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

No annotations provided, but description implies read-only check and suggests appropriate usage context. Lacks detail on return value or potential error states, but sufficient for simple auth check.

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, dramatically front-loaded. First sentence states purpose, second gives prerequisites, third lists use cases. 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?

For a zero-parameter, no output schema tool, description fully explains what it does, prerequisites, and when to use it. Complements sibling tools well.

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?

No parameters defined; schema covers 100%. Description does not add parameter info, but with zero parameters, baseline is 4 per guidelines.

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 tool checks authentication status with Brightspace. Distinct from siblings which handle file downloads, course content, etc.

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 instructs to run a CLI first, specifies when to use: when user asks about login status or when auth errors occur from other tools.

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

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

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?

No annotations provided; description fails to disclose authentication requirements, side effects, or any behavioral traits. It implies a read operation but without explicit statement, leaving the agent without critical safety cues.

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, no fluff, front-loaded with purpose then usage scenarios. 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?

Simple tool with one parameter. Description covers purpose and usage but omits return format (e.g., list of emails, comma-separated). Adequate but could improve.

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 covers the single parameter with a description. The tool description does not add additional semantic value beyond the schema, meeting baseline for 100% 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 it fetches email addresses for all roles (instructors, TAs, students) in a course. It uses specific verb and resource, and distinguishes from siblings like get_roster by focusing solely on emails.

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 scenarios such as when the user wants a list of emails for a class. Lacks explicit when-not-to-use or alternatives, but the context is clear enough.

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 behavioral disclosure burden. It usefully explains that due dates are derived from assignments and quizzes, which adds context beyond the schema. However, it doesn't describe output shape, timezone handling, or whether past-due items are excluded, which are relevant for this kind of aggregation 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 compact sentences: one states what the tool does and where the data comes from, the other gives clear usage cues. There is no redundancy or filler, and the most important 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?

The description covers the tool's purpose, data source, and usage triggers, which is sufficient for a simple read-only aggregation tool with optional parameters. Since there is no output schema, a little more detail about the returned due-date format would make it fully complete, but the core calling context is well covered.

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 reinforces the default 'across all courses' behavior and the upcoming-time window, but it doesn't add meaningful parameter-level detail 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 uses a specific verb and resource: 'Fetch upcoming due dates across all your courses.' It also clarifies the source (assignments/dropbox folders and quizzes). It doesn't explicitly differentiate from sibling tools like get_assignments, but the aggregated 'across all courses' framing makes the intent clear.

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 trigger conditions: 'when the user asks about deadlines, what's due, upcoming work, or what they need to do this week.' It lacks explicit when-not-to-use guidance or alternative tool names, so it falls just short of a 5.

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