datingcoaches

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 The only gap is behavior for a nonexistent or unpublished slug, which an agent would want to know.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 readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so safety is covered. The description nonetheless adds a genuine behavioral constraint: only 'published' listings are retrievable, implying draft or unpublished slugs will not resolve. It stops short of stating the not-found behavior or response shape.

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 resource, scope qualifier ('published'), and lookup key all stated up front. Nothing is wasted and nothing is buried.

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-only lookup with full annotation coverage and no output schema, the description covers what matters. The minor gap is the failure mode for an unpublished or nonexistent slug, which an agent would plausibly 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?

With 100% schema description coverage, the schema already documents the slug's format, pattern, and length. The description only restates 'by its slug' and adds no syntax, format, or resolution behavior beyond the structured field, 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?

The description states a specific verb and resource ('Get one published dating coach') and narrows it to a single record fetched by slug, which is clearly distinct from the plural list siblings (list_categories, list_places, search_listings). It never names those siblings explicitly, so an agent must infer the single-vs-collection distinction rather than being told it.

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 usage condition (you already have a slug), but there is no statement of when to prefer this over search_listings or what to do when the slug is unknown. Usage is inferable but not explicit, and no exclusions 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?

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?

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds useful behavioral detail beyond that ('published' scope only, and that a last-changed timestamp is included), but says nothing about auth needs, caching, or response shape.

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 scope word ('published') and the enumeration of counted entities both earn their 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 are no parameters and no output schema, so the description must carry the return-content burden: it does name the counted entities and the freshness field. It stops short of giving field names or a date format, but for a trivial zero-argument stats endpoint this is close to 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 and the schema is empty, so there is no parameter semantics to document. Baseline 4 applies; the description correctly avoids inventing 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 (get) and resource (stats), and enumerates exactly what is counted: published dating coaches, places, categories, plus the last-changed timestamp. This is clearly distinguishable from the sibling list_* and search_* tools, which return records rather than counts.

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 description's emphasis on counts signals this is the summary/aggregate tool, so an agent can infer it shouldn't substitute for list_categories or list_places when enumerating items. However, no alternative is named and no explicit when-to-use or when-not-to-use condition 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, idempotentHint, destructiveHint=false and closed-world scope, so the safety profile is fully covered. The description contributes the one extra behavioral fact available without an output schema: what each returned item contains (a coach count per category). No pagination, ordering, or volume limits are 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 front-loaded sentence with no filler, no restatement of the title, and the most informative element (what comes back alongside each category) placed immediately.

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 parameterless read-only list tool with no output schema and comprehensive annotations, this covers the essentials: the resource enumerated and the shape of each result. Only the absence of usage routing and ordering/pagination notes keeps it short of full completeness.

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. Baseline 4 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+resource ('List categories') and adds the payload detail that each entry carries dating coach counts. That distinguishes it from the other list_* siblings (list_places, list_sources), though it never names an alternative 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?

No when-to-use, when-not-to-use, or alternative routing is provided. An agent must infer that this is the entry point for enumerating category facets rather than using get_stats or search_listings.

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 a closed world, so the safety profile is covered. The description usefully adds that results are restricted to places that actually have coaches, which is real filtering behavior beyond the annotations, but says nothing about ordering or result size.

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, no filler, and the resource and its scope are front-loaded. 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-arg, no-output-schema lookup, the description covers what is returned at a conceptual level (countries, regions, cities). It is slightly ambiguous whether the result is flat or hierarchical, but that is a minor gap against the tool's simplicity.

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 schema cannot carry any semantics and the baseline of 4 applies. There is nothing parameter-related for the description to compensate for.

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?

Clear verb+resource: lists countries, regions and cities, plus the scoping qualifier 'that have dating coaches'. It distinguishes this from sibling list tools (list_categories, list_sources) by resource, though it never names 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?

No when-to-use guidance, no prerequisites, and no reference to alternatives such as search_listings or get_listing. The zero-parameter surface limits ambiguity, but the description gives the agent nothing explicit about when this tool is the right call.

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 the safe read-only, idempotent, non-destructive, closed-world profile, so the bar is lower. The description adds genuine context beyond them by specifying the content of each entry (license and refresh information), which is useful since 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?

A single sentence with zero waste, front-loading the action and resource before the detail about entry contents. Nothing needs trimming and nothing critical is buried.

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 no output schema, the description covers purpose and return content adequately. Minor gaps remain, such as whether the list is ordered or paginated, but an agent has everything needed to call it correctly.

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 clarify; the baseline of 4 applies. No parameter-related gaps 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?

States a specific verb ('List') and resource ('sources' of the dating coach data), and adds what each entry contains (license, refresh). It is clearly distinct from the sibling enumeration tools list_categories and list_places, though it never explicitly contrasts itself with 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?

Usage is only implied: the agent can infer this is for inspecting data provenance, licensing, and refresh cadence. There is no statement of when to prefer this over get_stats or the other list_* tools, and no 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, idempotentHint, destructiveHint=false and a closed-world scope, so the safety profile is covered. The description adds only the meaningful 'published only' scope constraint; it says nothing about pagination behavior, result volume, or ordering semantics beyond what the schema states.

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 scope qualifier 'published' and the filter axes appear immediately. Nothing in it is redundant with structured fields.

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 8-parameter, paginated search with no output schema, the description is thin: it never mentions that results are paginated via cursor or what a result represents. The schema compensates for parameter detail, but the overall call context is only minimally covered.

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 all eight parameters (including the q matching behavior, slug sources, and cursor reuse rules) are already fully documented in the schema. The description's 'text, place and category' mapping adds nothing beyond that baseline.

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 a precisely scoped resource ('published dating coaches'), with the three filter axes named. It does not explicitly distinguish itself from siblings like get_listing or list_places, but the 'search published listings' framing is unambiguous.

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 choose this tool over siblings (e.g. get_listing for a single coach, list_places/list_categories for resolving slugs). The 'by text, place and category' phrase hints at supported filters but never states conditions, prerequisites, or alternatives.

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