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

The description adds value beyond annotations by listing exact output fields (email, credits remaining, total purchased, card on file, active keys) and stating that the call is free and does not consume credits. Annotations already mark it as read-only and idempotent, but the description provides concrete behavioral details.

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?

Two sentences: the first lists output fields, the second states cost. Extremely concise with no filler, front-loaded with key information. Every sentence adds value.

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?

Given no parameters and no output schema, the description provides sufficient context: it lists all returned fields, states it's free, and annotations cover safety. The tool is simple and fully described for an agent to decide when to invoke it.

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?

There are no parameters (empty schema with 100% coverage). The baseline for zero parameters is 4, and the description does not need to add parameter meaning since none exist.

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 explicitly states that the tool shows the calling key's profile with specific fields: email, credits remaining, total purchased, card status, and active API keys. This is a specific verb+resource combination that clearly distinguishes it from sibling tools like topup_credits or start_checkout.

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 mentions the tool is free and shows the key's profile, implying use for checking balance/status. While it does not explicitly state when not to use or name alternatives, the sibling list provides context for differentiation. A clear usage scenario is implied but not spelled out.

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 indicate readOnly, non-destructive, idempotent behavior. The description adds credit consumption details (Potarix Enricher API credits) and pricing, which are relevant behavioral traits not covered by annotations.

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?

Three sentences efficiently convey purpose, pricing, and credit usage. Front-loaded with key action items. No redundancy or fluff.

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?

Despite no output schema, the description adequately explains what the tool returns (website, emails, roster). The reference to /find-all docs provides an escape hatch for more details. Suitable for a combined call 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?

The schema covers all 4 parameters with descriptions. The description adds value by noting default values for dm_categories and the cap of 6 items, which are not in the schema. No contradictions or missing param info.

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 explicitly states the three functions combined (resolve website, find decision-maker emails, pull company-wide email roster) and distinguishes it from siblings like find_company_emails and find_decision_maker_email by noting it does all in one call.

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 mentions pricing model (sum of sub-calls) and references external docs, providing clear context for when to use this combined call vs individual sibling tools. It could be improved by explicitly stating when not to use it.

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 indicate read-only, idempotent, and non-destructive behavior. The description adds the important context that it uses API credits, which implies cost. No contradictions with annotations.

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, concise sentence that efficiently conveys the tool's function and a key constraint (credit usage). No unnecessary words.

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 simple tool with one input parameter, the description adequately covers the purpose and a behavioral aspect (credit usage). Annotations provide safety info. However, no output schema is provided, but the return type is likely clear from context.

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 coverage is 100% with a clear description for the domain parameter. The description does not add significant additional meaning beyond the schema, as it only reiterates the purpose without detailing parameter 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 clearly states it finds public company email contacts for a domain, with a specific verb and resource. It distinguishes from sibling tools like find_person_email and find_decision_maker_email, which target individuals.

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 mentions credit usage but does not explicitly state when to use this tool versus alternatives like find_person_email. Usage context is implied through the domain parameter and sibling tool names, but no direct guidance is given.

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, destructiveHint=false, idempotentHint=true. The description adds that it uses API credits and returns a 'likely' decision maker with 'verified' email, providing some behavioral context beyond annotations. However, it does not discuss rate limits or result reliability in depth.

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?

Single sentence that is front-loaded with the core action and resource. No unnecessary words; every part is informative.

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?

No output schema exists, yet the description only mentions 'find a likely decision maker and verified email' without specifying return format or multiple results. Adequate for a simple lookup but missing some completeness for an agent relying on this description alone.

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 coverage is 100% with descriptions for both domain and category in the schema. The description does not add any additional meaning or usage details for the parameters beyond what is already in the 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 the action (find), the resource (decision maker and verified email), and the scope (for a domain). It distinguishes itself from sibling tools like find_company_emails or find_person_email by focusing specifically on a decision maker.

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 mentions credit usage as a constraint but does not provide explicit guidance on when to use this tool versus alternatives. There is no 'when not to use' or mention of other tools.

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, destructiveHint, idempotentHint, and openWorldHint. The description adds that it uses Potarix Enricher API credits, which is useful beyond annotations, but does not disclose potential error states or rate limits.

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?

Two sentences, each purposeful: first states the tool's action and resource, second notes resource usage. No waste, front-loaded.

