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

No annotations exist, so the description carries the full behavioral burden. It discloses what categories of data come back (useful), but says nothing about cost, rate limits, per-domain query expense, failure behavior for invalid domains, or whether 'verified' means SMTP or MX-level checks. For an enrichment tool that likely incurs per-call cost, these omissions are significant.

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?

A single front-loaded sentence with no filler; the output categories are listed efficiently. It is lean, though the brevity leaves the gaps noted above rather than being wasteful.

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?

With no annotations and no output schema, the description must explain both behavior and return shape. It enumerates return categories but not their structure, and omits any mention of the maxItems parameter or operational constraints, leaving the definition incomplete for a two-parameter enrichment 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?

With only 50% schema coverage, the description does not compensate: 'domains' is documented in the schema with an example, but 'maxItems' (default 10) is undocumented in both schema and description. There is also no hint about batching behavior or whether the cap applies per call or per domain.

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 ('Extract') and names the resource ('company domains') plus the concrete payloads returned (verified B2B emails, social links, MX provider, tech stack). This makes the tool distinguishable from fetch_ats_career_jobs and find_b2b_company_executive_leads, though the overlap with verify_bulk_emails_mx ('verified ... emails') is not explicitly addressed.

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?

There is no when-to-use or when-not-to-use guidance, no mention of the sibling verify_bulk_emails_mx as an alternative for email-only verification, and no prerequisites. Usage must be inferred entirely from the verb and the listed outputs.

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?

No annotations are supplied, so the description carries the full disclosure burden, yet it only states the source providers and that listings are 'active'. It says nothing about whether these are public unauthenticated endpoints, rate limits, whether results are merged across boards or grouped per board, ordering, or truncation behavior.

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?

A single front-loaded sentence with no filler, and the provider list is useful scoping information. It is efficient, though its brevity contributes to the gaps noted in other dimensions rather than being a structural flaw.

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 three-parameter tool with no annotations, no output schema, and low schema coverage, one sentence is not enough. An agent still lacks the meaning of two parameters and any sense of return shape, result grouping, or limits.

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 33%: only 'boards' is documented (with a useful example format), while 'keyword' and 'maxItems' have no schema descriptions at all. The tool description does not compensate by explaining that keyword filters titles/listings or that maxItems caps results, leaving two of three parameters semantically opaque.

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') and resource ('active job listings') and names the three supported ATS providers (Greenhouse, Lever, Ashby). It is clearly distinguishable from the sibling tools, which cover domain enrichment and email verification, though it does not explicitly contrast itself with any alternative.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives or when not to use this tool. The agent must infer that it is for pulling job postings from public ATS boards, and nothing tells it how this relates to a keyword search versus a board sweep.

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?

No annotations are supplied, so the description carries the full burden. It discloses that leads are MX-verified, which is useful, but it does not explain accuracy, whether emails are inferred guesses, cost/rate limits, permissions, or what the response contains.

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, front-loaded sentence with no filler. It is efficiently written, though its brevity leaves significant gaps that are better captured under contextual completeness.

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?

This is a complex lead-generation tool with inference and verification behavior, yet it has no annotations, no output schema, and 0% schema description coverage. The description is too sparse to tell an agent how many leads are returned, how patterns are inferred, or what the output looks like.

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 0%, so the description must compensate. It implies that company domains are the input, but it says nothing about the companies array structure, the optional companyName field, or the maxItems parameter and its default.

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 names specific actions and a resource: infer email patterns and generate MX-verified executive email leads from company domains. It is clear what the tool does, but it does not explicitly differentiate itself from siblings like enrich_b2b_domain or verify_bulk_emails_mx.

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?

There is no explicit guidance on when to use this tool versus alternatives such as enrich_b2b_domain or verify_bulk_emails_mx. The phrase 'from company domains' implies inputs, but no prerequisites, exclusions, or alternative-selection criteria are provided.

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?

With no annotations, the description carries the full behavioral burden; it does disclose the specific verification checks performed, which is useful context beyond the schema. However, it does not explain whether the tool makes network/DNS calls, whether it is read-only, how failures are reported, or what the response contains, leaving meaningful gaps.

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 front-loaded sentence with no wasted wording. Its brevity is appropriate, though the same sentence could have carried a bit more operational detail without becoming bloated.

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?

There is no output schema, so the description should explain what verification results look like, but it does not. It also omits the maxItems parameter behavior and any limits or side effects relevant to a bulk verification tool, leaving the definition materially 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?

Schema coverage is only 50%, with 'maxItems' undocumented in both the schema and the description. The description says nothing about batch limits, default maximum of 25, or how the 'emails' array is processed, so it fails to compensate for the coverage gap.

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 states a specific verb and resource: 'Verify email addresses,' and enumerates the verification techniques used (RFC syntax, DNS MX, disposable domain detection, role-account scoring). This is clear enough for an agent to understand the tool's function, though it does not explicitly differentiate it from sibling tools.

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 offers no when-to-use guidance, no alternatives, and no exclusions. An agent must infer from the verb alone that this is for validating a list of email addresses rather than, for example, enriching or searching them.

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