kdata-gate

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 mentions the tool builds a queue with various elements but does not disclose behavioral traits such as idempotency, rate limits, authentication requirements, or side effects. For a creation tool, important behaviors are missing.

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 with two sentences: the first states the main action and components, the second clarifies exclusions. It is front-loaded and avoids unnecessary words, though a bit more structure (e.g., listing components) could improve readability.

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 lack of annotations and output schema, and three undocumented parameters, the description is insufficient. It hints at the output components but does not explain how inputs map to them, nor what the agent can expect from the 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 has three string parameters (offer, category, target_market) with no descriptions and 0% schema coverage. The tool description does not add any meaning to these parameters, leaving the agent without guidance on how to populate them.

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 builds an 'operator-confirmed buyer discovery queue' with specific components (public search links, qualification rules, proof assets, guardrails). It uses a specific verb and resource, and the negative list (no scraping, sending, posting, etc.) helps distinguish from sibling tools, though it does not explicitly differentiate from other build_* tools.

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

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

The description provides a negative list of what the tool does not do, giving some context, but it lacks explicit guidance on when to use this tool versus alternatives. No mention of prerequisites or conditions for use, nor any comparison to 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, description partially discloses behavior by stating it builds a packet and lists included components. However, it does not clarify if this is a mutation or read operation, or what side effects occur (e.g., persistence).

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

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

Two concise sentences with no filler. Front-loaded with specific verb and resource. Every sentence adds value.

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?

Despite low complexity, the description lacks parameter explanation and does not specify the output format (e.g., document, data structure). The agent lacks enough context to fully understand how to use the 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 coverage is 0%, and the description provides no information about the two parameters ('usd_krw', 'target_krw'). The parameter names alone are insufficient for an agent to determine format or required values.

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 clearly states it builds an 'operator-confirmed cash sprint packet' and lists specific components. Explicitly excludes sending, invoicing, and payment collection, distinguishing it from sibling tools like build_invoice_draft_packet.

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 explains what the tool does and what it does not do, indicating it is for building packets, not for sending or invoicing. However, it does not name alternative tools explicitly for those excluded actions.

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 only states 'Official-source mapping only' and negations, but fails to mention whether the tool is read-only or destructive, what side effects exist, or what the output format is.

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 concise sentences, with the primary purpose stated first and boundary conditions immediately after. Every sentence adds non-redundant information, and there is no wasted text.

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 has three parameters with no schema descriptions and no annotations or output schema, the description is insufficient. It does not explain the output format, how the sample is built, what happens if parameters are omitted, or any prerequisites for successful use.

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 any of the three parameters (category, ingredients, target_market) and the description provides no additional meaning about them. This leaves agents guessing how to populate these fields and what values are valid.

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 action ('Build') and specific deliverable ('buyer-ready MFDS K-beauty ingredient source-map sample for Compliance Scout'). It distinguishes from sibling tools by mentioning a unique product and explicitly excludes unrelated services like legal advice or payment collection.

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 boundaries by listing what the tool is not for (e.g., legal advice, import clearance), helping agents avoid misuse. However, it does not explicitly name alternative sibling tools or specify exactly when to use this one over others.

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 provided, so description carries full burden. It mentions 'operator-confirmed' but does not explain behavioral traits like required permissions, side effects, or whether the pack is stored or sent. Only functional boundaries are given.

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

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

Two concise sentences pack the purpose and limitations without any fluff. Every sentence provides value.

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 complexity of building a delivery pack with multiple components and no output schema or annotations, the description lacks detail on process, prerequisites, and outcome. It fails to provide a complete picture.

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?

Six parameters with 0% schema description coverage and no parameter information in the description. The parameter names are somewhat self-explanatory, but the description adds no meaning to them.

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 states a specific verb 'Build' and a specific resource 'operator-confirmed paid delivery scope pack', listing components and explicitly distinguishing from siblings by stating what the tool does not do (start delivery, send files, invoice, or collect payment).

