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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds that it returns 'source and context,' but doesn't disclose any other behaviors like pagination or error cases, so it's adequate but not rich.

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 concise sentence with an example, no fluff. It's efficient and front-loaded, earning every character it uses.

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 three parameters and no output schema, the description provides the core purpose and output type, but lacks parameter semantics and usage timing. It's sufficient for a simple lookup but leaves gaps for the optional 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 coverage is 0% and the description provides no parameter explanations beyond examples of code formats. The limit and curriculumType parameters are entirely unexplained, leaving the agent to guess their semantics.

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

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

The description clearly states the tool finds achievement standard codes and returns their source and context, with concrete examples of code formats. This is specific and distinct from sibling tools by focusing on code lookup rather than broader curriculum search.

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

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

The description implies the tool is for finding achievement standard codes, but it doesn't explicitly state when to prefer this over search_curriculum or other siblings. No exclusions or alternative guidance is provided, so usage context is only implied.

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

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds context about 'still being collected separately,' indicating the report may reflect incomplete data. However, it does not clarify the report's format, limitations, or any side effects beyond what annotations imply, so it adds modest value.

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, but it packs substantial detail about the report's content. It is not overly verbose, though splitting into two sentences could improve readability. The core information is front-loaded before the verb, which is acceptable in Korean. Overall, it earns its 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 the tool's simplicity (no parameters, no output schema), the description sufficiently conveys what the report covers. It mentions completeness of certain documents and scope of auxiliary materials, which is the core purpose. Without an output schema, some might expect a clearer description of the return format, but for a simple report tool, this is adequate.

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

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

The tool has zero parameters, so there is no schema to elaborate. The description provides no parameter-related information, which is appropriate. Baseline for 0 parameters is 4, and the description does not need to compensate for missing parameter documentation.

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

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

The description states the tool reports on the completeness of curriculum inclusion and scope of auxiliary materials, which is a clear purpose (a coverage report). It distinguishes from sibling tools that focus on listing, searching, or chunk retrieval. However, it lacks specificity about exactly which documents are covered and the nature of 'auxiliary materials,' so it's not a 5.

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

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

The description implies the tool is for checking coverage/completeness, but it does not explicitly state when to use it versus alternatives, nor does it mention any exclusions. Given the existence of sibling tools (search, list), some inference is possible, but no direct 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by stating that it returns the '원문 청크와 정확한 출처 위치' (original text chunk and exact source location), which is behavioral information not present in the annotations. No contradiction with annotations.

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

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

A single, front-loaded sentence that clearly communicates the tool's purpose and inputs without wasted words. It is concise and efficient, with no redundant information.

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

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

For a simple retrieval tool with 3 parameters and no output schema, the description adequately states what is returned (chunk and source location) but lacks details about maxChars behavior, error conditions, or response format. Given the absence of an output schema, more detail about the return value would improve completeness, but the description is minimally acceptable.

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 mentions sourceId and chunkId as inputs but does not explain their meanings beyond the names, and completely omits maxChars, which controls chunk length. The agent cannot infer syntax or purpose of maxChars from the description, leaving a significant gap.

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

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

The description clearly states the tool's function with a specific verb ('조회합니다' - retrieves) and resource ('educational curriculum chunk'), and explicitly mentions the inputs (sourceId and chunkId) and outputs (original text chunk and exact source location). It distinguishes itself from siblings like search_curriculum by targeting a specific chunk from search results.

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 use after a search ('검색 결과의'), providing clear context that it retrieves a chunk given IDs. It does not explicitly name alternatives or exclusions, but the purpose is evident from the phrasing, making it clear when to use it versus a search tool.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds context about the output fields, but does not disclose additional behavioral traits such as whether it returns all sources, pagination, or ordering. With annotations in place, the description provides minimal extra value but does not contradict them.

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 action and lists the key outputs. Every word is meaningful, with no filler or redundancy. It is appropriately sized for the tool's simplicity.

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 lack of parameters, output schema, and straightforward nature, the description is mostly complete. It identifies all the data points returned, but could be slightly more explicit about the scope (e.g., 'all official sources' or 'current official sources') and whether any filtering applies. However, for a simple listing tool, this is adequate.

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 baseline is 4. There is no parameter information to add, but the description clarifies what the tool returns, which indirectly helps users understand the tool's scope. Since there are no parameters, the description fully covers the semantics.

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

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

The description clearly states what the tool lists: current base date, notifications/supplements, original URL, extraction status, and chunk count. The verb '나열합니다' (list) is specific and the resource is explicit, distinguishing it from sibling tools like search_curriculum or get_curriculum_chunk, which have different purposes.

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

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

No guidance is provided on when to use this tool versus alternatives. It does not mention scenarios where it should be preferred, nor any exclusions or prerequisites. The description only states what it does, leaving usage decisions to inference from the name alone.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds value by specifying the document types searched (고시 원문 vs 해설서) and the exact return fields (자료 유형, 고시·자료명, 쪽수, 목차 경로, 공식 출처 URL), providing useful behavioral context without contradicting annotations.

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 consists of two efficient sentences: the first defines the action and scope, the second enumerates the return fields. There is no repetition, fluff, or irrelevant detail, making it easy to parse at a glance.

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

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

For an 8-parameter tool with no output schema, the description adequately communicates the search domain and result format. It does not describe search semantics like fuzzy matching or pagination, but the annotations and schema defaults (e.g., materialKind default, limit bounds) fill in most gaps, making it complete enough for agent selection.

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

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

Schema description coverage is 75%, meaning most parameters are already explained. The description maps major concepts (중·고등학교, 고시 원문/해설서) to schoolLevel and materialKind parameters, but leaves limit and curriculumType untouched. Since the schema carries most of the semantic weight, the description adds only modest value.

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

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

The description states a specific verb ('검색합니다' – searches) and resource ('중·고등학교 특수교육 교육과정 고시 원문 또는 별도 해설서 청크'), with clear scope. It distinguishes itself from siblings like get_curriculum_chunk and find_achievement_standard by focusing on cross-document search and listing result fields.

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 through the search verb and scope but does not explicitly state when to use this tool over siblings or when not to use it. There is no mention of alternatives like list_official_sources or get_curriculum_chunk, so the agent must infer selection from context.

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