Saymon RU Data API

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 meaningful context: official CBR source, daily refresh frequency, and pricing ('$0.008 USDC'). However, it does not describe result format, rate limits, or how invalid or missing currency codes 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 one compact sentence that front-loads the core purpose and update frequency, followed by a short price note. There is minimal filler, though the '$0.008 USDC' string is not functional guidance and could be moved to metadata.

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 tool with one optional parameter and no output schema, the description provides the essential context: official source, daily refresh, and currency coverage. It falls short only on input behavior (null handling and expected format) and return shape, which an agent would need for a fully confident call.

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 the description never names the 'currencies' parameter or explains its default null behavior. It hints that ISO codes are accepted ('USD, EUR, CNY, GBP, KZT и другие ISO-коды'), but it does not clarify array vs. single-value input or what null returns.

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 concretely ('Official rates of the CBR RF') and gives the update cadence plus concrete currency examples, so an agent can identify this as a currency-rate lookup tool. It lacks an explicit verb and does not directly distinguish itself from the financial sibling moex_quote, 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?

No when-to-use vs alternatives guidance is provided; the description only states that rates are daily and lists examples. There are no exclusions or comparisons to sibling tools, so the agent must infer the appropriate use case from context.

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 of behavioral disclosure. It does disclose that the tool costs $0.05 USDC and bundles three services, but it does not explain whether this is a read-only lookup, whether payment is triggered immediately, what the response contains, or any restrictions or side effects. This is a significant gap for an unannotated 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?

The description is a single sentence with no filler: it names the package, lists its component services, and states the price. Every element earns its place and the most important purpose information is front-loaded.

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 that there is no output schema, no annotations, and three undocumented parameters, the description is not complete enough for an agent to invoke the tool correctly. It provides useful package context and pricing, but omits parameter semantics, expected return data, and operational 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?

Schema description coverage is 0% and the description does not mention inn, limit, or max_pages at all. It adds no meaning beyond the raw parameter names, so an agent cannot infer what values are valid for limit or max_pages or how they affect the report.

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 tool as a counterparty-check/KYB-dossier package combining EGRUL, self-employed status, and a deep internet dossier. It lacks an explicit verb like 'fetch' or 'generate', but the package framing makes the purpose understandable and distinguishes it from the individual sibling services.

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

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

The description implies the usage context: use this when a full KYB/counterparty check with multiple data sources is needed in one paid call. It does not explicitly state when not to use it or point to sibling tools such as ru_research or inn_lookup for narrower needs, so guidance is only 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 provided, so the description must fully disclose behavioral traits. It only states the data source (FNS registry) and the cost, omitting details about read-only nature, response format, error handling, or any side effects. For a tool with zero annotation coverage, this under-discloses critical operational behavior.

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

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

A single concise sentence that includes the core function and the pricing. Every word earns its place, and the most important information is front-loaded.

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 lookup without an output schema, the description covers the purpose and cost, but lacks details about the return value structure, possible errors, or prerequisites (e.g., valid INN format). An agent would know to call it but not what to expect in response, making it partially 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%, so the description must explain the 'inn' parameter. It merely repeats the name and implies it's the tax identification number, but does not specify format (e.g., digit count), validation rules, or any special handling. This barely adds value 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 description states a specific action (checking status) on a specific resource (FNS registry for self-employed by INN). It clearly distinguishes this from the siblings (e.g., inn_lookup) by specifying the NPD context, making the purpose 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 description implies usage: to obtain self-employed (NPD) status for a given INN. It does not explicitly mention when not to use it or compare to alternatives like inn_lookup. However, the NPD specificity provides clear context, so an agent can infer the appropriate scenario, but explicit exclusions are missing.

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 behavioral disclosure burden. It discloses the data source (EGRUL) and the cost ($0.01 USDC), which is useful. It does not describe the response shape, potential failure modes, or any side effects beyond the paid lookup.

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 concise sentence with the core purpose front-loaded and a useful cost detail appended. Every word earns its place; there is no redundancy or 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?

For a simple one-parameter lookup, the description provides the resource and source, but it lacks parameter format guidance and does not hint at what the response contains, especially since no output schema is available. It is adequate but not fully self-sufficient.

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 the description only says 'по ИНН', which repeats the parameter name without adding format, validation, or example. Since this is for Russian legal entities, the expected 10-digit INN format should be stated; otherwise an agent may supply an invalid 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?