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?

Description implies usage context by listing what the tool builds and excludes, but does not explicitly state when to use this tool versus alternatives or provide conditions for 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?

No annotations are provided, so the description carries the full burden. It describes outputs (list of deliverables) and non-actions (not posting, etc.), but does not disclose behavioral traits like required authentication, rate limits, or whether it modifies existing data. It is transparent about what it produces but lacks deeper behavioral 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?

The description is two sentences with no fluff. The first sentence lists what it builds, the second clarifies limitations. Every phrase adds value, and the structure is front-loaded with the core purpose.

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 has 3 undocumented parameters, no annotations, and no output schema, the description is adequate for purpose and limitations but lacks parameter documentation and return format details. It helps distinguish from siblings but is incomplete for full autonomous use.

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%. The description mentions 'operator-confirmed' but does not explain the three parameters (offer, category, target_market). Their meaning is left to inference, and the description adds minimal value beyond the param 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 states the tool builds listing packs for multiple freelance platforms, listing specific components (copy, price tiers, etc.) and explicitly stating what it does not do (create accounts, post, etc.). This provides a specific verb+resource and distinguishes it from sibling tools like build_delivery_pack or build_sourcing_pack_report.

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 preparing freelance listings but does not explicitly state when to use this tool versus alternatives. The 'Does not' part clarifies limitations but no exclusions or alternatives are mentioned. Usage context is inferred but not directly guided.

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 clearly states the tool produces a draft only and lists actions it does not perform (issue invoice, generate payment link, send, collect). This gives good transparency about its non-destructive, pre-final nature. However, it does not mention any authentication or rate limits.

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

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

The description is a single concise sentence with an additional clarifying sentence about what is not done. It is front-loaded with the core purpose. However, it could be more structured by grouping the listed contents into parameter hints.

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 undocumented parameters, no output schema, and no annotations, the description fails to provide sufficient context. It does not explain required inputs, prerequisites, or return values. The warning about 'draft only' is helpful but leaves many gaps for effective tool 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 input schema has 7 parameters with 0% description coverage. The description mentions 'line items, buyer wording, payment-method placeholders' but does not map these to the parameters (buyer, offer, company, etc.). It adds no semantic meaning beyond the parameter names, leaving the agent to guess their purpose.

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 it builds a 'draft invoice packet' with specific contents like line items and buyer wording, and explicitly lists what it does NOT do (no invoice issued, etc.). However, it does not differentiate from sibling tools like 'build_cash_sprint_packet' or 'build_delivery_pack', which may cause confusion.

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 when to use (when a draft invoice packet is needed) and what it does not do (no actual invoice or payment), but it provides no explicit guidance on when not to use or which alternative tool to consider. The sibling tools are diverse, but none clearly serve as an alternative for issuing an actual invoice.

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 carries full burden. It mentions what the tool does not do (no payment collection, no private endpoint bypass) but lacks details on side effects, permissions, or whether it creates or modifies data.

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

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

Two sentences, first defining purpose with specific components, second adding a behavioral constraint. No冗余, efficient.

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?

Despite listing pack components, description lacks info on output format, parameter effects, and prerequisites. Given no output schema and complex tool, agent is under-informed.

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 description provides no mapping between its listed components (product candidates, trend signal, etc.) and the schema parameters (category, price_band, target_market). Agent cannot infer how inputs affect output.

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 specifies a clear verb ('Build') and distinct resource ('seller-ready Korea sourcing signal pack') with listed components, differentiating it from sibling tools like build_cash_sprint_packet or build_compliance_scout_sample.

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 on when to use this tool versus alternatives such as build_sourcing_pack_report. The warning about payment collection and endpoint bypass is a constraint, not usage advice.

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 full burden. It explicitly lists what the tool does NOT do ('Does not submit to hubs, scrape, invoice, collect payment, or activate Paddle'), providing useful safety and boundary information. It lacks detail on permissions or side effects, but for a build tool, this is sufficient.

