Brightspace MCP Server

by RohanMuppa

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.7
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific Brightspace resources like courses, assignments, announcements, or files. The descriptions explicitly define unique use cases, such as get_announcements for news versus get_upcoming_due_dates for deadlines, with no overlap that could cause confusion.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., get_announcements, download_file, check_auth), using snake_case uniformly. The naming convention is predictable and readable, making it easy for agents to understand each tool's function at a glance.
Tool Count5/5
With 12 tools, the server is well-scoped for a Brightspace LMS integration, covering essential academic functions like course management, content access, and grading. Each tool earns its place by addressing a specific need without being overly broad or sparse.
Completeness4/5
The tool set provides comprehensive coverage for core Brightspace workflows, including CRUD-like operations for courses, assignments, and discussions. Minor gaps exist, such as the lack of tools for creating or updating announcements or assignments, but agents can still perform most common tasks effectively.
Average 4.3/5 across 12 of 12 tools scored. Lowest: 3.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 3 of 3 community issues answered or closed in the last 6 months
- 18 commits in the last 12 weeks
- Last stable release on February 20, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters3/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
Behavior2/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters3/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
Behavior3/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters3/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool fetches due dates and includes assignments, quizzes, and other items within a configurable time window. However, it does not specify the output format, potential side effects (none expected), or authentication requirements, but the basic behavior is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences only: the first defines the action and scope, the second provides usage guidance. No extraneous information, front-loaded with essentials.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately explains the tool's purpose and parameters. It mentions the types of items returned (assignments, quizzes). For a simple fetch tool, this is sufficient, though it could hint at the output structure (e.g., dates and names).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters described. The description adds value by specifying that the tool returns assignments, quizzes, and other items, which goes beyond the schema. It also clarifies the default behavior (across all courses) and the optional courseId filter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches upcoming due dates across all courses, showing assignments, quizzes, and other items within a time window. The verb 'fetch' and resource 'upcoming due dates' are specific, and it distinguishes from siblings like 'get_assignments' which might provide more detail but not time-bound due dates across courses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to use this tool when the user asks about deadlines, what's due, upcoming work, or what's needed this week. This provides clear context, though it lacks mention of when not to use it or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters5/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Though no annotations exist, the description indicates a read operation ('fetch') and specifies it returns data for the current user. It could mention if authentication is required or any rate limits, but the core behavior is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that are front-loaded with purpose followed by usage guidance. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input schema and no output schema, the description adequately explains the return content (names, codes, IDs) and the activeOnly parameter. Sufficient for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single boolean parameter already described. The description adds no extra meaning about the parameter beyond the schema definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches the user's enrolled Brightspace courses with specific fields (names, codes, IDs). It is distinct from sibling tools that handle announcements, assignments, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit use cases are provided: user asks about courses, enrolled classes, semester schedule, or needs a course ID. While no alternative tools are mentioned, the context makes it clear this is the only course-listing tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters4/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
Behavior3/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters5/5
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.
Purpose5/5
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.
Usage Guidelines5/5
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.
Behavior4/5
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.
Conciseness5/5
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.
Completeness4/5
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.
Parameters5/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
Behavior4/5
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.
Conciseness5/5
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.
Completeness5/5
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.
Parameters4/5
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.
Purpose5/5
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.
Usage Guidelines4/5
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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full transparency burden. It discloses the default privacy behavior (only instructors/TAs), the optional full list via includeStudents, and the return content (names, emails, roles). However, it does not mention authentication requirements, rate limits, or potential side effects, which is acceptable for a read-only query tool returning structured data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two clear, concise sentences. The first states the core function and data returned, the second provides usage guidance and default behavior. Every sentence serves a purpose, and the information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, no output schema, no annotations), the description is mostly complete. It covers the return content, default behavior, and parameter usage. The absence of an explicit output schema is mitigated by describing the return fields (names, emails, roles). It could mention pagination or error conditions, but for typical roster queries this is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all three parameters described). The description adds value by explaining the default for includeStudents ('Default is instructors and TAs only') and the purpose of searchTerm ('filter by name'). This goes beyond the schema's description of 'Optional search term to filter by name' by providing usage context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the verb 'Fetch' and the resource 'roster', and lists included roles (instructors, TAs, optionally students) and data fields (names, emails, roles). This clearly differentiates from sibling tools like get_classlist_emails (likely only emails) and get_my_grades (grades data). The purpose is specific and distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: 'when the user asks about classmates, instructor contact info, TA emails, professor names, or who's in a class'. It also notes the default behavior (only instructors/TAs) and when to use includeStudents for full list. This gives clear guidance on when and how to use the tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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.
Conciseness5/5
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.
Completeness5/5
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.
Parameters4/5
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.
Purpose5/5
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.
Usage Guidelines5/5
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.

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