The description states a specific action and resource: 'Проверка российского юрлица по ИНН (ЕГРЮЛ)' — checking a Russian legal entity by INN using the EGRUL registry. This clearly distinguishes the tool from siblings like cbr_rates or pochta_offices.

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 clear context for when to use the tool: when an agent needs to verify a Russian legal entity by INN. However, it does not explicitly mention when not to use it or point to an alternative like company_report, so usage guidance is implied rather than explicit.

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 provided, the description carries the full burden of behavioral disclosure. It does disclose the per-call cost ($0.008 USDC) and the data source (MOEX ISS), which adds useful context. However, it omits important behavioral traits such as data freshness/delay, return format, availability limitations, or whether it only returns last price as opposed to other quote fields.

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 compact sentence, front-loaded with the main purpose and ending with the cost. Every word adds value, with no redundant 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?

The tool is relatively simple with two parameters and no output schema, so the description should explain return values and parameter options. It does mention 'last price' as the output and provides examples, but it fails to clarify the exact 'market' parameter values, the response structure, or any operational constraints. It is adequate for a basic call with defaults but incomplete for arbitrary symbols.

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?

Since schema description coverage is 0%, the description must compensate for the bare parameter names. It provides real symbol examples for each asset class (SBER, GAZP, USD/EUR/CNY, IMOEX) and implies the 'market' parameter selects among shares, currency pairs, and indices. Yet it does not enumerate exact valid values for 'market', leaving the exact syntax for currency pairs or indices ambiguous.

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

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

The description clearly states the tool provides Moscow Exchange quotes with the last price of stocks, currency pairs, and indices, and gives concrete examples like SBER and IMOEX. It identifies the resource (MOEX ISS) and the action (delivering quotes), but it does not explicitly differentiate itself from sibling tools like cbr_rates, so it loses a point for lack of sibling distinction.

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 no guidance on when to use this tool versus alternatives such as cbr_rates for official exchange rates, ru_page for general data, or other quote-like tools. It does not provide any exclusions, preferred contexts, or conditions that would help an agent choose this tool over 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?

With no annotations, the description carries the full burden of behavioral disclosure. It reveals only the operation and a price, but not output format, validation semantics, failure modes, or whether a complete address is required. The cost detail is useful but does not compensate for the missing context.

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 short, front-loaded sentence states the provider, action, target, and price with no filler. 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?

For a one-parameter tool with no annotations and no output schema, the description is too thin: it omits output shape, usage conditions, and alternative routing. The price and function are present, but an agent lacks enough to reliably distinguish and invoke it without external knowledge.

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. It tells the agent that the single 'address' string is a Russian address and hints that normalization yields index/region/street/house, but it does not specify input format or whether partial addresses are accepted.

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 uses a specific verb ('нормализация') and resource ('российского адреса'), and enumerates the normalized fields (индекс, регион, улица, дом). This makes it distinguishable from sibling tools like pochta_delivery, pochta_track, and pochta_zip, which address different postal operations.

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 or exclusions is provided; the tool is not contrasted with any sibling. 'Нормализация' implies the context, but the agent must infer when to choose this over pochta_zip or pochta_delivery.

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 disclose behavior. It only states it provides a package of services and a price ($0.04 USDC), but does not disclose that it likely triggers a payment or that it aggregates multiple API calls. It also does not mention any side effects or limitations. This is a significant transparency gap for a paid 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?

The description is a single sentence, short, and front-loads the key value proposition (package of services). It is efficient but lacks essential operational details; it is not overly verbose, so it earns a 4 for structure, but not a 5 because it is more of a marketing blurb.

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 7 parameters, no output schema, no annotations, and no usage guidance, the description is woefully incomplete. An agent cannot know how to fill parameters, what the service actually returns, or when to use it. The complexity is moderate, but the description only lists features and price, leaving all critical information 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?

The input schema has 7 parameters with 0% description coverage. The description mentions 'адрес, индекс, отделение, стоимость и срок' (address, index, office, cost and time) which loosely maps to parameters like to_address, to_index, from_index, but it does not explain each parameter's meaning or how they are used. It adds no detail beyond what the schema already shows (e.g., default values are clear but not explained). The baseline for 7 params with low coverage is to compensate, but it barely does.