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 (two sentences) and front-loaded with the main action. The second sentence listing exclusions is valuable but could be integrated more cleanly. No wasted words, but could use a bullet structure for readability.

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 one parameter and no output schema, the description covers the tool's purpose and non-behaviors adequately. However, it lacks explanation of the output structure ('patterns to copy, gaps to own, listing copy, proof links, source notes, and guardrails') which would help an AI anticipate results. For a complex build tool, this is a minor 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?

The single parameter 'target_market' has no description in the schema (0% coverage), and the description does not elaborate on its format, allowed values, or role. While the purpose context implies it specifies the market, the lack of explicit guidance weakens parameter understanding.

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 ('Build') and clearly defines the resource ('benchmark packet comparing overseas ecommerce/seller MCP patterns against K-Data Gate positioning'). It lists exact outputs (patterns, gaps, etc.) and non-actions, distinguishing it from sibling tools like 'build_buyer_discovery_queue'.

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 comparing overseas MCP patterns against a specific positioning. While it does not explicitly state when not to use or name alternatives, the sibling list shows distinct purposes, and the context is clear enough for an AI to infer appropriate 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?

The description clarifies non-actions (e.g., does not post, submit, DM), which adds transparency. However, it does not disclose behavioral details like side effects, system modifications, or what 'building' entails (e.g., creating a file or returning data). With no annotations, the burden is high, and this is only partially met.

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 with one clear sentence and a list of excluded actions. It is front-loaded with the main purpose. Minor improvement could be structuring the components list more clearly.

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?

While the tool's high-level purpose is stated, the complete lack of parameter documentation and no output schema leaves the tool under-specified. An agent cannot reliably invoke the tool without understanding the parameters, which are critical for 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 0% description coverage for both parameters ('usd_krw' and 'target_krw'), and the description provides no explanation of their meaning or how they relate to building a commercial playbook. This leaves the agent guessing about parameter usage.

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 builds a commercial operator playbook and lists its components (deploy, list, user actions, etc.), distinguishing it from other 'build_*' tools by specifying a unique resource. It is a specific verb+resource combination with explicit inclusions.

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 indicates what the tool does and explicitly lists actions it does not perform, implying usage boundaries. However, it lacks guidance on when to choose this tool over sibling 'build_*' tools, such as 'build_buyer_discovery_queue' or 'build_cash_sprint_packet'.

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 description must carry full burden. It lists report contents and what it does not do, but fails to disclose side effects, authorization needs, rate limits, or output format. The description 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 sentence plus a short clarifying sentence. It is relatively concise with no redundant information, though could be better structured with bullet points.

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 3 undocumented parameters, no output schema, and no annotations, the description is incomplete. It explains the report's content but not how to use parameters, what the return value is, or any prerequisites. The tool's purpose is clear but operational details are 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?

Input schema has 3 parameters (format, category, target_market) with no descriptions and 0% schema coverage. The description gives no information about what these parameters mean, valid values, or how they affect the report. This is a critical 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?

Description clearly states the tool builds a 'sourcing pack report' with specific components (market validation, price context, competition checks, etc.). The verb 'Build' is specific and the resource is well-defined, though sibling differentiation is not explicit.

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 on when to use this tool versus siblings. The 'No checkout, physical purchase, shipping, or profit guarantee' provides a negative boundary but lacks positive usage context or alternative suggestions.

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 provided, so description must disclose behavior. It states the tool does not collect money or trigger Korean purchasing, and describes possible outcomes. However, it omits details about authentication requirements, idempotency, or write operations.

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?

Four sentences, front-loaded with purpose, no wasted words. Each sentence adds distinct value: purpose, differentiation, non-payment constraint, and outcome states.

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?

Despite good purpose clarity, the tool has 10 parameters with no schema descriptions, no output schema, and no annotations. The description only partially covers parameter meanings and omits return structure, error scenarios, and prerequisites, making it insufficient for full understanding.

