Усилитель сигнала

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

With no annotations provided, the description must carry the behavioral burden. It discloses that the return is full article text including Q&A, which tells the agent what comes back, but it says nothing about read-only nature, authentication, missing-slug errors, or how a URL is resolved versus a slug.

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 what is returned, followed by parameter guidance. No filler, though the second sentence reads as a terse fragment rather than a fully formed instruction.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter retrieval tool with no output schema and no annotations, the description covers the essential facts: the returned content and the two accepted input forms. Error behavior and output shape are unaddressed but are minor for this complexity level.

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 0% and the schema only has a bare 'Slug Or Url' title, so the description must compensate, and it does: it explains that slug_or_url accepts either a slug obtained from usilitel_articles or a direct article address. It could go further on format expectations, but the dual-mode semantics are made clear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource and scope: it returns the full text of a blog article, including its Q&A content. This distinguishes it from the sibling usilitel_articles, which is referenced as the source of slugs, though the differentiation is implied rather than stated outright.

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 the reference to usilitel_articles as the place to obtain a slug, which suggests a two-step list-then-fetch flow. However, there is no explicit statement of when to use this tool versus usilitel_page_text or usilitel_content_search, and no 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?

No annotations are provided, so the description carries the burden. It discloses ordering and the shape of returned fields, implying a read-only listing, but says nothing about result limits, pagination, total counts, or whether all articles are returned. Adequate but with real gaps for a multi-item listing tool.

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, front-loaded clauses with no filler: the resource and ordering lead, and the pointer to the sibling closes. Every element 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?

With no output schema, the description usefully enumerates the returned fields and their ordering, which is the main thing an agent needs. It stops short of explaining volume or pagination behavior, a modest gap for a zero-param 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?

The tool takes zero parameters, so there is nothing to disambiguate and the baseline applies. The description reinforces this by not implying any required filters or arguments.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Names the resource (blog articles), states ordering ('новые первыми'), and enumerates the returned fields (title, date, summary, address). It also distinguishes itself from the sibling usilitel_article, which holds the full text. The only shortfall is that the listing action is implied rather than stated with an explicit verb.

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 to usilitel_article when the full article body is needed, which gives clear when-to-use-which guidance. It doesn't state exclusions or when this tool should be skipped entirely, which keeps it just short of a 5.

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?

With no annotations, the description carries the full disclosure burden; it does add genuinely useful context that the window is bounded by when the server began tracking the site, and that results span multiple change categories. It falls short on return shape (what fields a change entry has, URLs, old/new values), ordering, result limits, and whether the call is expensive.

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 core purpose is front-loaded in the first clause, and the enumeration of change types plus the `kind` value list is dense and earns its space. Slightly list-heavy, but no filler sentences.

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 read tool with no annotations and no output schema, the description needs to say what a returned change record looks like and how results are ordered/limited; it does not. The tracking-window caveat and kind enumeration cover the most important gaps.

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 0% and neither parameter is documented in the schema, so the description must compensate. It does this well for `kind` by enumerating all eight accepted values, but `days` is only obliquely implied by 'за последние дни' — its default of 7 and its interaction with the tracking-start bound are never stated.

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-like function (report what changed) and enumerates the exact change classes returned: new/departed products, price and stock changes, card updates, new articles, page text updates. It is clearly distinguishable from siblings like usilitel_products_search or usilitel_content_search, though it does not explicitly name a sibling it is not.

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 by the framing 'what changed since the server started tracking,' which tells the agent this is a delta/digest tool rather than a current-state query. However, there is no explicit when-to-use vs when-not-to-use guidance and no mention of alternatives such as usilitel_refresh or usilitel_content_search.

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?

No annotations are provided, so the description must carry behavioral context. It implies a read-only informational tool and describes the returned content categories, but it does not state freshness, caching, rate limits, or whether all catalog sections are always included.

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 a single front-loaded sentence that efficiently lists the catalog components returned. It is dense but every phrase contributes information, with no obvious filler.

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 output schema, the description adequately explains the return contents: sections, product counts, in-stock counts, collections by several dimensions, brands, service pages, and URLs. It could still specify the exact response structure, but it is sufficiently complete for a zero-parameter catalog overview tool.

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 has zero parameters, so there are no parameter semantics to explain; the baseline score of 4 is appropriate. The description does not need to compensate for missing schema parameter details.

