Global Connect Show (GCS)

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

The annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful information about what is returned (an explanation of the offering, audience description, and link collection), but gives no detail on the format or size of those links. This extra information is moderate against a low bar.

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?

It is a single compact sentence that lists the return contents early. It does not waste words, and it is appropriately brief for a static informational tool, although the parenthetical about audience could have been trimmed.

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 carries the burden of telling the agent what comes back. It names three content categories, which is decent, but 'the main links' is vague: the agent cannot know whether it gets URLs, labels, or a nested structure. A short note on the return shape would complete 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?

The tool takes zero parameters, and the schema confirms that, so there is nothing to clarify. The baseline for parameter-free tools is 4, and nothing in the description creates confusion about inputs.

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?

It states the content of the response precisely: what GCS is, its target audience (brands seeking international trust and media visibility), and its main links. This differentiates it from siblings like get_registration_form or subscribe_to_newsletter, which serve transactional purposes. The only weakness is that no explicit verb is used ('About...' rather than 'Returns an overview of...').

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?

It gives no explicit when-to-use guidance or references to alternatives. However, the orientation-style content (overview plus audience plus links) implies that it is the entry point for agents that need general context before taking action. This is usable but not explicit enough; naming a trigger such as 'Use this first when the user is new to GCS' would raise the score.

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 and openWorldHint=false, so the agent knows this is a safe, self-contained read. The description adds the useful signal that the payload is descriptive metadata (cadence, roles, interests) rather than a live data feed, but it does not note whether results are cached, static, or how current the 'recent issues' list is.

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 that lists the returned facets in a natural reading order with no filler. Every clause maps to a distinct piece of content the agent will receive.

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 parameters, no output schema, and annotations covering the safety profile, the description carries the main burden of telling the agent what comes back — and it does so by enumerating the four content areas. Only minor gaps remain, such as whether registration is required to receive the newsletter.

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 tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description correctly implies a single, unfiltered call with no arguments required.

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 specific resource (the free GCS newsletter) and enumerates the exact facets it returns: contents, cadence, recent issues, and accepted roles/interests. That is far more concrete than the bare name, though it does not explicitly distinguish this informational tool from the sibling subscribe_to_newsletter.

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 read-only, informational framing implies you call this to learn about the newsletter rather than to act on it, which indirectly separates it from subscribe_to_newsletter. However, no condition, prerequisite, or explicit alternative is stated, so the routing is left to inference.

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?

The annotations already state readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful behavioral context by enumerating what the tool returns—fields, roles, options, and an example—which is especially valuable because there is no output schema.

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 one compact sentence that front-loads the returned content and then enumerates both form variants. It is appropriately sized for a simple one-parameter lookup tool, though the noun-phrase opening is slightly less direct than an explicit verb-led 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?

For a simple read-only metadata lookup with one required enum parameter and no output schema, the description is largely complete: it identifies the available forms and the kinds of content returned. The main missing piece is explicit guidance on when to use this tool versus the sibling registration tools.

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%, and the single form parameter has an enum with descriptions for both values. The description restates the same form meanings but does not add syntax or format guidance beyond the schema, so the 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 resource clearly: the fields, roles, options, and example for one of two named GCS registration forms. It also distinguishes the two form variants by audience. However, it does not use an explicit verb such as 'returns' and does not explicitly contrast this retrieval tool with the sibling registration actions.

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 the tool is for inspecting registration form content, but it gives no explicit when-to-use guidance. It does not mention when to call this instead of siblings like register_for_gcs or register_as_media, nor does it state prerequisites or exclusions.

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 and openWorldHint=false, so safety is covered. The description adds the returned field set (dates, cities, venues, event pages), which is useful given no output schema, but it says nothing about how many events come back, the time horizon, or ordering.

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 the scope ('Upcoming') and payload fields listed; every clause carries information and 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?

For a no-param read tool with annotations and no output schema, listing the returned fields is nearly sufficient. Remaining gaps are minor: result count, how far ahead 'upcoming' reaches, and ordering are unspecified.

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 tool takes zero parameters, so the baseline is 4. Nothing in the description conflicts with the empty schema, and no parameter meaning is left ambiguous.

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?

Names the specific resource (upcoming Global Connect Show and GCSx events) and the fields returned (dates, cities, venues, event pages), so the agent knows exactly what it retrieves. It does not explicitly contrast with siblings like about_global_connect_show or register_for_gcs, so differentiation is left implicit.