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% (no property descriptions). Description mentions 'bundled products, quantities, destination address, and seller responsibility consent,' covering only items, ship_to fields, and accepted checkboxes. Other parameters like email, company, buyer_name, target_market, notes are unexplained, leaving semantic gaps.

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 clearly states it creates a multi-item manual Korean buy/shipping exception request for overseas sellers/agents, and explicitly distinguishes from the main product flow, differentiating from sibling 'create_direct_buy_ship_order'.

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?

Description specifies it is for manual exceptions, not the main flow, and notes that it does not collect money or trigger purchasing. It also indicates return states (payment_pending vs review_required). Lacks explicit when-not-to-use but context 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. It discloses that the tool does not collect money or trigger Korean purchasing, and mentions two possible return statuses. However, it does not discuss authentication, rate limits, or side effects beyond creating the exception request.

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 reasonably concise but includes a sentence about K-Data Gate's primary purpose which seems tangential. It could be more streamlined by removing that sentence.

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

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

Given the complexity (15 parameters, no output schema, no annotations), the description fails to provide complete guidance. It does not explain error handling, prerequisites, or how the exception request is processed after creation.

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 should add meaning. It lists high-level data recorded (product, quantity, destination address, consent) but does not explain individual parameters like accepted_b2b_cs, accepted_regulatory_notice, or formatting requirements. With 15 parameters, this is insufficient.

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 creates a manual Korean buy/shipping exception request for overseas sellers. It specifies what it records and what it does not do (collect money, trigger Korean purchasing). However, it does not explicitly differentiate it from the sibling tool 'create_buy_ship_cart_order', which may have similar functionality.

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 manual exceptions when not wanting to collect money, but does not explicitly state when to use this tool versus alternatives like create_buy_ship_cart_order. No exclusions or when-not-to-use guidance is 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?

With no annotations, the description carries full burden. It discloses that the mapping is from official sources only and disclaims legal advice. However, it omits details such as authentication requirements, rate limits, error handling, or what happens for unmatched queries.

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 concise sentences: first states the core purpose, second clarifies limitations. No unnecessary words, all content is relevant.

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 5 undocumented parameters and no output schema, the description is insufficient for effective tool usage. It lacks parameter guidance and return value expectations, leaving agents with incomplete information.

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 five parameters (q, cas, claim, country, ingredient). An agent cannot determine how to use each parameter or their relationships from the description alone.

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 clearly states the tool performs a lookup of MFDS cosmetics ingredient source mapping for K-beauty sellers. The verb 'Lookup' is specific, and the resource is uniquely identified, distinguishing it from sibling tools that deal with stocks, real estate, or other data.

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?

Description provides context that the tool is for K-beauty sellers and explicitly states it is not legal advice or import clearance, setting appropriate expectations. However, it does not explicitly mention when to use this tool versus alternatives, though sibling tools are sufficiently different.

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, and the description does not disclose any behavioral aspects such as data freshness, rate limits, authentication needs, or whether the tool is reversible. It merely states the action without additional 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 extremely concise (one sentence), but it sacrifices necessary detail. While there is no waste, it is under-specified for effective use.

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 absence of annotations, output schema, and parameter explanations, the description is insufficient for an agent to understand the tool's full capability and constraints. It lacks completeness for a tool with two unexplained parameters.

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

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

With 0% schema description coverage and no parameter details in the description, the meaning of 'period' and 'indicator' is entirely ambiguous. The description adds no semantic value beyond the schema's structure.

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 Korea FX rates and macro indicators, specifying both the domain (Korea) and the data type. This distinguishes it from sibling tools like get_korean_stock_prices or get_korea_real_estate.

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, nor are there any prerequisites or contextual cues. The description simply states what it does without any 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?

The description mentions the source (DART) and language (English), but does not disclose whether the tool is read-only, any authentication requirements, or response characteristics. Without annotations, the description carries the full burden and falls short.

