D2L BrightSpace MCP

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

No annotations are provided, so the description carries full burden. It discloses that the tool downloads (writes) files and mentions user interaction (asking for path/rename). However, it lacks details on overwrite behavior, permissions, size limits, or error handling, which are important for a file download 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?

The description is 4 sentences with no fluff. It immediately states the purpose, then provides usage context, and ends with actionable guidelines. Every sentence 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?

Given 6 parameters, no output schema, and no annotations, the description is thorough in covering purpose, usage, and parameter context. It lacks only minor behavioral details (e.g., overwrite). Overall, it is well-rounded for an agent to use 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 100%, but the description adds significant value: it explains the two types of file sources (course content via topicId vs dropbox via folderId/fileId) and how customFilename works. It also advises on when to use each parameter, going beyond the schema's basic descriptions.

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 'Download a file from course content or assignment submissions to a local directory' with a specific verb ('download') and resource ('file from course content or dropbox submissions'). It distinguishes from sibling tools (no other download tools exist) and provides context for use cases.

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 explicitly says to use this when 'the user wants to download, save, or get a file from Brightspace course content or dropbox submissions'. It includes critical guidance: 'You MUST ask the user where they want to save the file before calling this tool' and suggests suggesting a clean filename, giving concrete examples.

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?

Implies read-only operation via 'fetch', but omits details like recency definition or impact of missing parameters. No annotations present.

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 front-loaded purpose and actionable usage hints. No wasted words.

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 2-parameter tool with no output schema. Could clarify 'recent' timeframe but overall sufficient.

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 already describes both parameters fully (100% coverage). Description adds marginal value by linking courseId absence to cross-course 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?

Clearly states the tool fetches announcements, distinguishes from siblings like get_assignments or get_discussions, and specifies filtering options.

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?

Provides explicit usage examples (announcements, news, updates) but lacks exclusion guidance or 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 are provided, so the description carries the full burden of behavioral disclosure. It clearly states that the tool reads and 'Returns the text itself,' implying a read-only operation rather than a download. It does not mention auth requirements or unsupported file type edge cases, but core behavior is transparent enough 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?

Every sentence earns its place: resource identification, call patterns, use cases, return behavior, and the sibling alternative are all covered in three compact sentences. The core purpose is front-loaded and there is no 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?

Given no output schema and no annotations, the description still covers the main invocation modes, the output nature, the supported file formats via schema, and the key sibling alternative. An agent has enough context to call this tool correctly without further investigation.

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 100%, so the baseline is 3, but the description adds meaningful workflow semantics: 'Call it with just courseId to see which assignments have attachments, then with folderId and fileId to read one.' This clarifies parameter relationships beyond the schema field descriptions.

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 opens with a concrete action and resource: 'Read the files an instructor attached to an assignment,' and names likely file types (PDF, workbook, rubric). It also distinguishes itself from the sibling download_file by contrasting reading versus saving, so an agent can tell them apart without opening schemas.

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 explicit when-to-use conditions: 'when the user asks what an assignment requires, what the instructions say, or to summarize a handout.' It also names the alternative: 'Use download_file instead when the user wants the file saved to disk.' It even prescribes a two-step call pattern, which removes ambiguity.

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 discloses that the operation is a fetch (read-only) and describes returned data. No contradictions; additional behavioral details like authentication or pagination are not critical for a simple read 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 sentences, concise and front-loaded. Every sentence adds value with no redundancy.

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 no output schema, description provides adequate detail about return values (dropbox submissions and quizzes with due dates, status, rubric info). Could mention if results are paginated, but overall sufficient.

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 100% coverage with parameter 'courseId' described. Description adds crucial context: omitting it returns assignments for all enrolled courses. This adds 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 'Fetch assignments and quizzes' with specific resources (dropbox submissions, quizzes) and details (due dates, status, rubric info). It distinguishes itself from siblings like get_course_content or get_my_grades by specifying the data type.

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?

Explicitly states when to use: 'Use this when the user asks about assignments, homework, what to submit, quizzes, or assignment details and rubrics.' Does not mention when not to use or alternatives, but context is clear.

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. 'Fetch' clearly implies a read-only retrieval with no mutation, and the description specifies exactly what data is returned: email addresses for instructors, TAs, and students. It does not mention access requirements or rate limits, but these are less critical for a simple 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?

The description is two sentences with no filler. It front-loads the core action and then provides practical usage context, making it easy for an agent to parse quickly.

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 is simple with one parameter and no output schema. The description adequately explains the return content, but it does not specify the exact return structure (e.g., array of strings vs. objects) or explicitly contrast with get_roster. Overall it is complete enough for effective 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 100%, and the only parameter, courseId, is already documented as 'Course ID to get emails for.' The description adds no additional parameter-level detail beyond what the schema provides, so the baseline of 3 applies.