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 it is a package for 'Доставка Почты России' (Russian Post delivery) including address, index, office, cost, and time in one payment. It clearly indicates the tool covers delivery-related services, but it is vague about the exact action (e.g., compute delivery, get rates) and does not specify the primary function beyond being a bundle. It distinguishes from siblings like pochta_tariff and pochta_delivery_time by implying it combines them, but the verb is 'пакет' (package) which is not an action.

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 use this tool versus alternatives like pochta_tariff or pochta_track. It mentions the package includes cost and time, but does not say 'use this instead of individual tools when you need everything in one payment.' The description is merely a product pitch, not usage guidance.

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

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

No annotations are provided, so the description carries full responsibility. It discloses the cost ($0.01 USDC), which is useful, but does not state that it is a read-only operation, what happens with invalid indexes, whether authentication is needed, or any rate limitations. The safety profile is largely undisclosed.

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 short sentence that leads with the purpose and includes the cost. It is efficient and free of fluff. However, it under-specifies important details, so while concise, it is not backed by supporting structure like parameter notes.

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 a 4-parameter tool with 0% schema coverage, no output schema, and no annotations, the description is severely insufficient. It omits parameter semantics, expected output, error handling, and any usage conditions. An agent would struggle to call this tool correctly without external knowledge.

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 the description mentions none of the four parameters (from_index, to_index, mail_type, mail_category). It does not explain what these values represent or how to format them. The description fails to compensate for the missing schema documentation.

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 ('delivery times') and resource ('between indexes'), and mentions the unit ('in days'). It conveys the core function clearly and is distinct from siblings like pochta_tariff (tariffs) and pochta_track (tracking). However, it doesn't explicitly name alternatives or differentiate itself, so it falls 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?

No guidance is given on when to use this tool compared to siblings like pochta_tariff or pochta_delivery. There are no exclusions, prerequisites, or suggested contexts. The description merely states what it does without any usage direction.

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. It does disclose the cost ($0.01 USDC) and the two lookup modes, which is useful. However, it does not state that this is a read-only operation, describe the response format, or mention any rate limits or error behavior. The lack of explicit safety information is a gap, though the tool name suggests a non-mutating lookup.

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 efficient sentence followed by the cost, with no superfluous words. It front-loads the primary purpose and includes the pricing information. While it is brief, 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?

The tool has no annotations, no output schema, and low parameter coverage; the description does not mention return value format, pagination behavior, or how conflicting inputs (both postal_code and coordinates) are handled. An agent would have to guess or experiment to fully understand the tool's behavior.

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. It explains postal_code and coordinates (latitude/longitude) but does not clarify the meaning of 'top' (the maximum number of results). This leaves one parameter semantically unexplained, and the description only partially maps to 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 clearly states the tool returns Russian Post offices either by postal code or by coordinates, which distinguishes it from sibling tools like pochta_track (tracking) and pochta_tariff (pricing). However, it lacks an explicit verb like 'get' or 'find', making it slightly less direct than an ideal verb+resource formulation.

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

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

The description implies the tool is for looking up offices but provides no explicit guidance on when to prefer it over alternatives, nor any exclusions. It mentions two modes (postal code or coordinates) but does not explain when to choose one over the other or what happens if both are provided.

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 exist, so the description carries the burden. It notes pricing (official API, $0.01 USDC) but does not disclose error behavior, result format, or whether a live external call is made. The term 'официальный API' implies a network call, but this is not 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?

One dense sentence, immediately states the core value proposition and pricing; no fluff. The price note is useful for an agent planning tool usage.

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 7 parameters and no output schema or annotations, the description omits enough context for correct invocation—especially allowed values of mail_type/mail_category, the meaning of indices, and units of weight.

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?

Input schema coverage is low (no descriptions), and the description only clarifies the meaning of 'between indices' (from_index/to_index) and, implicitly, tariffs. It adds nothing about weight, mail_type, mail_category, declared_value, or their allowed values, leaving the agent to rely on parameter names and defaults.

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 (Russian Post) and the purpose (delivery cost and times between postal codes), plus cost/pricing info. It is specific enough to distinguish the tool from its pochta_* siblings, though it doesn't use an explicit verb like 'calculate'.

