voiceagents

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered structurally. The description still adds genuine value with the "published only" scope and the explicit exclusion "Exam questions and answers are never returned" — a meaningful data-boundary disclosure. It stops short of describing behavior on missing inputs or error outcomes.

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, front-loaded with the action and resource, followed immediately by the data-exclusion caveat. Nothing redundant or padded.

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 read tool with full annotations and no output schema, the description adequately covers what is returned and what is deliberately withheld. The only gap is behavior for a nonexistent or unpublished slug, which an agent would want to know.

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 slug parameter already carries a pattern, length bounds, and description. The description only restates lookup-by-slug and adds the published-only filter implication, which is close to the baseline for a fully documented 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 verb and resource ("Get one published academy course by its slug") and even enumerates the payload contents (objectives, lessons, FAQ). The singular "one ... course" implicitly contrasts with the listing siblings such as list_courses, but no sibling is actually named, so it falls just 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 word "published" signals that only live courses are retrievable, which is a partial when-to-use constraint. There is no explicit guidance on when to prefer this over list_courses or a search sibling, nor what to expect for an unpublished or unknown slug.

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 readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered structurally. The description adds one genuinely new behavioral fact: only *published* vendors are returned, implying unpublished slugs are not resolvable. It does not say what happens on a miss (error vs empty).

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 tight sentence with the resource and the lookup key front-loaded; there is no filler to remove.

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 read tool with complete annotations and no output schema, the description covers purpose, key, and the published-only constraint. The only real gap is not-found/error behavior, which is a minor omission at this complexity.

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 slug parameter is fully specified with a pattern and length bounds, so the schema carries the semantics. The description adds nothing beyond 'slug' as the key, which is the baseline case.

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?

Specific verb ('Get') plus a precisely scoped resource ('one published voice AI vendor') with the lookup key named ('by its slug'). It is distinguishable from search_listings and the list_* siblings, though it never names them directly.

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 'by its slug' implies the precondition that the agent already has an exact slug, which nudges toward search_listings when it doesn't. However, no alternative is named and there is no explicit when-not guidance.

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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new information by stating the response includes the product's page and outbound link, which matters because there is no output schema. It omits not-found behavior, which keeps it below 5.

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 lookup key and the returned content are both stated in one pass.

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 read tool with full annotation coverage and complete schema documentation, this is nearly sufficient. The only real gap is what happens when the slug does not resolve, which an agent would want to know.

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 slug parameter carries its own description plus a pattern, so the schema does the heavy lifting. The description's 'by its slug' restates rather than extends that, matching the baseline 3.

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 ('Get one affiliate product') and scopes it to a single-item lookup, which implicitly contrasts with the plural sibling list_products. It does not explicitly name the alternative tool, 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?

'by its slug' implies the precondition that the caller already has a slug, which is useful context for choosing this over list_products or search_listings. However, no explicit when-to-use/when-not statement or named alternative appears.

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 establish that this is a read-only, idempotent, non-destructive, closed-world operation. The description adds useful behavioral context by specifying that the counts are limited to published vendors/places/categories and that the response includes a data freshness timestamp.

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 efficient sentence that front-loads the action and enumerates the returned values. There is no redundant or filler language.

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 zero-parameter, read-only statistics tool with rich safety annotations and no output schema, the description is complete enough: it names the counted entities and the freshness field. Nothing an agent needs to invoke it correctly is missing.

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 zero parameters, so there is nothing for the description to clarify about parameter semantics. The schema is empty and complete, matching the description's no-input nature.

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 set: it returns counts of published vendors, places, categories, and the last-change timestamp. This clearly distinguishes it from the list/search siblings in practice, though it does not explicitly name or contrast them.

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 guidance on when to use this tool versus list_categories, list_places, or search_listings. The aggregate nature implies summary/statistics use, but there are no alternatives, exclusions, or prerequisites 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 readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds that each category comes with a vendor count, which is useful return-shape context, but says nothing about ordering, pagination, or completeness of the list.

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 or redundancy. Every word earns its place.

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 must carry return information, and it only partially does: it names categories and vendor counts but not the entry fields, ordering, or whether results are paginated. Adequate to call correctly, thin for interpreting results.

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 no parameters, so the baseline is 4; there is nothing the description could add on this dimension and it correctly makes no parameter claims.

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 ('List') and resource ('categories') plus what each entry carries ('voice AI vendor counts'). It is clearly distinct from list_places and list_sources by resource noun, but never explicitly says so.

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 indication of when to use this rather than list_places, list_sources, or get_stats, and no exclusions or prerequisites. The usage context (browsing categories before picking a vendor) is left entirely 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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds two genuinely new facts beyond that: only published courses are returned, and each record includes level, length, pass mark and certificate validity. It does not mention ordering or what happens at the limit boundary, so it adds context without being rich.

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 sentence, front-loaded with the verb and scoped resource, then the returned fields. Every clause earns its place and there is no redundant restatement of the name.

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 two-parameter, zero-required read tool with complete annotations, the definition covers scope (published only) and return fields, which matters because no output schema exists. The remaining gap is result ordering and whether the 50-item cap implies truncation, which an agent might want to know before listing.

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%, with the level enum and limit bounds (1-50, default 50) fully documented in the schema. The description's mention of 'level' marginally reinforces the filter but adds no syntax, default, or pagination semantics beyond the schema, so the 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?

States a specific verb (List) and a precisely scoped resource (published academy courses), plus the fields each result carries. It is clearly distinguishable from get_course (single item) and the unrelated list_* siblings, though no sibling is named explicitly.

