seoultech_c4t

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

With no annotations, the description carries the full burden. It discloses the filter criteria (unsubmitted or unconfirmed) and ordering (by deadline), which is useful. However, it omits any mention of prerequisites (e.g., login required) or side effects, and does not clarify behavior when course_id is null.

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, well-structured sentence that front-loads the core filter and ordering. There is no unnecessary verbosity; every word earns its place.

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

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

For a simple tool with one optional parameter and an output schema, the description is adequate in stating the core behavior. However, it lacks any explanation of the course_id parameter and does not address whether login is required, which are important gaps given the absence of annotations.

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

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

The schema description coverage is 0%, so the description must explain the parameter course_id. It does not mention it at all, leaving the agent without any understanding of how this optional parameter affects the result set.

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 assignments that are unsubmitted or have unconfirmed submission status, ordered by deadline. It specifies a distinct filter (pending assignments) which differentiates it from a general list_assignments tool, though it does not explicitly name the alternative.

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

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

The description provides no guidance on when to use this tool versus siblings like list_assignments or get_upcoming_deadlines. It does not mention exclusions or alternative selection criteria, leaving the agent to infer the appropriate context.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the core behavior—returning unsubmitted assignments with upcoming deadlines—but does not mention whether course_id filtering applies, how results are ordered, whether pagination exists, or any side-effect considerations. The read-only nature is only implicit in '조회한다'.

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

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

A single compact Korean sentence that front-loads the operation and the main filter. There is no filler, repetition, or redundant detail.

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 read-only tool with only two optional parameters and an output schema, the definition is mostly adequate, but it omits course_id semantics and any usage guidance relative to sibling tools. The output schema covers return-value structure, so that absence is not a gap.

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

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

Schema description coverage is 0%, so the description must compensate for both parameters. It indirectly clarifies 'days' through '지정한 일수', but it never mentions the course_id parameter or how it filters results, leaving that entirely to inference from the parameter name.

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

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

The description uses a specific verb (조회한다) and a precise resource (미제출 과제, unsubmitted assignments), with a clear time-window condition: deadlines within a specified number of days from today. This is enough to distinguish it from the broader list_assignments and from get_pending_assignments.

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 guidance about when to prefer this tool over siblings such as list_assignments or get_pending_assignments. The time-window condition implies a use case, but no alternatives, exclusions, or prerequisite conditions are stated.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns assignments, deadlines, and submission status, and that it can filter by course. However, it does not disclose behavior around the include_completed parameter (e.g., default false means completed assignments are excluded), nor any pagination, ordering, or side effects. For a read-only query tool, this is a moderate gap.

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 in Korean, front-loading the main purpose and scope. It is efficient and easy to parse. It could be slightly more structured by separating the filtering options, but it earns its place.

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

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

The tool has an output schema, so return values are presumably documented there. The description covers the main query dimensions (all/specific course, deadlines, submission status). However, given the sibling tools get_pending_assignments and get_upcoming_deadlines, the description should clarify how this tool differs (e.g., it lists all assignments including completed ones if include_completed=true, while siblings focus on pending/upcoming). This missing differentiation makes it incomplete for an agent to choose correctly.

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

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

Schema description coverage is 0%, so the description must compensate. It explains course_id implicitly ('지정한 과목' - specified course) and mentions submission status, which relates to include_completed. However, it does not explain the exact meaning of include_completed (whether it includes or excludes completed assignments) or the default behavior. The description adds some meaning but leaves a key parameter ambiguous.

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

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

The description states a clear verb ('조회한다' - retrieves) and resource (assignments), and specifies the key attributes returned (과제, 마감일, 제출 여부 - assignments, deadlines, submission status). It also distinguishes between all courses and a specified course. However, it doesn't explicitly differentiate from sibling tools like get_pending_assignments or get_upcoming_deadlines, which also deal with assignments.

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 context: use this to view assignments for all or a specific course, with deadlines and submission status. It does not explicitly state when to use this vs. get_pending_assignments or get_upcoming_deadlines, nor does it mention the include_completed parameter's role in filtering. The context is clear but exclusions/alternatives are not addressed.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly signals a read-only operation ('조회한다') and scopes the result to currently enrolled courses)Skip... It does not mention authentication, pagination, or ordering, but those are less critical for a simple list tool and the output schema 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?