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 clearly identifies the resource: catalog structure, including sections with product counts, collections within sections, brands, and service pages with URLs. It is specific enough to distinguish this from product search or catalog change tools, though it does not explicitly name or contrast sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this tool versus alternatives such as usilitel_catalog_status, usilitel_products_search, or usilitel_content_search. Usage is only implied by the noun phrase 'Структура каталога'.

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?

No annotations are present, so the description carries the full behavioral burden. It discloses the metrics returned but does not explicitly state that the operation is read-only, has no side effects, requires no permissions, or describe any rate limits. A status tool is implicitly safe, but the description could be more explicit.

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 sentences, zero waste. The core content is front-loaded, and the usage trigger follows immediately. Every phrase 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?

With no output schema and no annotations, the description should explain return values. It lists the key metrics (rebuild time, sync time, counts), which is sufficient for an agent to understand what will be returned. However, it omits explicit read-only assurance and any output format details.

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 has zero parameters, so parameter semantics baseline is 4. The description does not need to explain any inputs and correctly focuses on outputs.

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 clearly states what the tool provides: freshness and volume metrics (last rebuild, last sync, product/page/article/PDF counts). It is specific about the content, though it does not explicitly differentiate itself from siblings like usilitel_catalog_changes or usilitel_refresh.

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 a clear trigger: 'Вызывайте, если спрашивают, насколько актуальны данные' (call if asked how current the data is). There is no explicit when-not-to-use guidance or named alternative, but the context for use is unambiguous.

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?

No annotations are provided, so the description carries the full burden. It discloses content scope well, but says nothing about the return shape (single text blob vs. structured fields), whether the data is static or fetched live, or whether it aggregates several pages. For a zero-parameter informational tool that is a moderate but not severe 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?

A single front-loaded sentence opens with the resource and then enumerates coverage; nothing is redundant. The long comma-separated tail is dense but each item adds information about retrievable topics.

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-param, annotation-free info tool with no output schema, the description covers what content an agent can expect. The only material omission is the return format (plain text vs. structured), which would help the agent decide how to consume the result.

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 nothing for the description to disambiguate; baseline 4 applies. The schema is an empty object and the description correctly implies a no-argument call.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource ('Контакты и условия магазина') and enumerates the concrete topics covered (phone, email, hours, delivery, payment, returns), which clearly separates it from siblings like usilitel_articles or usilitel_products_search. It lacks an explicit verb (e.g. 'returns/gets'), but the resource 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?

The topic list implies when to call it (contact, delivery, payment, return questions), but there is no explicit statement of when to use it versus usilitel_page_text or usilitel_content_search. Usage must be inferred from the enumerated content.

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?

No annotations are provided, so the description carries the full burden. It does disclose the return shape ('matching pages with a text snippet'), which is genuinely useful, but says nothing about search semantics (exact vs full-text, language, stemming), result limits, or whether the snippet is truncated.

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 sentences, zero filler, front-loaded with the search scope and the exclusion. Every clause 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 snippet-of-results note partly compensates for the absent output schema, but with no annotations and 0% parameter documentation, the definition leaves an agent without enough detail on query syntax or result count to invoke it confidently.

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 0% and neither parameter is explained. The description never clarifies what 'query' accepts (keywords, phrase, natural-language question) nor what 'limit' bounds, so the agent must guess at the most consequential input.

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) over specific resources (blog articles, section/collection/service texts) and explicitly excludes products, naming the sibling that handles them. An agent can distinguish it from usilitel_products_search without opening any 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 product case to usilitel_products_search, which is a real when-not rule. However, it gives no guidance on the boundary with usilitel_article, usilitel_articles, or usilitel_page_text, which also return article/page content and are the most likely source of mis-selection.

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?

There are no annotations, so the description carries the full burden. It does disclose the return shape (matching models, in-stock first, plus an explanation of the selection rules) and frames itself as a preliminary pick, which is useful. It never states whether this is read-only/no side effects, whether prices are live, or any rate/availability caveats for a tool that queries a live catalog.

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 in one sentence, followed by a compact parameter glossary and a closing caveat about measurement. Every line is informative; the dense em-dash parameter run is slightly harder to scan than a list, but nothing is redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter, no-output-schema tool, the description covers nearly everything an agent needs: intent, per-parameter meaning, ranking behavior, and the measurement follow-up. Only the limit parameter and output format details (units, structure of the 'explanation') are left unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 8 params, so the description must compensate, and it largely does: it enumerates object_type values, explains operators (МТС, Билайн, МегаФон, T2), bands_mhz, need (calls|internet|both), ready_kit semantics, and max_price in rubles. The only undocumented parameter is limit, and the need enum is given only in prose while the schema declares it as a bare string.