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 lacks depth. For a tool with three parameters and no output schema, it is underspecified.

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 lack of annotations, output schema, and parameter descriptions, the description is incomplete. It does not provide enough context for an 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?

Schema description coverage is 0%, and the description does not explain any of the three parameters (corp, year, report). The agent receives no guidance on parameter meaning or valid values.

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 it retrieves Korean company profiles and filings (DART) in English. This verb+resource combination distinguishes it from sibling tools like get_korean_stock_disclosures, which focus on stock-specific data.

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. There is no mention of prerequisites, context, or scenarios where this tool should be preferred.

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 states that disclosures are 'summarized in English', hinting at a translation/summarization behavior, but does not disclose whether it is read-only, auth requirements, rate limits, or what the output format is. For a tool with 5 parameters, this is insufficient.

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 does not earn its place due to vagueness. It lacks necessary detail and structure, such as parameter explanations or usage context.

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 5 undocumented parameters, no output schema, and no annotations, the description is severely incomplete. It fails to provide sufficient information for correct usage, leaving the agent with minimal understanding of how to invoke the 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 coverage is 0%—none of the 5 parameters (corp, report, ticker, date_to, date_from) have descriptions. The tool description adds no meaning beyond the schema. The agent has no idea what each parameter represents.

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 clearly states 'Get Korean DART equity disclosures summarized in English', specifying a specific verb and resource. It distinguishes from sibling tools like get_korean_company_filings by mentioning DART, a specific Korean disclosure system, and the summary in English. However, it lacks explicit differentiation from similar tools.

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

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

No guidance on when to use this tool versus alternatives. There is no mention of prerequisites, context for usage, or exclusions. The agent receives no help in deciding between this and sibling tools like get_korean_company_filings.

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 fully disclose behavior. It only states it 'gets' data but does not mention read-only nature, rate limits, authentication needs, or pagination. The minimal description is insufficient for safe invocation.

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 of 12 words, which is concise, but it lacks structure and important details. It is front-loaded but under-specified.

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 5 parameters, no output schema, and no annotations, the description is critically incomplete. It fails to explain the returned data, filtering behavior, or any constraints, making it inadequate for reliable tool 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 input schema has 5 parameters with 0% documentation coverage. The description adds no information about valid values, formats, or semantics (e.g., market codes, date format, investor types). The agent must guess parameter usage.

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 verb 'Get' and lists specific data types (investor flow, program trading, short, lending data). However, it does not differentiate from sibling tools like get_korean_stock_prices or get_korean_stock_fundamentals, which are distinct in purpose.

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. There is no mention of context, prerequisites, or exclusions, leaving the agent without decision support.

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 full burden. It does not disclose behavioral traits such as whether the operation is read-only, authentication requirements, rate limits, or what data format is returned. The description only states the action, omitting important behavioral 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?

The single-sentence description is concise and front-loaded, but it lacks structure and additional informative content. It could be improved without much added 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?

Given five parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain what fundamentals are returned, how parameters interact, or any usage context. The tool's complexity is not addressed.

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 any parameter details (e.g., how to specify the stock via corp, ticker, year, quarter, metric). The five parameters are entirely undocumented, adding no semantic 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 'Get Korean stock fundamentals and valuation ratios' clearly states the verb ('Get'), resource ('Korean stock fundamentals and valuation ratios'), and implies distinction from sibling tools like get_korean_stock_prices. However, it does not specify which fundamental metrics are included, slightly reducing clarity.

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 similar tools like get_korean_stock_overview or get_korean_stock_screeners. There are no exclusions or context for optimal 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?

With no annotations provided, the description carries full burden. It only states 'Get' without disclosing whether the operation is read-only, destructive, or any side effects. No mention of authentication, rate limits, or return 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?

The description is extremely concise (6 words) but at the expense of informativeness. It does not provide enough detail to be useful, making it under-specified rather than efficiently concise.

