DevOps Enhanced MCP

by wangkanai

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific Azure DevOps resources and actions. For example, create-work-item, get-work-items, update-work-item, and add-work-item-comment form a coherent work item lifecycle without overlap, while get-builds, get-pipeline-status, and trigger-pipeline cover distinct pipeline operations. No tools appear to do the same thing.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with hyphens, using clear action verbs like 'get', 'create', 'update', 'add', and 'trigger' paired with specific nouns. There are no deviations in naming conventions, making the set predictable and readable throughout.
Tool Count5/5
With 10 tools, this server is well-scoped for Azure DevOps operations, covering work items, pipelines, repositories, and pull requests. Each tool earns its place by addressing a core DevOps workflow, avoiding both thin coverage and bloat.
Completeness4/5
The tool surface provides strong coverage for key Azure DevOps domains, including CRUD operations for work items and pipeline management. Minor gaps exist, such as no tools for creating or merging pull requests or managing repository branches, but agents can work around these with the available tools.
Average 2.9/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- 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.
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 only states the action without disclosing behavioral traits such as whether it's read-only, requires authentication, has rate limits, returns paginated results, or handles errors. For a tool with 3 parameters and no annotations, this is a significant gap in 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 a single, efficient sentence with no wasted words. It's appropriately sized for a simple tool, though it could be more front-loaded with key details. It earns its place but lacks depth.
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's complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't cover return values, error handling, or behavioral context, leaving gaps for an AI agent to understand how to invoke it correctly. It should do more to compensate for the lack of structured data.
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 description coverage is 100%, so the schema fully documents parameters (wiql, ids, fields). The description adds no meaning beyond this, as it doesn't explain how parameters interact (e.g., wiql vs ids) or provide usage examples. Baseline is 3 since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the basic action ('Get work items') and source ('from Azure DevOps'), which provides a general purpose. However, it lacks specificity about what 'get' entails (e.g., list, retrieve, query) and doesn't distinguish it from siblings like 'create-work-item' or 'update-work-item' beyond the verb difference. It's vague but not tautological.
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. It doesn't mention scenarios like querying with WIQL versus retrieving by IDs, or how it differs from other get-* tools (e.g., 'get-builds', 'get-pull-requests'). The description offers no context for selection, leaving usage unclear.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool adds a comment but lacks critical details: whether this requires specific permissions, if it's a write operation (implied but not explicit), what happens on success/failure, or any rate limits. This is inadequate for a mutation tool with zero annotation coverage.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly, with every part earning its place.
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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain behavioral aspects like authentication needs, error handling, or return values, leaving significant gaps for an AI agent to understand how to invoke it correctly in context.
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 schema description coverage is 100%, with both parameters ('id' and 'comment') clearly documented in the schema. The description doesn't add any meaningful semantic context beyond what the schema provides (e.g., format of ID, comment length limits), so it meets the baseline for high schema coverage without compensating value.
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 the action ('Add a comment') and target resource ('to an existing work item in Azure DevOps'), making the purpose immediately understandable. However, it doesn't distinguish this tool from potential sibling tools like 'update-work-item' that might also handle comments, missing explicit differentiation.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing work item ID), exclusions, or comparisons to sibling tools like 'update-work-item' that might overlap in functionality, leaving usage context unclear.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Create' implies a write operation, the description doesn't address permissions needed, whether creation is idempotent, what happens on failure, or what the response contains. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
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 a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a tool with comprehensive schema documentation and gets straight to the point with zero wasted verbiage.
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?
For a creation tool with 8 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what happens after creation, what permissions are required, or how to handle errors. The agent would need to guess about the tool's behavior and output format based solely on the schema.
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 description adds no parameter information beyond what's already in the schema, which has 100% coverage with detailed descriptions for all 8 parameters. The baseline score of 3 reflects that the schema adequately documents parameters, though the description could have provided additional context about parameter interactions or constraints.
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 the action ('Create') and resource ('new work item in Azure DevOps'), making the purpose immediately understandable. It distinguishes this as a creation tool among siblings like 'update-work-item' and 'get-work-items', though it doesn't explicitly contrast with them in the description text itself.
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?
The description provides no guidance on when to use this tool versus alternatives like 'update-work-item' or 'get-work-items'. It doesn't mention prerequisites, dependencies, or contextual factors that would help an agent decide if this is the appropriate tool for a given situation.
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 are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't cover key traits like whether it's read-only, requires authentication, has rate limits, returns paginated results, or what 'recent builds' means in terms of time range or sorting. This leaves significant gaps for an agent to understand operational behavior.
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 a single, efficient sentence with no wasted words, front-loading the core purpose. It's appropriately sized for a simple retrieval tool, making it easy to parse quickly.
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 lack of annotations and output schema, the description is incomplete for a tool with 2 parameters and no behavioral context. It doesn't explain return values, error handling, or prerequisites, leaving the agent with insufficient information to use the tool effectively in complex scenarios.
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 100% description coverage, clearly documenting both parameters ('definitionIds' and 'top'). The description adds no additional meaning beyond the schema, such as explaining default behaviors or interactions between parameters. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but the description doesn't enhance parameter understanding.
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 the action ('Get') and resources ('build definitions and recent builds'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get-pipeline-status' or 'get-work-items', which also retrieve information but for different resources, so it lacks explicit sibling distinction.
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?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get-pipeline-status' or 'get-work-items' that might overlap in context (e.g., CI/CD workflows), there's no indication of when this tool is preferred or what scenarios it's designed for, leaving usage ambiguous.
