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

Annotations already declare this as a read-only, idempotent, non-destructive open-world operation. The description adds valuable context beyond those annotations: the data is public, parsed from Organization JSON-LD, and the organization data is global even when a locale is supplied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the purpose and return shape, then moves through args and examples efficiently. It is appropriately sized, though the line identifying it as the brief's "get_store_information" is internal meta-context that does not help an agent select or invoke the tool.

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 tool with no required parameters, full schema coverage, annotations, and an output schema, the description is complete. It covers the source, return shape, locale behavior, and example use cases, leaving no critical gap for correct invocation.

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 both parameters are already well documented in the input schema. The description adds only a small amount of meaning, mainly clarifying that locale selects the market page while the organization data itself is global; otherwise it largely echoes 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?

The description states a specific verb and resource: return Hemmiles' public company and contact information parsed from Organization JSON-LD, and it enumerates the fields returned. It is clear what the tool does, but it does not explicitly distinguish itself from sibling tools such as hemmiles_get_contact_options, which likely overlaps with the contact-points portion.

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 through example questions like "How do I contact Hemmiles?" and "Who makes Hemmiles?", which gives the agent useful triggers. However, it does not state when to prefer this tool over alternatives, especially hemmiles_get_contact_options, nor does it provide 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 readOnly/idempotent/openWorld annotations, the description discloses that it only returns official links, never performs transactions, and never submits forms. It also explains that results are assembled from Organization contact points and known pages, adding useful provenance.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and includes a useful rationale for the cart/checkout alternative. It is somewhat verbose in repeating return fields and argument details already covered by structured data.

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?

Given the rich annotations, full schema coverage, and an output schema, the description supplies everything needed: purpose, alternative context, safety behavior, parameters, and return fields. No material gap remains for an agent selecting or invoking 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 description coverage is 100%, so the schema already fully documents locale and response_format. The description repeats their meaning but adds little parameter-specific detail beyond what the schema provides.

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: returning Hemmiles' official sales/demo, contact, and support email options. It is clear what the tool does, but it does not explicitly distinguish itself from sibling tools such as hemmiles_get_company_info or hemmiles_get_policies.

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 clear usage context by positioning the tool as the legitimate alternative to cart/checkout tools that do not exist for Hemmiles. It does not, however, explain when to choose this over the many Hemmiles informational siblings.

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 cover read-only, idempotent, and open-world semantics, so the description adds context on data provenance (parsed from JSON-LD) and the return shape. It does not mention behavior when a page lacks FAQ markup, which is the one remaining disclosure gap.

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?

Purpose is front-loaded, followed by args and a return shape and example. Slight redundancy between the description's args block and the schema, but nothing is wasted 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?

With an output schema, rich annotations, and full param coverage, the description covers what an agent needs to call it. Only the empty/no-FAQ-result case is unaddressed, a minor omission given the structured richness.

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 three parameters are already documented. The description restates path and locale semantics ('market prefix for a bare path') with little that isn't in the schema, meriting 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+resource ('Return the frequently-asked-questions published on a Hemmiles page') and names the parsing source (FAQPage JSON-LD), which distinguishes it cleanly from siblings like get_page, get_pricing, and get_policies.

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 concrete usage context (pricing page carries detailed billing/user-minimum/trial FAQs) and a worked example mapping a natural question to path='pricing'. It stops short of naming alternatives or stating when to prefer get_page over this tool.

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 beyond the annotations (which already declare readOnly/idempotent/non-destructive/open-world) by documenting the error taxonomy — NOT_FOUND and DISALLOWED_PATH for robots-blocked routes like /api/ — plus the rule that locale is ignored when a full URL is passed. Minor flaw: it says 'Returns JSON' while response_format permits 'markdown', leaving the actual return shape slightly ambiguous.

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?

Front-loaded summary, then a correctly separated Args block and error-handling block — easy to scan. It loses a point for restating parameter meanings already present in the schema, which is the only real redundancy.

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?

Covers the full burden for this tool: what is fetched, how paths resolve, output shape, and failure modes with recovery paths. Since an output schema exists and 100% of parameters are schema-documented, nothing an agent needs in order to call this 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?

Schema description coverage is 100% and the descriptions already state the path-or-URL behavior, the locale-ignored-for-full-URLs rule, and the response_format enum. The Args block largely restates those facts, so the description adds little semantic value 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?

