Hermes Plant

EmailGuard — email validation

emailguard_validate

Idempotent

EmailGuard (x402-paid, $0.02): deterministic email/contact quality scorer — validity, deliverability score, disposable/role/free classification, typo suggestion. Pure function, no DNS.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	No	Optional contact name associated with the email
`email`	Yes	Email address to validate
`payer`	No	Optional wallet/account identifier; stored only as a hash
`apiKey`	No	Free-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.
`domain`	No	Optional explicit domain hint (usually derived from email)
`channel`	No	Discovery channel or source tag
`campaign`	No	Campaign tag for downstream telemetry
`xPayment`	No	Raw X-PAYMENT proof from an x402-compatible wallet/client
`actorType`	No	Caller type for analytics: agent, human, synthetic, system, or unknown
`mxPresent`	No	Caller-supplied MX hint
`synthetic`	No	Mark this paid retry as an internal test/probe for analytics exclusion
`paymentSignature`	No	x402 payment proof to forward as PAYMENT-SIGNATURE and X-PAYMENT on retry
`paymentIdentifier`	No	Optional x402 payment identifier for idempotency/retry correlation

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	True when the upstream storefront call returned a 2xx response
`httpStatus`	Yes	Upstream HTTP status code
`paymentRequired`	No	True when the response is an x402 HTTP 402 payment challenge

TDQS

A3.6/5.0

Behavior4/5

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

The description adds meaningful behavioral context beyond annotations: it is a pure function with no DNS, costs $0.02 via x402, and mentions how API keys forward payments. It does not contradict the readOnlyHint=false annotation because the payment mechanism is a side effect. It does not fully detail all side effects, but the key ones are disclosed.

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?

Two crisp sentences. The first front-loads the tool's purpose and cost, and the second adds a key behavioral detail. Every word earns its place.

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?

With 13 parameters, a rich output schema, and annotations, the description covers the essential behavioral and functional aspects. It mentions cost, determinism, and the pure function nature. It does not mention the batch sibling or alternative usage scenarios, which would improve completeness but is not strictly required given the schema and output schema.

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 details beyond the schema, but it does reinforce the purpose of the email parameter via the overall use case. No additional semantic value is provided.

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?

The description clearly identifies the tool as a deterministic email/contact quality scorer with specific outputs (validity, deliverability score, disposable/role/free classification, typo suggestion). It distinguishes itself from the batch sibling in name but does not explicitly contrast with it, which is the only gap.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives like emailguard_validate_batch. It implies use for single-email validation and notes cost and payment options, but does not state exclusions or compare to sibling tools, leaving the agent without clear selection criteria.

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

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