copilot-cloud-agent-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
The tools cleanly separate into task management (create, get, list, wait) and org permission management (enable, disable, get, set, list). No overlapping purposes; each tool targets a distinct API operation.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_task, get_org_permissions). No mixing of conventions or vague verbs.
Tool Count5/5
11 tools cover two focused domains (task lifecycle and org permissions) without redundancy or bloat. The scope is appropriate for a Copilot cloud-agent server.
Completeness4/5
Task management is well-covered (create, get, list, wait) but lacks a cancel/stop tool, which is a noticeable gap given that `cancelled` is a terminal state. Org permissions are fully covered.
Average 3.8/5 across 11 of 11 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
This repository is archived. Archived repositories automatically receive an F maintenance tier.
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.
Add a glama.json file to provide metadata about your server.
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 are provided, so the description carries full burden. It mentions the HTTP method and required scope but does not disclose idempotency, side effects, or error conditions. The behavioral disclosure is minimal.
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 extremely concise with two lines, front-loading the purpose and providing the API endpoint. Every sentence is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 required parameters, no output schema, and no annotations, the description lacks completeness. It does not explain return values, error cases, or idempotency, leaving the agent with incomplete context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds no parameter-specific meaning. It only implies org and repository_id through the URL pattern but does not explain their types or roles. The agent gains little beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Add one repo to the org's selected cloud-agent list', specifying the verb and resource. While it doesn't explicitly differentiate from disable_repo_for_org, the sibling names imply the opposite action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides the HTTP method (PUT) and required OAuth scope (admin:org), giving some usage context. However, it does not specify when to use this tool versus alternatives like set_org_selected_repos.
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?
With no annotations, the description carries full burden. It discloses the HTTP method (PUT), required scope, and condition. However, it does not explain side effects (e.g., replacing the entire list), reversibility, or error cases. For a mutation tool, more behavioral detail is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with three sentences and front-loaded purpose. Including the full URL may be slightly excessive but not detrimental. No filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, mutation nature, and poor parameter documentation, the description is incomplete. It does not explain return values, error handling, or what happens to existing settings. An AI agent would lack sufficient context for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It does not describe either parameter (org, selected_repository_ids). The description only mentions them implicitly in the URL path, failing to add meaning beyond the schema's basic types.
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 it replaces the org's selected-repos list for cloud-agent access, using the verb 'Replace' and specifying the resource. This distinguishes it from sibling tools like enable_repo_for_org (adds one repo) and disable_repo_for_org (removes one repo), as well as set_org_permissions (broader scope).
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?
Description explicitly notes when the tool is meaningful ('Only meaningful when enabled_repositories=selected') and requires 'admin:org' scope. However, it does not compare to alternatives (e.g., using enable/disable for individual repos) or state when not to use it.
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 required admin:org scope and HTTP method (PUT), implying idempotent update. Lacks details on rate limits or undo behavior, but simple mutation is sufficiently 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 concise sentences, front-loaded with purpose. No unnecessary words or repetitions.
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?
Adequate for a simple 2-param tool with no output schema. Lacks mention of return behavior or error conditions. Missing link that 'selected' requires another tool, but overall functional.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%. Description partially explains enabled_repositories enum values (all, selected, none) but does not clarify that 'org' is the organization name or how 'selected' is managed. No detail on parameter formats.
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 sets whether all, selected, or no repos can use the cloud agent. Distinct from siblings like get_org_permissions (read) and set_org_selected_repos (list selection).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use versus alternatives. The description does not mention that for 'selected' repositories, set_org_selected_repos must be called separately.
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?
Annotations are absent, so the description carries full burden. It explains parameters and returns a Task object, but it does not disclose behavioral traits such as async nature (the task likely runs asynchronously), rate limits, auth requirements, or potential costs. Some transparency is present via parameter explanations, but broader behavioral context is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a concise opening sentence followed by a clear parameter list resembling a docstring. While slightly verbose, each sentence earns its place. It efficiently communicates purpose and parameter details without redundancy.