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 opening line states a specific verb and resource: selecting equipment variants for a given object (дача, офис, склад...). That is clearly distinct from the generic catalog/search siblings, though it never names the alternative tools explicitly. An agent can grasp the goal without reading the schema, but the boundary versus usilitel_products_search is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives real selection logic: bands_mhz from a measurement override operators when known, ready_kit switches between kits and repeaters, and it advises offering a signal measurement as the next step. There is no explicit 'use this instead of X' routing to the sibling search tools, which keeps it below a 5.

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?

With no annotations, the description carries the behavioral burden. It usefully discloses the returned content structure (title, description, block text, Q&A), but does not explicitly state read-only behavior, error handling, URL/path handling, or any limits.

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 compact and front-loads the resource being returned, followed by content types and use cases. It is appropriately sized for a simple one-parameter retrieval tool, with only minor verbosity in the page-type list.

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 low-complexity retrieval tool with no output schema, the description gives a reasonable picture of returned content and intended use. However, it leaves the only parameter underspecified and does not clarify boundaries with sibling content tools, so it is adequate rather than 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?

Schema description coverage is 0% for the single required path_or_url parameter. The description only incidentally includes an example path (“/repiteri/dlya-dachi/”) without explaining whether full URLs are accepted, expected path format, or required semantics.

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 clearly states that it returns website page text and enumerates page types (section, collection, brand, service, home) plus returned content elements (headline, description, block text, Q&A). It is specific about the resource, though it does not explicitly distinguish itself from sibling tools such as usilitel_article or usilitel_content_search.

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 a use case: explanations such as “how to choose” and service terms. However, it does not say when to use this tool versus alternatives or when not to use it, so the guidance remains implicit.

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?

No annotations are supplied, so the description must carry the behavioral load: it does state what is returned in unusual detail (including PDF documents such as passports and certificates), which implies a read-only lookup. But it is silent on failure behavior for a bad id/URL, permissions, and whether fetching PDFs is costly or slow, so a mutation-free but non-trivial retrieval tool remains partially opaque.

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 return contents are front-loaded and the parameter note comes second, so the agent can decide relevance in one pass. The field enumeration is long but each item (prices, presence, PDFs) is genuinely discriminating; only slight trimming would help.

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 one required parameter and no output schema, the description does the necessary work by describing the returned payload in detail. The remaining gaps — not-found behavior and whether the URL must be exact — are minor for a single-argument lookup tool.

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 0%, so the description is the only source of meaning for id_or_url, and it adds real value by declaring three accepted forms: an id from usilitel_products_search, an артикул (SKU), or a page URL on usilitel-signala.ru. It stops short of giving the expected URL shape or id format.

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+resource ('Полная карточка товара') and then enumerates the exact contents of that card (price, availability, characteristics, photos, PDFs, site description text), which distinguishes it from lightweight siblings such as usilitel_products_search. It also names the sibling that produces the id, anchoring its role in the catalog workflow.

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 explicitly says to pass an id obtained from usilitel_products_search, or an SKU, or a product page URL, which tells the agent where this tool sits in the sequence. It does not, however, say when to prefer it over usilitel_products_compare or usilitel_page_text, nor does it state any 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?

With no annotations, the description carries the behavioral burden. It helpfully states the output shape as a table of 'characteristic → values' and constrains comparison to 2–5 products, but it does not explicitly say whether the operation is read-only, whether it requires auth, or how invalid ids are handled.

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 two efficiently structured sentences: the first states what the tool does and its output format, the second explains the sole parameter. No filler or redundant 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?

For a one-parameter comparison tool with no output schema and no annotations, the description covers purpose, comparison fields, output table shape, parameter semantics, and the 2–5 product constraint. Minor behavioral details such as read-only status are absent but not critical for a comparison operation.

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 0%, so the description must compensate for the bare 'ids' array. It does so by explaining that ids may be product ids, article numbers, or product addresses, and by tying the 2–5 item constraint to that parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb, 'Сравнить' (compare), a specific resource, 2–5 products, and the comparison dimensions: price, availability, frequencies, area and characteristics. This operationally distinguishes it from sibling tools like product details and product search, which target one product or discovery rather than side-by-side comparison.