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 a specific verb and resource ('Fetch all email addresses for everyone in a course') and enumerates the included roles. It does not explicitly differentiate from the sibling get_roster, which may also involve contact information, so it stops short of 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 gives explicit when-to-use scenarios: wanting a list of emails for a class, emailing the whole class, or needing contact info for everyone enrolled. It does not mention when not to use it or name alternatives like get_roster, so it lacks 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. It describes 'fetch' implying read-only, but does not explicitly state no side effects or auth requirements. However, it gives clear behavioral insights on filtering and depth, which is adequate.

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 three sentences, front-loaded with purpose, followed by usage and parameter tips. No wasteful words; 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?

Given 4 parameters, full schema coverage, and no output schema, the description covers key use cases and parameter usage. It mentions the content tree components (modules, topics, files, links), but could provide more detail on the return structure. Still, it's sufficiently 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?

Schema coverage is 100%, baseline is 3. The description adds practical usage guidance for moduleTitle and maxDepth beyond the schema descriptions, such as 'table-of-contents view', improving 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 clearly states the tool fetches a course content tree listing modules, topics, files, and links. It distinguishes from sibling tools like get_assignments or get_discussions by focusing on course materials and structure.

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 explicitly says when to use the tool (user asks about course materials, lecture slides, etc.) and provides parameter guidance (moduleTitle, maxDepth). It does not explicitly state when not to use, but the context is sufficient.

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 focuses on functionality without mentioning behavioral traits like read-only nature, authentication needs, or side effects. For a fetch operation, this is adequate but could be more transparent.

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?

Three sentences. Front-loaded with purpose. No redundant information. Efficiently conveys parameter combinations and usage guidance.

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 100% schema coverage, no output schema, and no annotations, the description is complete for a simple fetch tool. It covers all parameter scenarios. Lacks mention of return format or whether it's read-only, but these are not critical for this 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 already covers all parameters with descriptions. Description adds significant value by explaining how parameters interact hierarchically (e.g., just courseId lists forums, add forumId for topics, add topicId for posts). This clarifies usage beyond individual field descriptions.

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 verb 'Fetch' and resource 'discussion board content for a course including forums, topics, and posts'. It distinguishes from sibling tools like get_announcements and get_assignments which cover different content.

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?

Explicitly states when to use: 'when the user asks about discussion boards, forum posts, class discussions, or wants to see what's been posted.' Provides parameter usage patterns but does not mention when not to 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, the description must carry the behavioral disclosure burden. 'Fetch' clearly indicates a read-only operation and 'your enrolled' defines scope, but it does not disclose authentication requirements, error behavior, or the fact that the result is a list. It is adequate 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?

Two sentences with no redundancy. The first sentence states the core purpose, and the second provides actionable usage triggers. 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 list tool with one optional parameter and no output schema, the description covers the essential context: what is returned and when to use it. It could mention that no other prerequisites exist or how results are ordered, but nothing critical is 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?

The single parameter activeOnly is fully described in the input schema, including its default behavior, so the schema covers the parameter semantics completely. The description adds no parameter-specific guidance, which is acceptable given 100% schema coverage.

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 a specific action ('Fetch') and resource ('your enrolled Brightspace courses') and enumerates the fields returned (names, codes, IDs). It is unambiguously distinct from siblings like get_course_content or get_roster, so an agent can immediately tell what this tool does.

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 explicit triggers: user asks about courses, enrolled classes, this semester, or needs a course ID for other queries. It does not explicitly mention when not to use it or name alternatives, but the use cases are concrete and sufficient for most situations.

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 behavioral traits. It only mentions output format (points, percentages, comments) but does not state that it is a read-only operation, any permissions needed, or side effects.

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, both front-loaded with key information. No unnecessary words.

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 one optional parameter and no output schema, the description provides adequate context: action, scope, output content, and usage hints. Missing explicit read-only declaration, but overall sufficient.

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 100%, with a clear description for courseId. The description adds context about the response but no additional parameter semantics. Baseline 3 is appropriate.

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 fetches grade breakdowns for a specific course or all courses, with specific fields (points, percentages, comments). It distinguishes itself from sibling tools like get_assignments by focusing on grades.

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?

Explicitly lists when to use: when user asks about grades, scores, marks, GPA, academic performance. Does not mention when not to use or alternatives, but the guidance is clear and sufficient.

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 burden of behavioral disclosure. It reveals a key privacy-related default: 'By default returns only instructors and TAs for privacy' and explains that includeStudents provides the full class list. This goes beyond the schema's default value by adding rationale and context. It does not cover permissions or result formatting, but the central behavioral trait is transparent.