The description is a single, front-loaded sentence that states the operation and the resource precisely. Every word earns its place, and there is no redundant or promotional content.

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 zero-parameter read-only list tool with an output schema, the description is fully sufficient. It tells the agent what will be returned (currently enrolled courses) without needing additional explanation of return structure or 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?

The tool has zero parametersasterisk, so parameter documentation is unnecessary. The schema coverage is 100% by definition and the description does not need to compensate for any parameter 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?

The description uses a specific verb and resource: '조회한다' (retrieves) and '현재 수강 중인 과목 목록' (currently enrolled course list). This clearly distinguishes it from sibling tools like list_notices and list_assignments, which operate on different resources.

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 when the current enrolled courses are needed, but it does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. The context is reasonably clear but relies on inference from the tool name and sibling names.

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 carry the full burden of behavioral disclosure. It only reveals that the result includes publication date and full text; it does not explicitly state read-only semantics, pagination behavior, or any prerequisites. '조회' weakly implies a query but is not a clear behavioral guarantee.

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 Korean sentence that states the action and scope with no filler. It conveys the essential purpose in one breath.

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

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

For a tool with two optional parameters and an output schema, the description should explain how parameters alter the result. It fails to explain include_content and never mentions ordering or pagination. The main gap is the unexplained boolean parameter.

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 is the only source of parameter meaning. It clarifies course_id as 'all courses or specified course' but says nothing about include_content, which remains ambiguous. The mention of 'full text' might hint at include_content, but doesn't explain the parameter's effect.

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 '조회한다' (retrieves) with a clear resource (notice list) and scope (all or a specified course), and even notes the included fields (publication date, full text). It does not explicitly contrast with sibling 'search_notices', but the listing nature is evident.

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

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

No guidance is given on when to use this tool versus 'search_notices' or other siblings. It neither states when to prefer this tool nor when not to use it, leaving the selection decision entirely to the agent.

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

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

No annotations are provided, so the description carries the full burden. It discloses that this is a read-style search and that results include a publication date, but it does not mention auth needs, course scoping behavior, or what happens when no results match.

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 compact sentence that front-loads the core action and result detail with no filler. Every word earns its place.

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

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

The output schema covers return values, so the extra note about posting dates is a bonus. However, the description remains incomplete around optional course_id semantics and when to use this tool versus list_notices, leaving the agent to infer those details.

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

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

Schema description coverage is 0%, so the description must compensate. It adds some meaning for query by clarifying that search targets the full notice body, but it does not explain the optional course_id parameter or how it filters 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?

Description states a specific action (search across full notice text) and a concrete output detail (returns each result's posting date). It clearly distinguishes from sibling list_notices by focusing on full-body search rather than listing.

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 full-text searching of notices, which distinguishes it from listing or deadline-oriented siblings. However, it does not explicitly state when to prefer this over list_notices or mention any prerequisites such as an active login.

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 must carry the full behavioral burden. It does disclose the core behavior: opening a user-facing Chrome window for manual login. However, it does not mention whether the call blocks until login completes, what happens on cancellation, or how the agent knows the login succeeded.

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, well-structured sentence that front-loads the condition ('when session is missing or expired') followed by the action. Every word adds value and there is no redundancy or filler.

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

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

For a simple parameterless tool with an output schema present, the description covers the essential purpose and trigger condition. The only notable gap is the lack of detail about post-call behavior (whether it waits, returns a session status, or raises an error), but the output schema may already document the return value.

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 and schema description coverage is 100%, so there is nothing for the description to add about parameter meaning. The baseline of 4 for parameterless tools applies, and the description correctly needs no parameter details.

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: it opens a Chrome window for the user to log in manually when a login session is missing or expired. This specific verb+resource combination makes it easy to distinguish from the sibling course/notice/assignment listing 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 gives a clear triggering condition: use this when there is no login session or when the session has expired. It does not explicitly name alternatives or when-not-to-use, but the condition alone is sufficient given that the sibling tools are all data-retrieval operations requiring authentication.

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