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 simple tool with one parameter and no output schema, the description covers the core functionality and a key behavioral detail (API credits). It is adequate but could mention expected output or error handling.

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 100% schema description coverage, the baseline is 3. The description does not add meaning beyond the schema's 'LinkedIn profile URL' description, lacking details on format or validation.

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 the tool finds a verified email from a LinkedIn profile URL, specifying the verb and resource. It distinguishes itself from siblings like find_company_emails and find_person_email by focusing on LinkedIn URLs.

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 use when a LinkedIn profile URL is available, but provides no explicit guidance on when not to use it or alternatives. The mention of API credits gives some cost context, but no exclusion criteria.

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 read-only, non-destructive, idempotent, and open-world traits. The description adds value by noting the tool uses API credits and returns a 'verified email', providing cost and reliability context beyond the annotations.

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 concise sentences with no wasted words. It delivers the core purpose and a key behavioral detail efficiently.

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 simple lookup tool with 5 optional parameters and no output schema, the description covers purpose and cost. It could mention response format or behavior when no email found, but the annotations partially cover limitations. Overall, it is adequate.

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 coverage is 100% with clear parameter descriptions. The description does not add further meaning to the parameters beyond what the schema already provides, so a baseline score of 3 is appropriate.

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 specifies the verb (Find), resource (verified email), and context (named person at company/domain). It clearly distinguishes from sibling tools like find_company_emails and find_decision_maker_email by focusing on a specific person.

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 mentions it uses API credits but provides no explicit guidance on when to use this tool versus alternatives. It implicitly indicates usage for a named person, but lacks when-not statements or direct references to siblings.

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 indicate readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds the behavioral context of credit usage, which goes beyond annotations but does not elaborate on other behaviors like error handling or return format.

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 consists of two concise sentences, each adding value: one for purpose, one for credit usage. No unnecessary words or redundancy.

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 tool is simple and the schema and annotations cover most aspects. However, there is no description of the output format (e.g., what is returned if no website found, or if multiple possible URLs). This gap makes it less complete for an agent to fully understand behavior.

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 100% schema description coverage, both parameters are already documented. The description does not provide additional semantic information beyond the schema; it merely states the tool's purpose, so it meets the baseline but adds no extra value.

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 the tool's purpose: 'Find the best website URL for a company name.' It uses a specific verb ('Find') and identifies the resource ('website URL'), distinguishing it from sibling tools like 'find_company_emails' or 'find_person_email'.

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 mentions that the tool 'Uses Potarix Enricher API credits,' implying consumption of credits but not providing explicit guidance on when to use this tool versus alternatives. No exclusions or when-not-to-use instructions are given.

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?

Description adds context beyond annotations: reveals human interaction requirement and relation to future charges. No contradiction but could mention potential failure scenarios or timeout.

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?

Two compact sentences with no redundancy. Each sentence adds essential information.

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?

Given low complexity and complete schema/annotations, description covers purpose, usage, and output handling. No output schema needed.

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 already fully describes the single parameter 'tier_key' with enum and description. Tool description adds no additional param info, so baseline 3 is appropriate.

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?

Clearly states the tool returns a Stripe Checkout URL for one-time card capture. Distinguishes from sibling 'topup_credits' which handles subsequent charges.

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?

Explicitly says to hand the URL to the user and not follow it yourself. Also explains that after checkout, 'topup_credits' calls become silent off-session charges.

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?

Description adds context beyond destructiveHint=true: it charges off-session and returns immediately on success. However, it does not mention failure scenarios (e.g., insufficient funds).

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?

Two succinct sentences with no extraneous information. Key points (buying, charging, alternative) are front-loaded and clearly separated.

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 single-parameter tool with annotations already indicating destructive nature, the description covers the core workflow, prerequisites, and behavior. No output schema is needed, and the description suffices.

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?

The input schema already covers the parameter tier_key with enum values and descriptions. The description adds no further parameter information beyond what the schema provides (100% coverage).

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 begins with 'Buy a credit pack', clearly specifying the verb 'buy' and the resource 'credit pack'. It distinguishes from sibling tools by referencing start_checkout as a prerequisite when no card is saved.

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 provides explicit guidance on when to use this tool (buying credits) and when to use an alternative (start_checkout if no card is saved), including exact tool name.

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