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?
The description covers all 7 parameters and returns a Task object, but lacks context about async behavior (e.g., that the task may be long-running and requires polling via get_task or wait_for_task). No mention of error states, limitations, or usage scenarios beyond the basic action. Given no output schema, the return info helps but completeness is limited.
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 0%, so the description must compensate. It fully explains each parameter's purpose, including owner, repo, prompt, base_ref, head_ref, model (with known values listed), and create_pull_request. This adds significant meaning beyond the raw schema structure.
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 'Start a new Copilot cloud-agent task on a repository,' identifying the specific verb (start), resource (Copilot cloud-agent task), and scope (on a repository). It also includes the HTTP endpoint and distinguishes from sibling tools like get_task and list_tasks by implying creation vs retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when to use list_tasks or wait_for_task instead, or any context for choosing this tool over others. The description only states what it does, not when or why.
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 the HTTP method, endpoint path, and required scope. It does not describe pagination behavior or side effects, but the 'List' verb implies read-only.
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: one for purpose, one for endpoint and scope. No wasted words.
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?
Given no output schema and missing parameter descriptions, the description lacks completeness. However, the tool is simple and the schema provides defaults for pagination params. Agent might struggle with parameter semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and description fails to explain any parameters (org, page, per_page). It only mentions org in the endpoint path. Agent cannot infer param meanings 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 uses specific verb 'List' and resource 'repos in an org that have cloud-agent access enabled'. It clearly distinguishes from siblings like enable_repo_for_org and disable_repo_for_org.
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?
Description states the purpose and required scope (admin:org). However, it does not explicitly state when not to use or compare with alternatives, but the distinction from siblings is clear.
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, and the description does not mention read-only nature, authentication requirements, or potential side effects. It does disclose the endpoint selection behavior and response structure, which adds some transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two focused paragraphs. The main purpose is front-loaded, but the endpoint explanation could be more compact. Overall efficient.
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?
The description explains the response includes sessions with key fields, which is helpful given no output schema. It covers the main behavior but does not address error responses or null parameter handling.
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?
With 0% schema description coverage, the description adds value by explaining how repo and owner affect endpoint selection and that task_id is required. This provides meaning beyond the raw 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?
The description clearly states the tool retrieves a single task by ID, including its sessions. It is distinct from sibling tools like list_tasks (plural) and wait_for_task, providing a specific verb-resource combination.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions endpoint preference based on parameters but does not explicitly state when to use this tool over alternatives or when not to use it. Usage context is implied rather than explicit.
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 must disclose behavior. It reveals the HTTP method (DELETE) and required scope, which are helpful. However, it does not mention idempotency, error handling (e.g., if repo not in list), or whether the action is reversible. These gaps leave some behavioral ambiguity.
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 extremely concise: two sentences plus a URL and scope requirement. Every word is necessary and front-loaded with the purpose. There is no fluff or 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 the tool's simplicity (removing a repo from a list) and lack of output schema, the description covers the core purpose, auth, and HTTP method. It could be improved by mentioning the expected response (e.g., status 204 No Content) and whether it is idempotent, but overall it is adequate for a straightforward DELETE operation.
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?
The input schema has no descriptions (0% coverage). The description partially compensates by showing the URL path with placeholders for 'org' and 'repository_id', indicating they are path parameters. However, it does not explain what 'repository_id' represents (e.g., GitHub repository ID), leaving some meaning to be inferred.
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 action: 'Remove one repo from the org's selected cloud-agent list.' It uses a specific verb-resource pair and distinguishes from sibling tools like enable_repo_for_org, which does the opposite.
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 specifies a prerequisite: 'Requires `admin:org` scope.' This guides usage by indicating required permissions. It implies when to use (to disable a repo) vs. enable_repo_for_org, but does not explicitly exclude other scenarios.