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 guidance on when to use this tool versus the alternatives (pochta_address, pochta_zip, etc.), no prerequisites, and no mention of index format requirements or edge cases.

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 disclose side effects, access needs, or expected output. It states the tool tracks and costs $0.01 USDC, but does not say whether the call is read-only, what information it returns, or any limitations such as barcode format requirements.

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 one front-loaded sentence with no filler, and the price is useful supplemental information. Every word earns its place.

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

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

This is a low-complexity, one-parameter tool, but with no output schema the description should still indicate what result to expect from tracking. It does not mention return data, errors, or input format, leaving an agent without full invocation context.

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 input schema has no descriptions for the sole 'barcode' parameter. The description adds that the barcode is a Russian Post tracking number, which clarifies meaning, but does not give format, examples, or constraints needed to validate the 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?

The description names the exact operation in Russian: tracking a Russian Post shipment by tracking number. This clearly distinguishes it from sibling postal tools like pochta_address, pochta_tariff, and pochta_offices, which cover different purposes.

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

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

The phrase 'tracking shipment by track number' gives a clear context for when to call this tool: when the user has a Russian Post tracking/barcode and wants shipment status. It does not explicitly rule out adjacent tools like pochta_delivery or pochta_delivery_time, so it falls 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?

There are no annotations, so the description carries the behavioral disclosure burden. It usefully discloses that the lookup costs $0.01 USDC and that it returns both office address and locality. It does not mention failure behavior, required authorization, or whether the tool performs an external API call, but the core read-only nature is implicitly clear.

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 one concise sentence plus a cost note. It front-loads the core purpose and adds only the relevant pricing detail, with no filler or 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?

For a single-parameter lookup with no output schema and no annotations, the description is minimal but broadly sufficient: it states what the tool does and its cost. It lacks explicit notes on return format, invalid postal codes, or whether the output is structured, which an agent might need for robust handling.

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. It adds that postal_code is an 'индекс' (Russian postal index) and ties it to the returned address/locality. However, it does not specify the expected format (e.g., 6 digits), validation rules, or any normalization behavior.

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 the resource (address of a Russian Post office and the locality) and the query criterion (по индексу / by postal code), so an agent can understand what the tool returns. It does not explicitly distinguish itself from sibling tools like pochta_address or pochta_offices, but the 'по индексу' scope is reasonably specific.

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

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

The description implies the tool should be used when an agent has a Russian postal code and needs the associated post office address and locality. However, it provides no explicit guidance about when to prefer this over siblings such as pochta_address or pochta_offices, nor 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 provided, the description carries the full burden. It discloses the conversion behavior, output format (Markdown), and cost ($0.01 USDC), but lacks details about fetching behavior, failure conditions, or page limits. That's adequate for a simple conversion tool but not deep transparency.

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 an extremely concise two-part statement: transformation and price. Both elements are useful and front-loaded with no 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?

For a one-parameter, no-output-schema tool, the description covers the essential use case and cost. It does not mention failure cases, URL requirements, or whether the returned Markdown is cleaned/truncated, but it is sufficient for a basic invocation decision.

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 compensate for the single 'url' parameter. It does so by specifying 'URL -> LLM-ready Markdown', clarifying the URL is expected and that output is markdown; this is meaningful but does not explain formatting or edge cases related to the URL.

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 'RU-страница URL -> LLM-ready Markdown' clearly defines the tool as converting a Russian webpage URL into Markdown, giving a specific input (RU page URL) and output (LLM-ready Markdown). It doesn't state explicit alternative-selection criteria or differentiate among sibling search/research tools, so not a perfect 5, but it's more specific than a mere restatement of the tool name.

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

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

The description implies the use case: supply a Russian page URL and receive LLM-ready Markdown. It does not explicitly tell the agent when to choose this over siblings like ru_search or ru_research, and it doesn't mention URL formatting or non-Russian page 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?

The description discloses the cost ($0.02 USDC) and the bundled output format (top pages in Markdown), which is useful behavioral context beyond the schema. However, with no annotations, it leaves out auth requirements, failure/refund behavior, rate limits, and whether the operation is read-only.

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 compact sentence that front-loads the tool's purpose and value proposition. Every phrase earns its place, though the lack of parameter or usage details limits structural completeness.

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 annotations, no output schema, and only 0% schema description coverage, this description is too thin to support correct invocation. It covers cost and high-level output but omits parameter behavior, return structure, and selection criteria; an agent is left with significant ambiguity.

