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. 'Fetch' implies a read-only operation, but nothing is disclosed about authentication requirements, rate limits, failure behavior, or the structure/shape of the returned raw 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?

The description is a single concise sentence with no filler. However, it is somewhat under-specified rather than efficiently complete, so it earns high but not full marks.

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

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

For a tool with no output schema and no annotations, the description should explain what the returned data looks like or how the raw data relates to sibling tools. It does neither, leaving the agent without enough context to confidently use the tool beyond making a trivial call.

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

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

Schema description coverage is 0%, and the description does not explain the corp_code parameter beyond what the schema's name and regex pattern already imply. Since the description must compensate for the low coverage but does not, it falls below the baseline.

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 ('Fetch') and a clear resource ('raw OpenDART company registration data'). It is distinguishable from siblings like dart_financial_statements and dart_disclosures, though the word 'raw' is somewhat vague and could mislead about what form the data takes.

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 about when to use this tool versus alternatives such as resolve_dart_company or dart_disclosures. The description does not mention prerequisites like how to obtain a corp_code, nor does it exclude cases where another sibling would be more appropriate.

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 behavioral burden and it does disclose that only one bounded page is returned and that a partial status signals remaining pages. It does not explain return format, error semantics, or whether authentication or intermediate calls like resolve_dart_company are prerequisites.

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

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

The description is a single compact sentence that front-loads the main action and includes a meaningful pagination caveat. It is appropriately brief, though some parameter semantics are sacrificed 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?

For a 5-parameter tool with three required parameters and no output schema or annotations, the one-sentence description is insufficient. An agent lacks enough context about input formats, page size semantics, or what 'partial status' looks like in the response.

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 provides 0% description coverage and the description itself gives no parameter-level meaning. It does not explain what corp_code, start_date, end_date, page_no, or page_count represent or how they interact.

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

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

The description clearly identifies the tool's purpose: fetching a bounded page of raw OpenDART disclosures, and differentiates it from overview/financial-statement sibling tools. It does not explicitly name a sibling, so it misses the full differentiation criterion.

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

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

The description gives no guidance about when to prefer this tool over alternatives such as dart_company_overview or dart_financial_statements. Pagination behavior is hinted at with 'partial status marks remaining pages,' but there is no explicit when-to-use or when-not-to-use context.

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

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

No annotations are provided, so the description must carry the full behavioral burden. It discloses that the tool returns 'raw' statements, but it does not mention prerequisites, authentication, rate limits, response format, report_code semantics, or any caveats about data availability.

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 filler; the verb and resource come first. It is concise, though it omits important parameter and usage details that would make it more effective.

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 four required parameters, no output schema, no annotations, and no parameter coverage, the description leaves too much to inference. An agent cannot reliably select the correct report_code or understand what the returned statements contain or how they differ from sibling tool outputs.

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

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

Schema description coverage is 0%, so the description must compensate, but it only adds meaning for fs_div ('consolidated/separate basis') and partially for corp_code ('single-company'). It leaves business_year and especially the opaque report_code enum values (11013, 11012, 11014, 11011) unexplained.

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

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

The description names a specific verb ('Fetch'), a specific resource ('OpenDART single-company account statements'), and a distinguishing attribute ('explicit consolidated/separate basis'). It is clear and not a tautology, but it does not explicitly position itself against sibling tools such as dart_company_overview or dart_disclosures.

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

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

The description gives no explicit when-to-use guidance, no exclusions, and no mention of alternatives. The phrase 'raw single-company account statements' weakly implies a use case, but an agent receives no help choosing between this tool and the sibling OpenDART/DART tools.

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

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

With no annotations, the description carries the full disclosure burden, but it only states that the tool returns gaps. It does not reveal behavioral traits such as read-only/idempotent behavior, the shape of the returned gaps, data freshness, or whether any external/network dependency exists.

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

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

One sentence front-loads the action and object, with no filler or repetition of the tool name. It is as concise as a zero-parameter tool's description should be.