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 comparison purpose is clear and implicitly indicates when to use the tool, but there is no explicit guidance about when to prefer it over usilitel_product_details or usilitel_products_search. No exclusions or prerequisites are stated.

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

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

With no annotations at all, the description carries the whole burden. It does disclose the return shape (short product cards rather than full records) and pagination via offset, but says nothing about result ranking behavior, whether filters are combined with AND/OR, or any limits/costs of calling it repeatedly.

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 purpose is front-loaded in a single line, followed by a dense parameter glossary; for a 13-parameter tool this structure is appropriate and each line maps to a parameter. It reads as a list rather than prose, but there is no wasted sentence.

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 13 optional parameters, no annotations, and no output schema, the description is nearly sufficient: it covers every filter, the sort/limit/offset paging model, and the granularity of the returned cards. The remaining gap is how multiple filters interact and default behavior when everything is empty.

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 0%, so the description must compensate entirely, and it does: it explains query matching semantics (all words must appear, searched across name/article/specs) and enumerates valid values for section, brand, band_mhz, operator, object_type and sort. It also documents limit (1–50), offset, price range and the search_specs/in_stock_only toggles, leaving essentially nothing undocumented.

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?

Opens with a specific verb+resource: find equipment in the «Усилитель сигнала» catalog, and closes by routing to usilitel_product_details for full cards, which separates it from the details sibling. It does not explicitly distinguish itself from usilitel_content_search or usilitel_products_compare, so the differentiation is only partial.

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 by the parameter walkthrough and by the closing hint that this tool returns short cards while usilitel_product_details gives details. There is no explicit when-to-use/when-not or guidance on choosing between search, content_search, and compare, so the agent must infer.

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?

With no annotations, the description must carry the full behavioral load. It does disclose the key trait — this triggers an out-of-band immediate sync that is normally redundant — but says nothing about whether the call blocks until the sync finishes, what it returns, or whether it is costly/rate-limited.

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 sentences, both earning their place: the first states what happens and the default schedule it overrides, the second states the calling condition. The gating condition is placed last where it is most actionable.

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 tool with no annotations and no output schema, the description covers purpose, background behavior, and the trigger condition. The only material gap is return behavior — the agent cannot tell whether the call returns refreshed data, a status, or nothing.

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; no parameter information is needed or missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete action (immediately sync/refresh data from the site) and contrasts it with the automatic background refresh that runs every few minutes, so an agent can tell this is the manual cache-refresh tool rather than one of the sibling read tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit gating rule: call only when the user directly asks for a data refresh, otherwise wait for the scheduled update. That is a clear when-to-use and when-not-to-use statement, not an implied one.

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?

With no annotations, the description carries the full burden and largely does so: it explains what opening the link does (request window, selection pre-filled in comments, user only enters a phone), that a manager calls back during business hours, that product names/prices/availability get injected, and that up to 10 products are allowed. It does not state whether the link expires, is single-use, or whether anything is persisted server-side, which are the main remaining behavioral unknowns.

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 and trigger are front-loaded, followed by what happens on the link and then per-parameter guidance. Every sentence carries information (including the important PII warning), though the paragraph is a bit dense and could be split for scanning.

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 link generator with no annotations and no output schema, the description covers purpose, trigger, downstream user flow, and both parameters thoroughly — including the return artifact (a URL) implicitly. Missing only details on the returned value's form/expiry, which an agent rarely needs to act.

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 0%, so the description must define the parameters — and it does. It spells out the required `summary` content (object, area, operator or frequency, needed services, wishes) plus a hard rule to exclude PII, and explains `product_ids` accepts ids or urls, caps at 10, and clarifies that names/prices/stock are enriched automatically.

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 product: a link to the site's request form with the selection pre-filled in the comment field. It is clearly distinguishable from siblings like usilitel_equipment_pick (selection) — this is the final conversion step that hands the user a ready-to-submit form.

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?

"Давайте её, когда человек готов заказать, хочет расчёт, консультацию или монтаж" gives an explicit trigger condition covering the main intents. It does not name a sibling alternative or state what to do beforehand (e.g., pick equipment first), but the "с уже заполненным подбором" phrasing implies the prerequisite.

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