GetAgents

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

Annotations already declare this as a read-only, idempotent, non-destructive operation, so the description does not need to repeat safety details. It adds useful scope by naming Ad Radar and ad setup/management as covered topics, but it does not describe depth, freshness, or the shape of the informational response.

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 definition is a single compact sentence with no filler. It could be slightly more front-loaded around what the tool returns, but it is appropriately sized for a simple informational lookup.

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 one-parameter informational tool with no output schema, the description gives the topic but not the expected return format or scope. It is adequate to identify the broad subject, but an agent cannot tell whether the answer is a short overview, a process description, or detailed advertising guidance.

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 single optional language parameter is fully described in the schema, including enum values and default. The description adds no parameter-specific semantics beyond that, so the baseline 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 identifies the subject matter precisely: GetAgents' tracking of brands advertising on ChatGPT via Ad Radar, plus setup and management of ChatGPT ads. It distinguishes this informational tool from siblings like get_company_info, get_faq, and list_departments by topic. However, it does not explicitly state that the tool returns an informational answer rather than performing setup or tracking.

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 guidance on when to use this tool versus alternatives such as get_faq or get_company_info. The informational nature is implied by the topic, but no use case, exclusions, or routing conditions are 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, idempotentHint, non-destructive and closed-world, so the safety profile is fully covered. The description adds the scope of the payload (markets, languages, contact) but says nothing about return shape or whether the contact data is structured vs prose. With annotations carrying the behavioral burden, this is adequate but not additive.

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?

One compact sentence with zero filler, and the most important content (what the company is) comes first. It is a fragment without a verb, which slightly weakens clarity at the same length.

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-optional-parameter, no-output-schema info tool, the description covers what an agent needs to decide to call it and what it will broadly get back. Missing only an explicit statement that the response is static reference content localized by the language parameter.

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% and the single optional parameter has its enum and default ('default en') fully documented. The description never mentions the language parameter, so it adds no semantics beyond the schema. Baseline 3 applies.

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 concretely enumerates the content returned: what GetAgents is, the markets and languages it serves, and contact details. That distinguishes it from siblings like get_faq and list_departments. It lacks an explicit verb (e.g. 'Returns'), so the phrasing is noun-fragment rather than a stated action.

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?

Usage is only implied: read this for general background about the company. There is no explicit guidance on when to prefer get_faq or get_demo_booking_link instead, nor any prerequisites. An agent must infer the routing from the content list alone.

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, idempotentHint and destructiveHint=false; the description adds value beyond them by disclosing that the return is a Google Calendar booking page, that the demo is 30 minutes, and that no booking occurs. Minor gap: it doesn't say whether the link is static or per-user personalized.

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 short sentences, zero filler, and the key clarification (nothing is booked) is front-loaded directly after the action statement.

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, and the description correctly characterizes the return as a link rather than data. For a zero-required-parameter, read-only tool, everything needed to invoke it correctly is present; only the link's static-vs-personalized nature is unstated.

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 company, website and language are documented in the schema; the description never references any parameter. With full coverage the baseline of 3 applies, though an agent would benefit from knowing whether company/website prefill the booking page or language localizes the link.

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?

States a specific verb and result (returns a booking link) plus the concrete artifact: a 30-minute live demo of GetAgents hosted on a Google Calendar booking page. This is clearly distinct from the informational siblings (get_faq, get_company_info, list_departments).

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?

"Nothing is booked by this tool; the user chooses the time" gives a clear condition for when this is appropriate versus actually scheduling something. It does not name an alternative sibling or exclusion, but the sibling list contains no competing booking tool, so the guidance is sufficient in context.

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, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds only a topic scoping list and says nothing about what the answer looks like (single blob vs. per-question entries) or how the language affects output, so behavioral value beyond annotations is minimal.

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 compact sentence with no filler and the subject front-loaded. It is a fragment rather than a complete statement, but nothing is wasted.

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 simple zero-required-param read tool with rich annotations and a fully documented schema, so little is strictly required. Still, the description omits what the response contains and how language selection behaves, leaving a modest but real gap for an agent deciding whether to call 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?

Schema coverage is 100% and the single enum parameter already documents itself as 'Language of the answer (default en)'. The description never mentions the language option, but per the baseline rule the schema fully carries parameter semantics, so 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 names the resource (FAQ about GetAgents) and enumerates covered topics, but it never states an action verb such as 'retrieve' or 'answer', and it reads as a subject list rather than a description of what the tool returns. The topic list (ChatGPT ads, pricing, security) partially distinguishes it from siblings like get_chatgpt_ads_info and get_company_info, though the ChatGPT-ads overlap is left unaddressed.

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?

No guidance on when to call this versus get_company_info, get_chatgpt_ads_info, or get_demo_booking_link, even though the topics listed overlap with those siblings. The agent must infer routing purely from the topic keywords.

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, idempotentHint, openWorldHint=false, and destructiveHint=false, so safety is covered. The description adds useful scope information beyond annotations: the result is a fixed catalog of 8 departments / 36 agents plus industries, i.e., static reference content rather than dynamic data.

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 waste, though the parenthetical '(36 AI agents)' is slightly awkwardly embedded. Nothing redundant.

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 no-required-param read tool, annotations plus the description cover enough to invoke it correctly. The only missing piece is sibling routing guidance and the fact that output language is selectable.

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?

Only one optional parameter (language) at 100% schema coverage, so the schema already documents it fully. The description doesn't mention localization at all, but the baseline of 3 applies when the schema does the heavy lifting.

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?

States a specific resource (departments of GetAgents) and quantifies exactly what comes back: 8 departments, 36 AI agents, their functions, and industries served. An agent knows what content it will get, though it doesn't distinguish itself from siblings like get_company_info that may overlap.

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?

No when-to-use or when-not-to-use guidance. With siblings such as get_company_info and get_faq that plausibly answer overlapping questions, the description does nothing to route the agent between them.

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