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

No annotations are provided. The description mentions a ValueError for missing material, which adds some transparency. However, it does not disclose idempotency, mutation status, or other behavioral traits.

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

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

The description is concise and well-structured with Args, Returns, and Raises sections. The main purpose is front-loaded in the first 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 tool's complexity (3 params, 2 required, with optional output schema), the description covers all necessary aspects: parameter descriptions, return type, and error handling. No evident gaps.

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

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

Schema description coverage is 0%, but the docstring provides detailed explanations for all three parameters, including the optional dest_dir and its default behavior. This adds significant meaning beyond the schema.

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

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

The description clearly states the tool's action (download lecture materials) and its result (return the save path). It distinguishes from sibling tools like list_materials and submit_assignment_files.

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 does not explicitly state when to use this tool over alternatives or provide prerequisites. It is inferred that it is for downloading a specific material after listing.

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, but description explicitly states it filters to unsubmitted assignments and sorts by deadline. Adequate for a simple retrieval 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?

Two concise sentences plus structured Args/Returns. No wasted words, well-organized.

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 list retrieval tool with one parameter and output schema, description covers purpose, parameter, and return format completely.

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%, but description explains the 'days' parameter as 'Number of days ahead to target deadlines,' adding essential semantic meaning beyond the schema.

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

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

Description clearly states it retrieves upcoming deadlines for unsubmitted assignments in order. Differentiates from siblings like list_assignments which may not filter by deadline or submission status.

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?

Context is clear: use to view upcoming unsubmitted deadlines. No explicit when-not, but siblings provide context for alternatives.

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. Description only states it returns a list, with no mention of side effects, permissions, pagination, or ordering. Minimal disclosure for a read operation.

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?

Extremely concise with clear purpose and parameter description. No unnecessary words; front-loaded with key 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?

Given the simplicity (one optional param, output schema exists), the description is functional but lacks details like ordering, pagination, or scope. Output schema likely covers return structure, so completeness is adequate but basic.

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 add meaning. It describes course_id as 'course identifier' and explains behavior when omitted, adding value beyond the schema. However, the description is brief and lacks format 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?

Description clearly states it retrieves a list of announcements and class cancellations, with optional course_id filtering. However, it does not differentiate from sibling list tools like list_assignments or list_materials.

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. The description implies usage for announcements but lacks context 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 only states it gets assignments and returns a list. No disclosure of side effects, authentication needs, or limitations beyond the basic retrieval 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?

Extremely concise and well-structured with Args and Returns sections. Every sentence is necessary and 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?

Adequate for a simple list tool with one optional parameter and an output schema present. Could include more context like typical usage or error handling, but not critical.

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?

Despite 0% schema coverage, the description adds useful semantics: it explains that omitting course_id queries all courses. This compensates for the schema's lack of description.

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 retrieves assignments and deadlines, specifying the optional course_id scope. It implicitly distinguishes from siblings like 'get_upcoming_deadlines' by focusing on assignments, but does not explicitly differentiate.

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 siblings like 'get_upcoming_deadlines' or 'list_courses'. Lacks context or examples for typical usage.

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 behavioral context. It merely states 'get the list' without explicitly mentioning read-only behavior or any side effects. For a simple list, this is acceptable but minimal.

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

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

The description is extremely concise with two sentences, no wasted words. It front-loads the main action and includes a return statement.

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 no parameters and an output schema exists (covering return value details), the description is sufficiently complete for its simplicity. It could hint at what is included in 'list of courses,' but the output schema likely covers that.

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?

There are no parameters, so schema coverage is 100% trivially. Per guidelines, baseline is 3. The description adds no parameter information, which is fine as there are none.

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 '取得する' (get) and resource '履修中のコース一覧' (list of enrolled courses). It distinguishes itself from sibling tools that operate on specific sub-resources like assignments or materials.

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 on when to use this tool versus alternatives. It is adequate as a basic list query but lacks context such as prerequisites or cases where another tool 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?

No annotations are provided, so the description must fully disclose behavior. It states it 'retrieves' a list, implying a read-only operation, but does not mention any other behavioral traits such as permissions, error handling, rate limits, or whether it is destructive. For a tool with no annotations, this disclosure 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 extremely concise with three short sections: overall purpose, args, and returns. Every word serves a purpose, and the structure is clear and easy to parse. There is no extraneous information.

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

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

For a simple tool with one parameter and a read operation, the description is minimally adequate. It mentions that output is a 'list of lecture materials,' but since an output schema exists (context signal), the burden on the description for return values is reduced. However, it lacks context on what materials are included or how to interpret results. Overall, it is acceptable but not comprehensive.

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%, meaning the schema provides no descriptions for parameters. The description only restates 'course_id' as 'コースの識別子' (course identifier), adding no meaningful semantic value beyond the parameter name. This does not help an agent understand expected format or constraints.

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 a list of lecture materials for a specified course, using a specific verb ('取得する') and resource ('講義資料一覧'). It distinguishes from sibling tools like 'download_material' (download) and 'list_assignments' (assignments), making its purpose unambiguous.

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

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

The description indicates the tool requires a course_id, implying use when you have a course and need materials. However, it does not explicitly state when to use this tool versus alternatives like 'list_assignments' or 'list_announcements', nor does it specify prerequisites or conditions.

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 confirm=False does not write to Moodle and returns preview, while confirm=True performs actual submission. It also mentions ValueError for invalid files. However, it does not specify if submission is irreversible or any permission requirements.

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 well-structured with sections for Args, Returns, Raises. It is slightly verbose but every sentence adds value. Could be trimmed slightly without losing clarity.

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 presence of output schema, description adequately covers workflow, parameters, and exceptions. It could mention how to obtain assignment_intro, but overall complete for a submission 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?

Despite 0% schema coverage, the description's Args block fully explains each parameter: assignment_id (from list_assignments), file_paths (local paths), confirm (default false for preview). This adds significant meaning beyond the schema.

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

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

The description clearly states the tool's purpose: 'Submit files to assignment (2 steps: default is preview)'. It uses a specific verb ('submit') and resource ('assignment files'), and distinguishes from sibling tools which are primarily read/list actions.

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 explicitly explains the two-step workflow: use confirm=False for preview (no write) and confirm=True for actual submission. It instructs to verify files against assignment_intro before confirming, providing clear when-to-use guidance.

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