ResultRail by LarryBuildsAI

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=true. The description adds useful context about the returned result pack contents and source attribution, exceeding the annotation bar without contradicting it. It does not mention cost implications or failure modes, but the annotations cover the safety profile adequately.

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

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

The description is a single dense sentence that packs multiple output fields without unnecessary fluff. It is front-loaded and every phrase contributes meaning, though its length makes it slightly harder to parse than a shorter structured breakdown.

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

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

For a tool with 5 parameters, a cost cap, and PII mode, the description lacks essential operational guidance. It does not explain when or why to set max_price_usdc, what required_fields controls, or how pii_mode affects results. The output schema covers return values, but the input semantics are too vague for a complex tool.

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

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

Schema description coverage is only 40% (url and domain have descriptions). The description reiterates domain/url but leaves pii_mode, max_price_usdc, and required_fields completely unexplained. It does not compensate for the low schema coverage, so the agent is left without guidance on three key parameters.

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

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

The description clearly states it fetches a public domain/homepage and returns a structured result pack with specific fields (company info, industry guess, technographics, useful paths, confidence, sources, receipt hash). This distinguishes it from sibling tools focused on URL extraction or quote data.

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

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

The description implies it is used for domain enrichment, but does not explicitly state when to use it versus extract_url_result or quote_data_result, nor does it provide exclusions or prerequisites. Clear context but no alternative comparison.

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

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds meaningful behavioral context beyond those hints: it targets only public URLs, returns a specific set of fields, and operates on a pay-per-success basis, which signals cost implications the annotations do not cover.

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

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

The description is two sentences, front-loads the action, and includes no filler. Every phrase adds useful information about the tool's behavior and design context.

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

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

The description covers the primary input, output fields, and pay-per-success framing, but it omits important context such as how the output format parameter works, what failure or pricing caveats exist, and how this tool relates to its siblings. The output schema reduces the need to enumerate return values, but usage and parameter edge cases remain incomplete.

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

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

With only 33% schema description coverage, the description needed to compensate by explaining parameters such as 'output' and 'max_price_usdc', but it does not. It lists extraction result fields rather than parameter meaning, and 'pay-per-success' only hints at the cost parameter without explaining its role or constraints.

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

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

The description uses a specific verb ('Fetch one public URL') and identifies both the resource and the return payload, making the core purpose clear. It does not explicitly differentiate from sibling tools like enrich_domain_result or quote_data_result, so it stops short of a 5.

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

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

The phrase 'Designed for pay-per-success agent extraction' implies when this tool is appropriate, but there is no explicit guidance on when to choose it over siblings or when to avoid it. Usage context is implied rather than directly stated.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the specific return payload (price, paid endpoint, success contract) and the free nature of the quote, going beyond annotation basics.

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

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

The description is extremely concise—two sentences that front-load the core purpose and immediately list return values. Every word carries weight, and there is no irrelevant filler.

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

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

The description explains the tool's purpose, return values, and free nature, which is sufficient given the rich annotations and output schema. It could have mentioned explicit alternatives or eligibility conditions, but overall it is complete for a quote tool.

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

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

Schema description coverage is 100%, so all parameters (task, input, task_type, max_price_usdc) are already well-documented. The description references max_price_usdc implicitly ('buyer's max price') but does not add significant new parameter semantics beyond schema.

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

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

The description clearly states it provides a 'Free pre-payment quote for one ResultRail public-data result,' specifying the verb 'quote' and the resource. It also lists what is returned (price, paid endpoint, success contract, coverage check), distinguishing it from sibling tools like enrich_domain_result and extract_url_result, which focus on enrichment and extraction.

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

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

The description implies usage in the pre-payment phase ('Free pre-payment quote') and distinguishes it from enrichment/extraction by its purpose. However, it does not explicitly name alternatives or state when not to use it, so it lacks explicit exclusions.

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