marketplace

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

With no annotations provided, the description carries the full burden of disclosing behavior. It only mentions 'official' and 'free', but does not explain response format, error behavior, data freshness, or any constraints. This is insufficient for an agent to understand the tool's operational characteristics.

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 extremely concise with no fluff, and the key information is front-loaded. However, it is so terse that it borders on under-specification, hence not a perfect score.

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

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

Given the tool's simplicity, the description still lacks critical context: no usage scenarios, no return description, no parameter details, and no differentiation from sibling tools. An agent would struggle to know when to invoke this tool and how to construct a valid request.

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 labels the parameters as 'base' and 'symbols', which clarifies their roles, but provides no details about acceptable values, format, or examples. This adds minimal meaning beyond the bare schema field names.

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 as official ECB cross-rates and mentions the base+symbols scope, distinguishing it from sibling tools like kzt_rates. However, it lacks an explicit verb like 'get' or 'retrieve', making it slightly less direct than ideal.

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 such as kzt_rates or how it fits into a workflow. Sibling tools are not referenced, and no exclusions or prerequisites are mentioned.

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 convey behavioral traits on its own, but it only mentions the return format and content. It does not disclose error behavior (e.g., what happens if listing_id is not found), authentication requirements, rate limits, or 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?

The description is a single, front-loaded sentence that efficiently conveys the core action and output. Every word serves a purpose, with no redundant or extraneous 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?

Although the tool is simple (one parameter, no output schema), the description is too thin. It omits critical details like error handling, the meaning of 'KYA status', and how the response JSON-LD is structured. Without annotations or an output schema, the description does not adequately prepare the agent to use 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?

The schema only defines listing_id as a string with no description. The tool description adds no information about the expected format (e.g., UUID, integer) or how to obtain it. With 0% schema coverage, the description entirely fails to compensate, leaving the parameter 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's function with a specific verb ('Get') and resource ('one listing'), and adds distinguishing details ('incl. seller DID + KYA status' and 'as JSON-LD'). This differentiates it from search_listings and other siblings.

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 like search_listings. The necessity of having a listing_id from a prior search is implied but never stated, leaving the agent to infer the intended usage 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?

With no annotations provided, the description carries the full burden of disclosing behavior. It adds useful context about caching (hourly) and the cost ('Free'), which helps an AI agent set expectations. It doesn't mention output format or error behavior, but for a simple read-only tool this is adequate.

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, information-dense sentence with no filler. It front-loads the core purpose and includes essential behavioral details without unnecessary length.

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 tool with one optional parameter and no output schema, the description covers the key aspects: what it returns (rates per unit), freshness (cached hourly), and cost (free). It could be more explicit about what happens when 'codes' is omitted, but overall it is complete enough for basic selection and invocation.

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

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

The schema has zero description coverage for the 'codes' parameter, but the description hints that codes are currency codes (USD/EUR/etc), adding meaning beyond the raw schema. It doesn't explicitly explain the parameter's usage or default behavior, but the implication is 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 clearly states the tool provides live KZT exchange rates per unit of other currencies (USD/EUR/etc), making the resource and action unambiguous. It distinguishes itself from the sibling fx_rates by focusing specifically on KZT.

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 tool's purpose strongly implies use for KZT rate lookups, but there is no explicit guidance on when to use this vs. fx_rates or other alternatives. 'Cached hourly' hints at freshness limitations but not usage 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, so description must cover behavior. It mentions 'Compact due-diligence records' and 'Free', but omits read-only status, error handling, rate limits, or output structure. Sparse behavioral disclosure 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?

Exceptionally concise: two short clauses, front-loaded with core purpose. Every word adds value, no redundancy.

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

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

Covers purpose, parameters, and output type, but lacks return-field specifics and error scenarios. Since there's no output schema and no annotations, the description could be slightly more complete for agent decision-making.

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 only shows two string fields with no descriptions. Description clearly explains that 'lei' is for exact legal-entity identifier match and 'q' for name search, providing essential meaning 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?

States it's a global legal-entity lookup via GLEIF open data, with explicit parameter roles ('lei' exact, 'q' name search). Clearly distinguishes from sibling tools like listings, rates, or tracking.

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?

Provides clear context and explains which parameter to use for which lookup type. Does not explicitly mention alternatives or when not to use, but the domain is distinct enough among 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?

No annotations are provided, so the description carries the full burden. It discloses that the tool is public and requires no auth, but it does not describe return format, pagination, or any rate limits. Additionally, the phrase 'catalog of KYA-verified sellers' may be slightly ambiguous given the verified_only parameter, but there is no clear contradiction.

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 sentences, front-loaded with the primary action, and every word earns its place. It is appropriately concise 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 has 4 optional parameters and no output schema, so the description should provide more context about what results to expect or how the search behaves. It only mentions the resource and public access, leaving out important details like result ordering, filters, or pagination, making it incomplete for a search 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 75%, and the description adds no additional parameter meaning beyond what the schema already provides. The category parameter has no description in the schema, and the description does not compensate for that gap, so it adds limited 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 clearly states the action ('Search') and the resource ('the catalog of KYA-verified sellers'), giving a specific verb+resource. It distinguishes from sibling tools like get_listing by the verb, but does not explicitly reference alternatives, so it's clear but not fully differentiated.

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 provides a clear usage context ('Search the catalog') and an important prerequisite ('Public — no auth needed'). However, it does not mention when not to use this tool or point to alternatives such as get_listing for retrieving a specific listing, so guidance on tool selection is only implied.

