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Hermes Plant — Agent Commerce Assurance

by io.github.JesseGdotIO

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 cover idempotent and non-destructive behavior. The description adds useful context: 'Deterministic', 'x402-paid, $2.00', and 'cross-checked', which inform the agent about consistency, cost, and validation. It does not contradict annotations, and the added behavioral details go beyond what annotations provide.

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-loaded with the tool name and price, and every clause adds essential information. No redundant wording or fluff.

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?

Given the tool's complexity (12 params, nested objects), the description covers the core purpose, composition, and pricing. With output schema present, return values need not be explained. It lacks explicit error/rate-limit context, but the description is complete enough for selection and invocation.

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 every parameter already has a description. The tool description adds high-level grouping (DCF, returns, waterfall) but no additional parameter-specific detail. Baseline 3 is appropriate since the schema carries the parameter load.

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's function: 'full deal underwrite in a single call' with specific outputs (DCF valuation, fund returns, LP/GP waterfall, sensitivity). It distinguishes from siblings by explicitly naming CashflowLens and WaterfallLens as components it combines, making its unique value obvious.

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 signals when to use this tool by positioning it as the 'flagship' that combines CashflowLens + WaterfallLens, implying it is preferred for comprehensive underwriting. However, it does not explicitly state when to use the individual lens tools instead (e.g., for focused analysis), so exclusions are implied rather than stated.

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

A3.6/5.0
Disambiguation4/5

Most tools have clearly distinct purposes. Some overlap exists (e.g., dealanalyzer_analyze combines CashflowLens and WaterfallLens; action_safety_run includes DestructGuard evidence), but descriptions explicitly clarify scope so an agent can choose correctly.

Naming Consistency2/5

Naming patterns are mixed: some verbs precede nouns (get_product, purchase_with_x402), others follow nouns (bond_analyze, portfolioguard_score), and some are multi-word (action_safety_quick_gate). This inconsistency makes tool selection less predictable.

Tool Count3/5

At 25 tools, the server is at the heavy end and spans diverse subdomains (safety, payments, financial analytics, storefront). While each tool serves a purpose, the broad scope makes it feel overloaded for a single server.

Completeness3/5

Core assurance workflows (safety, payment, verification) are covered, but gaps exist: no refund/cancellation tools, no attestation lookup, and no way to retrieve 30-day action-safety status records. Financial analytics also have limited coverage (no equities).

Resources