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, but it only vaguely implies query and top pages. The 'limit' parameter is entirely unexplained, and 'max_pages' is not explicitly tied to the 'top-страницы' phrase. An agent has to guess parameter meanings.

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?

Description identifies a clear package: Cyrillic search plus top pages in Markdown in a single paid operation. It names the resource and deliverable, though it doesn't explicitly contrast with sibling tools like ru_search, ru_page, or ru_research_deep.

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

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

The description implies a bundled research use case, but it provides no explicit guidance about when to choose this tool over ru_search, ru_page, or ru_research_deep. No exclusions or alternative selection conditions 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?

With no annotations, the description carries the burden. It discloses that the tool is a paid action ($0.05 USDC), includes 3 searches, and returns up to 10 Markdown pages. However, it does not explain side effects (e.g., payment failure, result truncation beyond limits) or processing behavior, leaving significant ambiguity.

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 sentence, which is concise, but it reads more like a sales pitch than a function spec. Information about pricing and page count is front-loaded, but key operational details are missing. The structure is flat and not logically organized.

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 3-parameter tool with no output schema, this description is incomplete. It lacks explanation of return values (beyond Markdown pages), how query, limit, and max_pages interact, and operational prerequisites like wallet balance. It provides some context (cost, limits) but leaves major gaps for an agent to call 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?

Schema description coverage is 0%, so the description must compensate, but it fails to explain any parameter. It mentions '3 searches' which could map to limit or max_pages, but not clearly. The default max_pages (8) contradicts the advertised 'up to 10 pages', adding confusion. No parameter is elaborated.

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 identifies the tool as a 'research package deep' with 3 searches and up to 10 pages in Markdown for one payment. It implies it performs research on a query but lacks an explicit verb+resource structure like 'Performs deep research and returns...'. It distinguishes itself from siblings via 'deep' and pricing, but doesn't clearly state its core function.

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 guidance is provided on when to use this tool versus alternatives such as ru_research, ru_search, or ru_page. There is no mention of scenarios for deep research vs. basic research, or any exclusion criteria. The user is left to infer its use.

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 are absent, so the description carries full responsibility for disclosing behavior. It mentions a cost per call ('$0.02 USDC') and implies it returns search results, but it does not state whether the operation is read-only, what the response structure is, whether pagination is supported (despite a limit parameter), or any authentication or rate-limit requirements. The cost note is a minor positive but insufficient coverage.

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 with zero filler. It achieves conciseness, but the brevity sacrifices essential details; still, for the sole criterion of being concise, it is excellent.

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 (2 params, no output schema), but the description leaves out critical details: return format, result count behavior, and how it differs from ru_page/ru_research/ru_research_deep. An agent cannot fully judge when to invoke it or what to expect from results. The lack of output schema makes a description of the response shape particularly important.

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 the description does not compensate. It does not explain what 'query' should contain, how results are ordered, or what 'limit' controls (though its default of 5 hints at a cap). The agent must infer semantics from parameter names alone, which is risky for non-obvious behavior like language/locale constraints.

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 ('search') and resource ('web') with a scope qualifier ('Cyrillic'), making the primary purpose clear. It distinguishes from postal and financial siblings but does not explicitly differentiate from similar search/research tools like ru_page, ru_research, or ru_research_deep.

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 offers no guidance on when to use this tool versus alternatives. It does not mention any exclusions, complementary tools, or conditions that would lead an agent to prefer ru_search over ru_page or ru_research. This is a clear gap for a tool with many 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?

It discloses a non-obvious behavioral trait: the operation is paid, costing $0.18 USDC per package, and supports up to 10 queries at a 10% discount. With no annotations, though, it does not disclose payment prerequisites, failure behavior, or what happens if more than 10 queries are 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 one compact sentence that front-loads the core purpose and batch scope, then adds pricing. There is no filler or redundant restating of the tool 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 simple paid batch-search tool, it covers purpose, batch size, and cost, which are the essentials. However, it leaves parameter details and return/output behavior unstated, and there is no output schema to fill that gap.

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. It indirectly maps 'запросов' to the `queries` parameter and implies a batch cap of 10, but it does not define `queries` format, the `limit` parameter, or their relationship.