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

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

No annotations are provided, so the description carries the full burden. It adds valuable behavioral context by stating that the tool uses the official track.kazpost.kz source, that it is free, and that it returns 'status + route events'. While it doesn't explicitly state it is read-only, the verb 'track' implies no side effects, and the return content is specified.

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 concise and front-loaded, with two short sentences totaling 16 words. The purpose is stated immediately, and the added details (official source, return content, free) are valuable without being verbose.

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

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

Given the simple tool with one parameter and no output schema, the description is fairly complete: it covers the purpose, parameter semantics, and expected return content. It lacks mention of error handling or rate limits, but these are not critical for a straightforward tracking 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 input schema only defines a parameter named 'track' with a string type and no description (0% coverage). The description compensates by indicating that the parameter is the barcode for the parcel, providing essential semantic meaning 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 clearly states the tool's function with a specific verb ('Track'), the resource ('Kazakhstan Post parcel'), and the method ('by barcode'). It also distinguishes it from sibling tools by specifying the official source (track.kazpost.kz), which none of the siblings reference.

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 provides clear context for when to use the tool: when you need to track a Kazakhstan Post parcel using its barcode. It doesn't explicitly mention alternatives, but sibling tools are unrelated to parcel tracking, so the usage context is sufficiently clear.

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 of behavioral transparency. It discloses that the validation uses a 'real national checksum' and parses person/entity structure, which goes beyond basic format checking, but it does not specify output format or error behavior for invalid inputs.

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 starts with the action and includes key details about checksum validation, structure parsing, and that the service is free. No unnecessary words.

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 only partially covers the return structure by mentioning parsed fields (birth date/sex, registration) but does not explicitly state how results are returned or handled for invalid inputs. Given the simple one-parameter nature, it is adequate but not fully complete.

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

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

The schema provides no description for the 'iin' parameter (0% coverage), so the description compensates by clarifying that it represents a Kazakhstan IIN/BIN and explaining the parsing behavior. This adds meaningful context beyond the raw string type.

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 validates a Kazakhstan IIN/BIN with a real national checksum and parses its structure, distinguishing it from sibling validate_kz_iban which handles IBAN. The verb 'validate' and resource 'Kazakhstan IIN/BIN' are specific and 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 for anyone needing to validate Kazakhstan IIN/BIN numbers, and the distinction from other validation tools in the sibling list (e.g., validate_kz_iban) provides implicit context. It does not explicitly state when not to use it, but the scope is clear enough.

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 adds a cost-related trait ('Free') and the validation algorithm, but does not disclose the return format (e.g., boolean vs. error details) or any other side effects. This is partial but not complete 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 a single sentence that conveys the purpose and the 'Free' attribute with no redundant information. It is appropriately sized for the tool's simplicity and front-loads the core 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 simple validation tool with one parameter and no output schema, the description gives the core purpose and algorithm but omits the result shape (true/false/error) and any required input format details. It is adequate for a basic understanding but not fully complete for confident invocation without external domain 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 coverage is 0% and the only parameter 'iban' is an undocumented string. The description implies the parameter is the Kazakhstan IBAN to validate, but it does not provide format examples, length constraints, or structural details beyond what the tool name already suggests. The description does not sufficiently 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 clearly states the tool's purpose with a specific verb ('Validate') and resource ('Kazakhstan IBAN'), and explicitly mentions the algorithm (ISO 7064 mod-97 + KZ structure). This distinguishes it from sibling validation tools like validate_iin, which likely targets a different identifier.

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 validating Kazakhstan IBANs but provides no explicit when-to-use or when-not-to-use guidance, nor does it reference alternatives. The context is clear enough for basic usage, but no exclusions or decision rules are offered.

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 for behavioral disclosure. It states the action but does not reveal whether the operation is read-only, what the response contains, or any potential side effects, making the tool's behavior 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 description is a single, concise sentence that efficiently states the core purpose without unnecessary words. It is appropriately front-loaded, though it could benefit from additional context without becoming verbose.

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 is required to explain what the tool returns and any important operational context. It does not do so, leaving the agent with insufficient information to fully understand the tool's results and 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?

The input schema has one parameter, agent_id, with no schema description. The tool description implies agent_id identifies an agent, but it does not clarify the expected format, origin, or any constraints, adding little semantic value beyond the parameter's name.

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's function with a specific verb ('Check') and a specific resource ('agent's Regent identity/KYA status'). It is easy to understand what the tool does, but it does not explicitly distinguish itself from sibling validation tools like validate_iin or lei_lookup.

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 provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, leaving the agent without direction on selecting this tool over similar lookup/validation 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?

No annotations are provided, so the description bears the full burden of behavioral disclosure. It mentions the service is free and uses Open-Meteo, but does not disclose error behavior, rate limits, return format, or what 'range' means (e.g., forecast high/low). This is insufficient 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 concise sentence that immediately conveys the core functionality. There is zero word waste, and the structure is front-loaded with the key information (current weather and range).

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

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

Given the tool's simplicity (only two parameters), the description gives a reasonable sense of what the tool does. However, with no output schema and limited parameter details, it leaves ambiguity about the exact output structure and what '3-day range' includes. It is adequate for a simple tool but has clear 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 description coverage is 0%, so the description must compensate. It explicitly names 'lat/lon' which adds basic semantics, but it does not specify units, valid ranges, or coordinate format beyond the schema's number type. The description provides minimal additional meaning.

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 the tool provides current weather and a 3-day range for a lat/lon coordinate, using Open-Meteo. This is a specific resource and action, and it clearly distinguishes itself from sibling tools like fx_rates and track_parcel.

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 provides no guidance on when to use this tool over alternatives, nor does it mention any exclusions or prerequisites. While the tool's purpose is obvious, there is no explicit usage context.

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