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: the agent can infer this is the browse-all path as opposed to get_course for a single course, and that the optional level parameter narrows results. There is no explicit 'use this when' or exclusion statement, and nothing about what to do if no courses match.

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, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds one genuinely useful behavioral nuance — results are limited to places that actually have vendors, not all geographies — but says nothing about ordering, hierarchy (are cities nested under regions?), or result volume.

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. Every word earns its place: the verb, the three geographic tiers, and the qualifying condition 'that have voice AI vendors'.

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 zero-parameter, annotation-rich lister with no output schema, the description covers what the tool returns well enough to call it. The main residual gap is whether the returned list is flat or hierarchically nested across countries/regions/cities, which matters for downstream filtering.

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 per the rubric the baseline is 4. There are no parameter semantics to compensate for, and the schema's additionalProperties: false confirms the no-argument contract.

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 pairs the verb 'List' with a precise resource ('countries, regions and cities that have voice AI vendors'), making the geographic facet nature of the tool unambiguous. It doesn't explicitly contrast itself with siblings like list_categories or list_sources, but the resource is specific enough that confusion is unlikely.

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 when-to-use statement, no mention of prerequisites or ordering relative to search_listings/get_listing. Usage is only implied: it's the natural discovery call to find a geographic filter value before searching listings. An agent must infer that role.

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, non-destructive and closed-world, so the safety profile is covered. The description's contribution beyond that is that results include product counts — useful, but no ordering, pagination, or empty-result behavior is disclosed.

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 short sentence with zero filler, and the key payload detail (counts) is front-loaded where the agent will read it.

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 zero-parameter, read-only listing tool with full annotation coverage, the description plus schema is enough to invoke it correctly. Minor gap: with no output schema, the exact return shape (field names, ordering) is only alluded to.

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 no parameters, so there is no parameter semantics to explain; the baseline for a zero-param tool 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?

States a specific verb and resource ('List the product categories') plus a distinguishing payload detail (product counts). However, it does not differentiate itself from the sibling 'list_categories', leaving an agent to guess which category lister to 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?

There is no explicit when-to-use, when-not-to-use, or alternative-tool guidance. The only implied cue is that this variant returns counts, which the agent must infer rather than being told.

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 readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is fully covered. The description adds one genuinely non-obvious data semantic — the price is a point-in-time snapshot from the day the product was checked, not a current price — but says nothing about result volume, ordering, or pagination.

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, with the core action and the most decision-relevant detail (price snapshot semantics) front-loaded ahead of the filter note.

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-optional-param, read-only list tool with full schema coverage and annotations, the description is largely sufficient and even hints at the returned fields (product + price). The one gap is the absence of any output schema combined with no note on pagination or result 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 100% and the single optional parameter carries its own type, slug pattern, and length bounds. The description only restates that the parameter filters by category, adding no syntax or behavior beyond the schema, so the 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?

States a specific verb and resource ("List the affiliate products") plus the returned payload (price as of the check date) and the filter dimension. It implicitly separates from get_product (single record) and list_categories, but never names a sibling, so the differentiation 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?

"Filter by product category" plus the optional parameter implies narrowing usage, but there is no explicit when-to-use guidance and no mention of when to prefer get_product, list_product_categories, or list_categories instead. Usage is implied rather than 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 readOnly, idempotent, non-destructive and closed-world, so the safety profile is fully covered. The description adds that each entry carries license and refresh metadata, which is useful context, but says nothing about result size, pagination, or whether the list is static.

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 phrasing 'refresh of each source' is slightly ambiguous (refresh cadence vs. last-refreshed timestamp) but costs little.

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 and no output schema, the definition's job is to tell the agent what comes back, and it does (source, license, refresh info). A word on result shape or whether entries are stable would make it fully complete.

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 no parameter semantics to explain; baseline 4 applies. The description correctly does not invent 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?

States a specific verb (list) and resource (sources of voice AI vendor data) and previews the fields returned (license, refresh). It is distinguishable from siblings like list_categories or list_places, though it never names them or draws an explicit boundary.

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: this is the tool for provenance/licensing questions. There is no explicit when-to-use, when-not-to-use, or pointer to an alternative tool for related lookups.

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 readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description's one addition is the 'published' qualifier, which usefully implies unpublished vendors are excluded from results. It says nothing about pagination, result caps, or relevance fallback behavior beyond what the schema documents.

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 twelve-word sentence, front-loaded with verb and resource, with zero redundant clauses. Nothing to trim.

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 0-required-param search endpoint with rich schema descriptions and full annotations, the description covers what the tool searches and that results are limited to published vendors. Remaining gaps (sort behavior, cursor pagination semantics) are fully handled by the schema, and no output schema exists to explain.

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 parameter contract (q matching fields, sort defaults, slug formats, cursor reuse, 400 on uncovered country) is already fully specified in the schema. The description only restates the three broad filter families and adds no syntax or precedence detail.

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 (search) and resource (published voice AI vendors) plus the match dimensions (text, place, category). It is clearly distinct from get_listing (single-record fetch) and list_places/list_categories (slug lookup) by virtue of being a multi-field search, though it never names those siblings explicitly.

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 implied: an agent can infer this is the discovery tool when it doesn't already have an ID or slug. But there is no explicit when-to-use/when-not statement, no pointer to get_listing for a known vendor, and no mention that place/category slugs must come from /places or /categories (only the schema says that).

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