States a specific verb and resource ('Fetch a single hemmiles.com page') and immediately enumerates what comes back: title, description, headings, breadcrumbs, links, JSON-LD types, body text. It also positions itself against siblings by naming the pricing and FAQ equivalents, so an agent can distinguish it without opening another schema.

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?

Explicitly routes the agent: pricing goes to hemmiles_get_pricing, FAQs to hemmiles_get_faqs, and NOT_FOUND conditions point to hemmiles_list_pages / hemmiles_search_site for discovering valid paths. Both the when-to-use and the recovery alternatives are stated rather than implied.

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, openWorld, and non-destructive, so the safety profile is covered. The description adds genuinely new behavior: only pages that actually exist are reported, missing ones are surfaced in an 'unavailable' list, and locale lookup falls back to the global page.

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?

Front-loads the purpose and the important negative scope before the argument details. Some redundancy between the Args block and the schema, and the reference to 'the brief' is meta, but overall it is tight and scannable.

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?

Output schema exists and the description still summarizes the return shape (note, found entries with url/title/description/excerpt, unavailable list), so an agent knows exactly what to expect. Nothing about invocation or failure modes is left unclear.

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% with three enums, so the schema already fully documents topic, locale, and response_format. The description's Args block largely restates those enums and the locale fallback rule that the schema already states, adding only the 'all' default framing.

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 ('Fetch Hemmiles' publicly available policy pages') and enumerates the exact topic set, which distinguishes it from siblings like hemmiles_get_page and hemmiles_list_pages. It also routes the agent away from irrelevant policy types by declaring what does not exist.

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?

Explicitly says the e-commerce shipping and return policy tools do not apply, and names hemmiles_get_faqs as the alternative for billing, trial, and cancellation terms. That is both a when-to-use and a when-not-to-use with a named sibling.

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 cover safety (readOnly, idempotent, non-destructive), yet the description still adds real value: the upstream source is schema.org Offer markup on the public pricing page, and it explicitly scopes results to publicly displayed list price, excluding negotiated, annual-discount, and promotional pricing. That is exactly the kind of caveat an agent needs before quoting a price.

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?

Front-loaded purpose sentence, then args, return shape, example, and caveat in a predictable order. The Args block largely restates the schema enums verbatim, which is mild redundancy, but nothing is truly 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?

Even though an output schema exists, the description summarizes the return payload (url, locale, currency, plans array) and, more importantly, states the coverage limitation of the data. An agent can decide whether to call it and how to present the result without further inference.

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 both params have enums, so the baseline is 3. The description adds meaning beyond the schema: the default is the server locale, currency varies per market, and the example maps a natural-language question to a specific enum value.

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 Hemmiles subscription pricing for a market') plus the data source ('parsed from the pricing page's schema.org Offer data'). No sibling tool covers pricing, so the resource alone separates it from list_pages, list_features, get_policies, etc.

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 concrete triggering example ('How much is Hemmiles in India?' -> locale='in') and an explicit instruction ('Always pass the locale you care about'). It does not name a sibling alternative or state when-not to use it, but no sibling is a close substitute for pricing questions.

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, openWorld and non-destructive, so the safety profile is covered. The description adds real context beyond that: the underlying source (site JSON-LD), the optional URL linkage to per-feature pages, and the return shape. Remaining gaps (rate limits, freshness) are minor for a read-only listing.

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?

Front-loaded with the core purpose, then Args, Returns, and example queries in clean sections. The list of typical feature names is somewhat illustrative padding, but it does convey the domain vocabulary, so it largely earns its space.

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 only 2 optional params, an output schema present, and full annotation coverage, this is close to complete. The description reinforces the return shape and data provenance, leaving little an agent would need beyond 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 description coverage is 100%, with both parameters enum-documented and described, so the baseline is 3. The description's one-line restatement of locale ('market whose feature-page URLs to return') adds slight interpretive value but nothing the schema does not already carry.

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 gives a specific verb ('List') and resource ('Hemmiles product's capabilities / featured items'), and pins down the data source (SoftwareApplication JSON-LD feature list) with the linkage rule for dedicated pages. This is clearly distinguishable from siblings like hemmiles_list_pages or hemmiles_list_resources, which are page/resource inventories rather than the product's feature set.