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 three optional parameters and no output schema, the description is incomplete. It does not explain what the tool returns, how parameters filter results, or any example usage. The description is insufficient for effective agent use.

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 adds no meaning to the three parameters (market, sector, ticker). It fails to explain what values are valid or how they affect the results.

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 'Get Korean stock market overview rows' with a clear verb and resource, but it is vague and does not differentiate from sibling tools like get_korean_stock_prices or get_korean_stock_fundamentals. It lacks specificity about what 'overview rows' entails.

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 other Korean stock tools. There are no when-not scenarios or alternative suggestions.

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 but only states the output type (OHLCV, traded value). It does not disclose whether data is for a single date or range, authentication requirements, rate limits, or pagination 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?

Description is a single, front-loaded sentence that conveys the core purpose without unnecessary words. However, it may be too brief given the complexity of parameters.

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 5 undocumented parameters, no annotations, and no output schema, the description is severely incomplete. It does not explain parameter syntax, data formats, or return structure, leaving the agent with insufficient guidance.

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 for any of the 5 parameters (market, ticker, date_to, adjusted, date_from). The description fails to compensate for the lack of schema docs.

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 explicitly states it retrieves OHLCV and traded value for Korean stocks, making it clear what data the tool provides. It distinguishes itself from sibling tools focused on filings, flows, fundamentals, etc.

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

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

No guidance on when to use this tool versus alternatives like get_korean_stock_overview or get_korean_stock_fundamentals. No prerequisites or exclusions 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?

No annotations are provided, so the description carries full burden. It only says 'Get' (implies read), but does not disclose behavioral traits such as whether it is read-only, what 'derived' means, or any side effects or limitations.

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 only one sentence (8 words), which is too brief to be informative. It is under-specified rather than concise, lacking necessary details.

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 four parameters, no output schema, and no annotations, the description is critically incomplete. It does not explain what a screener is, what signals are derived, or how to use the parameters.

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 parameters. It does not mention any of the four parameters (market, preset, sector, min_volume) or their 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?

The description states 'Get derived Korean equity screening signals,' which is a verb+resource, but 'derived' and 'screening signals' are vague. It does not clearly distinguish from sibling tools like 'get_korean_stock_overview' or 'get_korean_stock_fundamentals.'

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 alternatives. The description lacks any context about scenarios, prerequisites, or exclusions.

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

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

No annotations are present, so the description carries full burden. It only states what it does (get records) but does not disclose if it is read-only, any rate limits, data freshness, or potential side effects. For a read operation, basic guarantee of safety is missing.

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, front-loaded with key information. Every word contributes to the purpose. However, it could be slightly expanded without losing conciseness to add parameter hints.

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 (2 string params, no output schema, no annotations), the description lacks completeness. It does not explain the output format, potential errors, or parameter constraints, making it insufficient for reliable agent use.

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 description must explain parameters. It mentions 'apartment transaction records' but does not clarify the expected format for 'region' (e.g., city/county) or 'yyyymm' (e.g., '202401'), nor provide examples. This leaves the agent to guess.

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 verb 'Get', the resource 'Korean apartment transaction records', and the data source 'MOLIT' with language 'English'. However, it does not differentiate from sibling tools like get_korea_weather or get_korean_stock_prices, but the resource is specific enough.

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. There is no mention of context, prerequisites, or exclusions.

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

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

With no annotations, the description carries full burden for behavioral disclosure. It only states 'Get' implying read-only but does not mention any behavioral traits such as rate limits, authentication, or response 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 a single short sentence, which is concise but lacks detail. It is not wasteful, but could be expanded with parameter hints 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?

Given 3 undocumented parameters, no output schema, and no annotations, the description is highly incomplete. An agent cannot determine valid parameter values, defaults, or the structure of results.

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 three parameters (area, lang, type) with no descriptions. Schema description coverage is 0%, and the tool description provides no additional meaning or examples for these parameters, leaving the agent without guidance on how to populate them.