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 exist, so the description fully carries the burden. It discloses the required admin:org scope, the API endpoint format, and the exact return structure with fields and types. This provides sufficient transparency for an agent to understand the tool's behavior and authorization needs.
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 concise with three focused sentences covering purpose, endpoint, return format, and required scope. No unnecessary 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 simple read tool with one self-explanatory parameter, the description provides all essential information: purpose, scope, and return schema. No output schema exists, but the description compensates with the return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not describe the 'org' parameter beyond its name. While the parameter is self-explanatory, the schema has 0% description coverage, and the description should have added context (e.g., the organization slug or login). This gap lowers the score.
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 retrieves the Copilot coding-agent repo-access setting for an org. It uses a specific verb and resource, and implicitly distinguishes from sibling tools like set_org_permissions or enable/disable operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a read operation but does not explicitly state when to use this tool versus alternatives like list_org_enabled_repos or set_org_permissions. No usage context or exclusions are provided.
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 the description carries full burden. It mentions API version but lacks details on idempotency, rate limits, or side effects. Only minimal behavioral context.
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 with no wasted words. Purpose is front-loaded.
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 zero parameters, an output schema exists, and the description provides a practical tip, it is sufficiently complete for the tool's simplicity.
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 exist, so the description cannot add parameter value beyond the schema. Baseline of 4 applies.
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 returns model strings accepted by `create_task`, which is specific and distinguishes it from sibling tools that deal with tasks, permissions, and repositories.
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 gives explicit guidance on omitting the `model` parameter to use defaults, implying the tool helps identify valid options. However, it does not explicitly say 'use this before create_task'.
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 must fully convey behavior. It explains the scoping logic and parameter filters but does not mention read-only nature, rate limits, or permission requirements. The behavior is adequately transparent for a list operation, though more could be said.
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 concise yet comprehensive. It starts with a clear summary, then conditional logic for API endpoints, followed by a well-organized list of parameters with their meanings. Every sentence earns its place without 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 the complexity (10 parameters, no output schema), the description covers usage and parameter details well. It lacks description of the return format (list of task objects), but for a list endpoint this is often assumed. Overall, it provides enough context for correct invocation.
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?
The schema has 0% description coverage, so the description carries the full burden. It provides detailed semantics for all parameters: owner/repo scoping, state with enumerated values, is_archived, since (ISO 8601), sort/direction options, pagination, and note that creator_id is repo-scoped only. This adds significant value beyond the raw 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?
The description clearly states the tool lists Copilot cloud-agent tasks and distinguishes between repo-scoped and global scope based on owner/repo presence. It also provides the API endpoints. This is specific and differentiates from sibling tools like get_task (single task) and create_task.
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 gives explicit guidance on when to use repo-scoped vs global listing based on the 'owner' and 'repo' parameters. It also lists optional filter parameters. While it doesn't explicitly say when not to use this tool, the context of siblings like get_task or wait_for_task implies its listing purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: it polls, defines terminal vs non-terminal states, specifies default timeouts and poll intervals, and details return values including _meta fields. No contradictions.
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 efficiently structured with a summary, state definitions, argument list, and return value specification. Every sentence adds value without redundancy, striking an ideal balance between detail and brevity.
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 tool's complexity (polling, multiple states, timeout), no output schema, and zero schema parameter descriptions, the description is fully complete. It covers behavior, parameters, returns, and edge cases, enabling correct agent invocation.
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?
Despite 0% schema description coverage, the description provides comprehensive explanations for all 5 parameters: task_id, owner, repo, timeout_seconds, poll_interval_seconds. It clarifies purpose, defaults, and relationships beyond the schema's bare types.
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's purpose: 'Poll a task until it reaches a terminal state, or timeout.' It lists terminal and non-terminal states, distinguishing it from siblings like get_task (single check) and create_task (creation).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains what the tool does but does not explicitly state when to use it over alternatives like get_task or when not to use it. It implies usage by describing its polling behavior, but lacks direct guidance or exclusions.
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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