conciseness5/5

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

The description is two sentences, front-loading the tool's identity and payment status, then listing concrete capabilities. No fluff or redundancy; it is compact yet information-dense, a model of concise documentation.

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 complex tool with 12 parameters and nested objects, the description provides a solid overview of what it computes and highlights cross-checking as a value-add. An output schema exists, so return details are not needed. Minor gap: 'sensitivity' is mentioned without explanation, but the schema likely covers it.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description does not add parameter-specific meanings beyond what the schema already provides, though it does tie the main input objects (dcf, returns, waterfall) to their output categories. The schema handles parameter semantics adequately.

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

Purpose5/5

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

The description clearly states the tool performs a full deal underwrite in a single call, listing specific outputs: DCF valuation, fund returns, and LP/GP distribution waterfall. It explicitly distinguishes itself from siblings by noting it combines CashflowLens + WaterfallLens, making its purpose and differentiation unambiguous.

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

Usage Guidelines4/5

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

The description gives clear context that this is the flagship, one-call tool for complete underwriting, and implies alternatives (CashflowLens, WaterfallLens) by saying it combines them. However, it does not explicitly state when not to use it or directly recommend alternatives for narrower needs.

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

A3.9/5.0
Disambiguation5/5

Each tool has a clear, distinct purpose. Financial tools (bond, cashflow, deal, options, portfolio, wallet, waterfall) each target a specific analysis type, email tools are batch vs single, and e-commerce tools are separate. No two tools could be easily confused.

Naming Consistency4/5

Most tools follow a noun_verb pattern (e.g., bond_analyze, emailguard_validate), but there is some inconsistency: some use verb_noun (get_product, list_products) and brand names like cashflowlens_analyze break the pattern slightly. Overall, it is still readable and mostly predictable.

Tool Count4/5

With 19 tools spanning finance, email, security, and e-commerce, the count is slightly high but reasonable for a pay-per-use server offering diverse deterministic analytics. Each tool serves a distinct function, and the number is not overwhelming.

Completeness4/5

The set covers major financial analysis types, email validation, and basic e-commerce operations. Minor gaps (e.g., no tool for portfolio rebalancing or more advanced email features) exist, but the core advertised services are well-covered.

Resources