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 statement of when to call this versus about_global_connect_show or register_for_gcs. 'Upcoming' implies a time scope, but there is no guidance on alternatives, prerequisites, or exclusions.

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?

Beyond the annotations, the description discloses important workflow behavior: the registrant confirms by email, and the media team later checks credentials. It also reinforces that consent must be true, adding context to the mutation. It leaves out return details and duplicate-handling specifics, but the annotations already cover idempotency and open-world 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?

Three short sentences, front-loaded with the action and audience. Every sentence contributes: scope, form reference, consent requirement, and post-submission workflow.

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 16-parameter mutation tool with no output schema, the description covers the essential context: who it is for, where to find field semantics, consent, email confirmation, and manual credential review. It could say more about what a successful call returns, but the schema and annotations carry most remaining burden.

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 the schema already documents all 16 parameters, including consent and enum-driven fields. The description adds only a pointer to get_registration_form for form-equivalent field meanings and repeats the consent requirement, which the schema already states.

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 action and resource: filling in 'Media registration' for a 'journalist or content creator', tied to 'GCS media invitations and news'. This clearly distinguishes it from the sibling general registration tool register_for_gcs and from subscription/newsletter 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?

It establishes the target audience and context for use, directs the agent to get_registration_form for field definitions, and states the consent prerequisite. It does not explicitly name register_for_gcs as the non-media alternative, but the audience-specific framing provides clear enough routing.

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?

The annotations already declare non-read-only, open-world, idempotent, non-destructive. The description adds genuinely non-obvious behavior: a double opt-in flow where GCS emails a confirmation link, registration only completes on click, and the GCS team then follows up. It does not address duplicate submissions or what happens on a second call despite idempotentHint=true.

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 short sentences, front-loaded with the action and followed by prerequisites and the post-submit flow. The opening 'Fill in Register for GCS for your user' is slightly awkward phrasing but no sentence 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?

For a 14-parameter, open-world mutation tool the description covers the essentials: prerequisites, where enum values come from, and what happens after submission. Missing only edge-case behavior (re-submission, duplicates, response shape), which is minor given strong annotations and a fully documented schema.

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%, so the baseline is 3. The description restates a few schema facts (consent: true, the role list) and adds one useful pointer — non-enumerated values like goals and events come from get_registration_form — but adds little beyond 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?

States a specific action and resource (register a user for GCS) and enumerates the registrant types it serves (brands, investors, judges/experts, distributors, analysts, associations), which implicitly separates it from register_as_media. It never names register_as_media, though, so the closest sibling is left to inference.

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?

Gives clear context: use it to register a person, field values come from get_registration_form, and consent must be true. It stops short of explicit exclusions — nothing says when to pick register_as_media or subscribe_to_newsletter instead.

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?

Goes meaningfully beyond the annotations by disclosing the double opt-in mechanic: 'GCS emails them a confirmation link; nothing is sent until they click it.' That tells the agent no subscription is live until confirmation, which matters for reporting success back to a user. It does not say what happens on duplicate submissions (despite idempotentHint=true) 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 first two sentences are tight and front-loaded with the essential consent and confirmation behavior. The third sentence then dumps two full enum lists that purely duplicate the schema, adding bulk without information — that is redundancy rather than concision.

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 an 11-parameter mutation with no output schema, the description covers the critical agent-facing concerns: consent legitimacy and the confirm-by-email flow. It leaves the return value and duplicate-subscriber behavior undocumented, a modest gap for a tool that agents will report results from.

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%, so the schema already documents all 11 parameters, including the role and interests enums. The description merely repeats those enum lists verbatim and adds only a minor hint ('marketing/brand people: brand') that is already present in the schema's role description. Baseline 3 is correct here.

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 resource: 'Sign your user up for the free Global Connect Show newsletter.' That is clearly distinguishable from the read-side siblings get_newsletter_info and about_global_connect_show, though the description never explicitly contrasts itself with register_for_gcs, which an agent might confuse for a mailing-list signup.

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?

Gives a firm eligibility rule — 'Only for people who asked for it or agreed' — which is real when-to-use guidance tied to the required consent parameter. However it names no alternatives and does not state when not to use it (e.g. existing subscribers, media contacts who should use register_as_media).

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