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?

Three sentences with no filler. The first sentence states the core operation and scope, the second gives concrete usage triggers, and the third explains the default and how to override it. Every sentence earns its place and key information is front-loaded.

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 fetch tool with no output schema and no annotations, the description plus fully documented schema covers the essential aspects: what is returned, default behavior, and when to use it. It does not mention truncation or search filtering, but those are already explained in the parameter descriptions. Minor gap: no explicit note about the response shape, but the content description suffices.

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 100%, so the baseline is 3. The description adds marginal value by explaining includeStudents in terms of the default privacy behavior, but it does not elaborate on limit, searchTerm, or courseId beyond what the schema already provides. This is adequate but not exceptional.

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 and resource: 'Fetch the roster for a course' and enumerates the contents (instructors, TAs, optionally students) plus names, emails, and roles. It gives clear use cases (classmates, instructor contact info, TA emails, professor names), but does not explicitly differentiate from the sibling get_classlist_emails, so it falls short of 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 explicitly says 'Use this when the user asks about classmates, instructor contact info, TA emails, professor names, or who's in a class,' giving clear context for when the tool is appropriate. It does not name any alternative tool or provide exclusions, so it earns a 4 rather than a 5.

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?

Discloses that the tool returns markdown text, conditionally downloads attachments, and requires user consent for file saving. Without annotations, it covers key behaviors.

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, all essential: purpose, return format, conditional behavior, and critical usage note. No redundancy.

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?

Covers all necessary information for a two-parameter tool: input, output format, conditional download, and user-consent requirement. No output schema needed.

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?

Adds value beyond schema by explaining that downloadPath triggers a download and that the text is markdown. Schema already describes both parameters fully.

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 'Fetch' and the resource 'syllabus/overview text and optional attachment', distinguishing it from sibling tools like get_assignments or get_course_content.

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?

Provides explicit instruction to ask the user for file save location before using downloadPath, but does not explicitly state when not to use the tool or suggest 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does so by detailing the exact mix of items included: due-soon, overdue, not-open, quiz check-items, and submitted work. This goes well beyond a generic 'returns to-do list' and gives the agent a solid model of the tool's behavior, even if it doesn't mention output structure.

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, front-loading the core purpose and then immediately providing practical usage guidance. The category list is dense but structured and easy to parse. There is no filler or repetition of the tool name.

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?

This is a low-complexity read-only retrieval tool with two optional, well-documented parameters. The description covers what the list contains, the scope, and when to use it. Since there is no output schema, the description's enumeration of categories effectively communicates the expected return content. Nothing critical is missing 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 already describes both parameters fully, including defaults, ranges, and meanings, giving 100% schema description coverage. The tool description adds no additional parameter-specific context. Baseline of 3 is appropriate because the schema carries the descriptive load.

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 defines the tool as a prioritized to-do list across all courses, enumerating specific categories like overdue, not-open, and submitted work. This distinguishes it from sibling tools such as get_upcoming_due_dates, which likely only covers due dates. The verb 'get' plus the resource 'to-do list' and the scope 'across all courses' makes the 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 gives explicit usage context: 'Use this first when the user asks what to work on, what's left, or what they should do now.' This tells the agent when to invoke the tool. It does not explicitly name alternatives or provide when-not rules, but the clear trigger phrases are sufficient for most decision-making.

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 disclosure burden. It usefully discloses the submissionStatus values and the UTC ISO date format, including the need to convert to local time. It does not mention sorting, pagination, or the effect of optional filters, but the described behavior is meaningful and goes beyond a generic 'get' statement.

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 compact and front-loaded: it immediately states what the tool returns, then adds valuable detail about statuses and date formatting, and ends with a clear usage directive. No unnecessary words or repetition.

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 that there is no output schema and no annotations, the description covers the core return semantics, including submission statuses and date formats. It could mention optional filtering behavior or default daysAhead, but the schema already documents those defaults and range, so the description is reasonably complete for a straightforward read 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 100%, so the schema already documents both courseId and daysAhead. The description adds context about 'all courses' but does not enhance the meaning of the parameters themselves beyond the schema, so the baseline of 3 is appropriate.

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 and resource: get upcoming due dates across all courses, and clarifies the scope (all courses). It also distinguishes itself from general assignment listing by emphasizing submission status and deadlines, making the tool's purpose clear relative to siblings like get_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 explicitly says 'Use for deadlines and what's due,' which gives the agent clear guidance on when to invoke this tool. It does not explicitly name alternatives or exclusion conditions, but the context is strong enough for selection among the sibling tools.

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