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 description is sufficient to select the tool, but with no output schema it does not explain what a returned 'gap' looks like, and the acronyms MFDS/CRIS are not expanded. More detail about the output format or the meaning of 'coverage gaps' would make it 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 tool has zero parameters, so the schema is fully covered and no parameter documentation is needed. Per the baseline for a no-parameter tool, the description need not compensate for missing parameter 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 uses a specific verb ('Return') and a concrete resource ('mandatory Korean regulatory coverage gaps'), naming the regulators MFDS and CRIS. This clearly separates it from the sibling DART/KRX tools, which address company data, disclosures, and stock trading.

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 intended use is implied: an agent would call this when coverage gaps under Korean regulations are relevant. There is no explicit when-to-use/when-not-to-use guidance or reference to alternatives, though the sibling tools are distinct enough that confusion is unlikely.

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, but it only mentions 'HTTPS-only' and 'Fetch'. It does not clarify whether the operation is read-only, what data is returned, how missing data is handled, or whether any rate limits or prerequisites apply.

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 focused sentence with no filler. It front-loads the core resource and scope, making it quick for an agent to parse.

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?

There is no output schema and no annotations, so the description alone needs to provide enough context for correct invocation. It fails to explain the return shape, the market parameter, or any behavioral caveats, leaving an agent with an under-specified tool.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions ticker and date, but says nothing about the required 'market' parameter or the meaning of the pattern constraints on ticker and date.

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

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

The description names a specific verb ('Fetch'), a concrete resource ('KRX daily trade data'), and a clear scope ('one ticker/date'). This distinguishes it from siblings like krx_stock_base_info, which covers base stock information rather than daily trade records.

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 about when to use this tool versus the sibling tools. It does not mention alternatives, exclusions, or conditions that would make another tool more appropriate.

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 it only adds the odd 'HTTPS-only' constraint and the singular scope. It does not disclose whether credentials are needed, what happens for missing or invalid inputs, rate limits, or the structure of the returned base information.

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 filler, which is appropriately compact for a simple tool. However, 'HTTPS-only' is awkwardly placed and the omission of any parameter guidance makes it slightly too thin for the three-parameter signature.

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

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

For a tool with no annotations and no output schema, the description should compensate with more context about expected behavior and return values, but it does not. An agent invoking this tool would still need to infer the meaning of 'issue base information,' the market parameter, and the output format.

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

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

Schema description coverage is 0%, so the description was expected to explain the three required parameters, but it only mentions 'one ticker/date' and says nothing about the required 'market' parameter or what the values mean. The schema's patterns and enum are useful, but the description adds little semantic value beyond the singular scope.

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 ('Fetch') and names a concrete resource ('KRX issue base information') scoped to one ticker/date, which is clear in isolation. It does not explicitly differentiate from siblings like krx_daily_trade, and the phrase 'HTTPS-only' is confusingly placed, so it stops short of full sibling distinction.

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

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

There is no statement about when to use this tool versus krx_daily_trade, the DART siblings, or any alternative. The only implied guidance is singularity ('one ticker/date'), but no exclusions, prerequisites, or trade-offs are provided.

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

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

With no annotations, the description carries the behavioral burden. It does disclose the core behavior: resolving a company to a code, implying a lookup/read-style operation. It does not explain behavior around ambiguous matches, simultaneous inputs, or response format, but the basic operation is stated.

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

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

A single focused sentence with no filler. The action and output are front-loaded, making it easy to scan.

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 two-parameter resolver, the description plus the oneOf schema gives a minimally viable picture. Still, there are no annotations and no output schema, and the description omits guidance on which parameter to prefer, so an agent must infer details from the schema alone.

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

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

Schema description coverage is 0%, so the description must compensate. It adds domain context but does not explain the roles of stock_code and corp_name, Korean-name expectations, or precedence between the two parameters. The oneOf schema partially covers this, but the description itself does not.

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?

Uses a specific verb ('resolve'), a specific resource ('Korean listed company'), and a specific output ('OpenDART corporation code'). This clearly distinguishes it from sibling tools like dart_company_overview, dart_disclosures, and krx_daily_trade.

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 purpose implies when to use it: when the agent needs an OpenDART corporation code for a Korean listed company. However, it gives no explicit guidance on when not to use it or how it relates to the sibling tools.

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