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 operation: Cyrillic web search in batch mode, with the concrete scope 'up to 10 queries in one payment.' This distinguishes it from `ru_search` (single search) and `ru_search_x100` (larger batch).

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

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

The description implies the intended use case: batch several Cyrillic search queries together to benefit from the 10% discount and single payment. However, it never explicitly says when to prefer this tool over `ru_search` or `ru_search_x100`, 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?

No annotations are present, so the description must carry full behavioral weight. It discloses that the tool requires payment and can handle up to 100 queries, but it does not state what a search returns, whether it is read-only, or any rate limits. This is insufficient for a tool with no annotation support.

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 short, but it spends its only sentence on pricing and batch size rather than on functional guidance. This is under-specification rather than concise usefulness, and the structure does not lead with the action.

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 tool with two parameters, no output schema, and no annotations, the description is incomplete. It omits parameter semantics, return behavior, and any usage examples, leaving an AI agent without enough information to invoke the tool 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?

Schema description coverage is 0%, and the description provides no explanation of the 'queries' array or 'limit' integer. An agent cannot infer what values are appropriate for these parameters, so the description fails to compensate for the schema gap.

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 identifies this as a Cyrillic web search package for up to 100 queries, which clearly distinguishes it from the sibling ru_search_x10. However, it is phrased as a noun phrase and a price tag, lacking a clear verb and a full functional explanation.

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 explicit guidance is given on when to use this tool versus ru_search or ru_search_x10. The price and batch size imply it is for large sets of queries, but the description never states that preference or mentions alternatives.

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 disclose behavioral aspects. It mentions the cost ($0.005 USDC per call) and the data fields returned, but omits details like rate limits, error handling, or whether it is strictly read-only (though that is evident). There is no mention of output format, pagination, or handling of invalid symbols, leaving significant gaps for a tool with zero annotation coverage.

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 sentence that efficiently conveys purpose, data fields, examples, and cost. It front-loads the core function and includes a price indicator, making it highly concise and well-structured.

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 one-parameter tool with no output schema, the description covers the essential data fields and examples. It lacks explicit mention of error scenarios or symbol format constraints, but these are minor for a ticker service. The cost disclosure adds practical context. Overall, it is nearly complete for an agent to use 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?

Schema coverage is 0%, so the description is the only source of parameter meaning. It provides example symbols (BTCUSDT, ETHUSDT) implying the 'symbol' parameter format, and indicates more are supported. However, it does not explicitly state that the parameter is optional (default BTCUSDT) or clarify uppercase/lowercase requirements, relying on inference from 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?

The description clearly states the tool retrieves crypto tickers from Bybit spot market, listing specific data fields (price, 24h change, volumes) and example symbols (BTCUSDT, ETHUSDT). This distinguishes it from sibling tools like moex_quote (stocks) and cbr_rates (currency) by specifying the exchange and asset class.

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 does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions. However, the Bybit crypto context strongly implies it is for cryptocurrency quotes, which is a clear use case. No direct comparison to other tools is provided, so guidance is implicit rather than explicit.

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 behavioral burden. It adds meaningful context: the underlying provider (Tavily via x402), the output type (fresh results plus a brief answer), and a hard cost of $0.02 USDC. It does not mention rate limits or failure modes, but for a simple search tool these disclosures are substantial.

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 sentence with no filler. It front-loads the core purpose, names the integration channel, states the output format, and appends the cost in a compact and readable way.

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 tool with no output schema and no annotations, the description provides a reasonable orientation but leaves gaps: the meaning of 'limit', the structure of the returned response, and explicit differentiation from ru_search and other Russian tools. It is adequate but not 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%, and the description does not compensate. The phrase 'по запросу' only restates that the tool answers a query, providing no additional meaning for the 'query' parameter. The 'limit' parameter is not explained at all, leaving its effect on result count entirely implicit.

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 opens with 'Глобальный веб-поиск' (global web search), a specific verb and resource, and states the deliverable: 'fresh results and a brief answer per query.' The word 'global' clearly distinguishes it from the Russian-focused sibling tools such as ru_search, ru_page, and ru_research.

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 'global' qualifier gives clear context that this tool is for international/non-Russian queries, and the sibling set of Russian-specific search tools reinforces that distinction. However, there is no explicit when-to-use or when-not-to-use guidance compared to alternatives.

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