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 verb 'Get', the resource 'Korean tourism places and attractions', and the scope 'in English'. This distinguishes it from sibling tools like get_korea_weather or get_korean_stock_prices.

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 usage guidance is provided. The description does not indicate when to use this tool versus alternative tools for Korean data, nor are there any prerequisites or exclusions 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 provided, the description carries the full burden of behavioral disclosure. It states that the tool gets trend indices, implying a read-only operation, but does not mention any important behavioral traits such as rate limits, authentication requirements, data freshness, or whether results are cached. The description is too sparse to adequately inform an agent about side effects or limitations.

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 very short at one sentence, which could be acceptable if it were complete, but it omits crucial details about parameters and usage. It lacks structure such as separate sections for behavior or examples. The brevity results in under-specification rather than conciseness.

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 has 3 unannotated parameters, no output schema, and no parameter descriptions, the description is severely incomplete. It does not explain what the output looks like (e.g., time series data), how to interpret the trend indices, or the role of the parameters. For a tool with such sparse structured metadata, the description must provide comprehensive context, which it fails to do.

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 by explaining the parameters. However, the description only mentions 'for a keyword' but does not elaborate on the 'period' or 'category' parameters, nor does it provide any format, allowed values, or examples. This fails to add meaning beyond the bare schema property 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 states that the tool retrieves Naver search trend indices for a keyword, specifically for viral detection in K-beauty/K-food. The verb 'Get' and resource 'search trend indices' are explicit, and the mention of 'Naver' distinguishes it from general Google trends. However, it does not differentiate from sibling tools like 'get_kbeauty_ingredients' or 'search_korean_products' beyond the specific use case.

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 provided on when to use this tool versus alternatives. The description implies a use case for viral detection in K-beauty/K-food but does not mention other scenarios or compare with sibling tools like 'get_kbeauty_ingredients' or 'search_korean_products'. There is no 'when not to use' or mention of prerequisites.

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 fully carries the burden of behavioral disclosure. It only states it 'gets' data but omits any details about side effects, data freshness, rate limits, or required permissions. Minimal 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, front-loaded sentence with no extraneous words. It efficiently conveys the core purpose.

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 absence of an output schema and the minimal parameter info, the description lacks completeness. It does not explain the output format, possible values for 'type', or how to specify cities. More context is needed for correct invocation.

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

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

The input schema has two parameters ('city', 'type') with 0% description coverage, and the tool description adds no explanation of their meaning, allowed values, or defaults. The agent has no guidance on how to fill these parameters correctly.

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 ('Get') and the resource ('Korean weather conditions and forecasts'). It distinguishes this tool from all siblings, which cover different domains like stocks, real estate, etc. No ambiguity.

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, or any prerequisites. The agent must infer usage solely from the tool's name and context. This lack of explicit guidance reduces usability.

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 traits. It only notes the output format ('English JSON'), but fails to mention any side effects, rate limits, required permissions, error behavior, or pagination. This is insufficient for an agent to safely invoke the 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 extremely concise (one sentence) but at the cost of omitting essential details. While brevity is good, it should front-load key information like parameters and output structure. Here, it sacrifices completeness for brevity.

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 has three undocumented parameters, no output schema, and no annotations, the description is severely incomplete. An agent has no way to know what parameters to use, what values are valid, or what the response looks like. This makes the tool nearly unusable.

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%, yet the description adds no information about the three parameters (q, source, category). It does not explain their purpose, expected values, or how they affect the search. The agent must rely solely on the parameter names, which are ambiguous (e.g., 'source' could mean many things).

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 searches Korean products and lists example categories (K-beauty, K-food, K-pop merch). This distinguishes it from sibling tools that focus on building reports or getting financial data. However, it could be more precise about the scope (e.g., does it cover all Korean products or only those categories?).

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

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

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, expected use cases, or situations where another tool would be more appropriate. The agent is left to infer usage from the name and context.

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