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 through example user queries ('What can Hemmiles do?' / 'List Hemmiles features'), which helps an agent recognize trigger phrasing. However, there is no explicit statement about when NOT to use this tool or which sibling to prefer for adjacent queries (e.g., company info vs. features).

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 establish that this is a safe, idempotent, open-world read, so the description doesn't need to repeat that. It does add real context beyond the annotations: the data source is the sitemap, results are marketing/docs pages rather than commerce categories, and locale defaults to the server's configured market.

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?

Front-loaded with the core purpose, then args, return shape, and examples in a scannable order with no filler. It is slightly longer than strictly necessary given the schema already documents all three params, but every line carries information.

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?

The tool is simple (3 optional params, 0 required), annotations cover the safety profile, and an output schema exists, so the return-shape sentence is a bonus rather than a necessity. The one gap is that the overlap with hemmiles_list_features and hemmiles_get_page is not resolved for the agent.

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 baseline is 3, but the description adds value beyond the schema by giving example section values, explaining that 'global' corresponds to locale-less canonical pages, and showing intent-to-argument mappings in the examples.

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 public pages of hemmiles.com, grouped by section, sourced from the sitemap) and enumerates the sections returned. It also pre-empts a likely confusion by explaining that Hemmiles is field-sales SaaS, not a store, so pages are the closest thing to 'categories'.

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 examples map natural user intents to concrete argument choices ('What pages does Hemmiles have?' -> no args; 'List the feature pages' -> section='features'), which is strong guidance. However, it never mentions when to prefer siblings such as hemmiles_list_features (which overlaps with section='features'), hemmiles_get_page, or hemmiles_search_site.

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 and destructiveHint=false, so the safety profile is covered. The description adds genuinely new context: results are sitemap-derived (implying potential gaps in coverage) and it documents the return payload shape. It omits freshness/caching behavior and any rate-limit notes, keeping it short of a 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?

The description is front-loaded with purpose, then follows a predictable Args/Returns/Example structure with no filler prose. The Args block duplicates enum values already fully specified in the schema, which is some wasted space, but overall it is tight and scannable.

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-required-parameter listing tool with an output schema, the description covers purpose, scoping, defaults and an invocation example, so an agent could call it correctly. The missing piece is positioning against hemmiles_list_pages and hemmiles_search_site, which matters given nine sibling 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?

With 100% schema description coverage, the schema already documents all three enums and defaults, and the description largely restates them verbatim. The only added value is the locale parenthetical (default: server locale) and the question-to-kind example, which is marginal 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?

The first line states a specific verb and resource ('List Hemmiles resource content') and enumerates the exact sections covered: guides, blog posts, resources/docs/help hubs. It also discloses the source of truth ('as discovered from the sitemap'). It does not explicitly contrast itself with the close sibling hemmiles_list_pages, so differentiation is inferred from the section enumeration rather than stated.

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 worked example ('What guides does Hemmiles have?' -> kind='guides') gives concrete guidance on how to translate a user question into a call, and the kind filter defines the scoping choices. There is no explicit when-not-to-use guidance or pointer to hemmiles_list_pages / hemmiles_search_site for broader or keyword-based needs.

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, and destructiveHint=false, but the description adds substantive behavior beyond them. It explains that deep=true fetches page bodies for full-text matching and snippets, that results are ranked by keyword relevance across titles, descriptions, slugs, and body text, and that scores are relative rather than absolute.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and then organized into Args, Returns, Examples, and Note sections. It is appropriately detailed for a seven-parameter search tool, though the return-shape description and per-parameter recaps partly duplicate the schema/output schema.

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?

Given the moderate complexity, rich annotations, 100% schema description coverage, and presence of an output schema, the description is complete enough for an agent to select and invoke the tool correctly. It covers purpose, parameter behavior, examples, pagination, ranking semantics, and return format.

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 seven parameters. The description still adds useful meaning, especially that locale controls which market's URLs are returned, that deep=false performs a fast slug-only match, and that section can restrict results to areas like 'guides' or 'features'.

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: 'Search hemmiles.com for pages matching a keyword query.' It also distinguishes the tool from catalog/product search by explaining that Hemmiles is a SaaS marketing site and this searches content pages such as features, guides, blog posts, docs, and pricing.

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 clear from the keyword-search framing, the deep=false fast slug-only option, and examples like '"offline"' and '"medical reps" with section="teams"'. It does not explicitly compare against siblings such as list_pages or get_page, but the intended search use case is understandable.

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