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 are provided, so the description carries full burden. It states the tool 'gets' context, implying a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error conditions (e.g., invalid directory), or what 'context' includes (e.g., returns project ID, user info). For a tool with no annotations, this leaves significant gaps in understanding its behavior.
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 a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action and resource, making it easy to parse. Every part of the sentence earns its place by specifying Azure DevOps and the directory basis.
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 complexity (context retrieval tool with no annotations and no output schema), the description is incomplete. It doesn't explain what 'context' means (e.g., project, repo, user details), the return format, or how this integrates with sibling tools. For a tool that likely provides foundational data for other operations, more context on its role and output is needed.
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 1 parameter with 100% description coverage, documenting the directory path and default behavior. The description adds no additional parameter semantics beyond what's in the schema (e.g., doesn't explain how the directory influences context retrieval or format requirements). With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.
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 the action ('Get') and resource ('current Azure DevOps context'), specifying it's based on directory. It distinguishes from siblings like get-work-items or get-repositories by focusing on context rather than specific entities. However, it doesn't explicitly differentiate from all siblings (e.g., doesn't contrast with get-builds or get-pipeline-status).
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., Azure DevOps setup), when this context is needed (e.g., for other operations), or what 'context' entails (e.g., project, organization). With siblings like get-work-items or trigger-pipeline, there's no indication of how this tool fits into workflows.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but only states the basic action. It doesn't cover whether this is a read-only operation, what permissions are needed, how errors are handled, rate limits, or the format of the returned status. This leaves significant gaps for a tool that likely interacts with a CI/CD system.
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 a single, clear sentence with zero wasted words, making it easy to parse and front-loaded with the core purpose. It efficiently communicates the essential function without unnecessary elaboration.
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 complexity of pipeline/status tools, no annotations, and no output schema, the description is insufficient. It lacks details on what the status includes (e.g., success/failure, stages), how to interpret results, or error conditions. This makes it incomplete for effective agent use in a real-world CI/CD context.
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 schema description coverage is 100%, so the input schema fully documents the three parameters (buildId, definitionId, includeTimeline). The description adds no additional parameter semantics beyond what's in the schema, such as explaining relationships between parameters or usage examples, which aligns with the baseline score for high schema coverage.
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 the tool's purpose with a specific verb ('Get') and resource ('status of a specific build or pipeline'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get-builds' or 'trigger-pipeline' regarding when to use each, which prevents a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives like 'get-builds' (which might list multiple builds) or 'trigger-pipeline' (which initiates builds). There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.
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?
With no annotations provided, the description carries full burden but only states the basic operation without behavioral details. It doesn't disclose whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or error handling, which are critical for a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 complexity of retrieving pull requests (which often involves filtering, pagination, and authentication) and the absence of both annotations and an output schema, the description is insufficient. It lacks details on return format, error cases, or operational constraints, leaving significant gaps for effective tool use.
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 100% description coverage, so parameters like 'repositoryId', 'status', 'createdBy', and 'top' are well-documented there. The description adds no additional parameter semantics beyond implying filtering capabilities, meeting the baseline for high schema coverage.
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 the action ('Get') and resource ('pull requests from Azure DevOps repository'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential siblings like 'get-work-items' or 'get-builds' that might also retrieve Azure DevOps data, missing explicit distinction.
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. The description doesn't mention prerequisites (e.g., authentication), context for filtering, or comparisons to sibling tools like 'get-work-items' for different data types, leaving usage decisions ambiguous.
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?
With no annotations provided, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't mention whether this is a read-only operation, if it requires authentication, rate limits, pagination, or what the response format looks like (e.g., list of repositories with details). This leaves significant gaps for a tool with potential complexity.
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 a single, efficient sentence that front-loads the core purpose without unnecessary words. It earns its place by clearly stating what the tool does, making it appropriately sized and well-structured.
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 annotations, no output schema, and a simple parameter set, the description is incomplete. It lacks details on behavioral aspects (e.g., safety, response format) and doesn't compensate for the absence of structured data, making it inadequate for full agent understanding in a context with sibling tools.
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 100% description coverage, with one parameter (includeLinks) fully documented in the schema. The description adds no additional parameter information beyond the schema, so it meets the baseline of 3 for high schema coverage without compensating value.
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 the action ('Get') and resource ('repositories'), specifying the source ('from Azure DevOps project'). It distinguishes from siblings like get-builds or get-pull-requests by focusing on repositories. However, it doesn't specify scope (e.g., all repositories vs. filtered), which prevents a perfect score.
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 like get-work-items or get-pull-requests. The description implies usage for retrieving repositories but lacks context on prerequisites, filtering needs, or explicit exclusions, leaving the agent to infer based on tool names alone.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('trigger') but doesn't cover critical traits like whether this is a mutation (likely yes), authentication requirements, rate limits, side effects (e.g., starting a build consumes resources), or response format, leaving significant gaps.
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 a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.
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's complexity (triggering a build pipeline is a mutation with potential side effects), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects, usage context, or what to expect after invocation, which are crucial for an agent to use it correctly.
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 description coverage is 100%, so the input schema fully documents all 4 parameters. The description adds no parameter-specific information beyond implying a pipeline is triggered, which is already covered by the tool name and purpose. Baseline 3 is appropriate as the schema handles the heavy lifting.
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 the action ('trigger') and resource ('build pipeline in Azure DevOps'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from potential siblings like 'get-builds' or 'get-pipeline-status' that might also interact with pipelines, missing explicit distinction.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid definition), exclusions, or compare it to sibling tools like 'get-builds' for monitoring, leaving the agent to infer usage context.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'update' implies a mutation operation, the description doesn't mention permission requirements, whether the update is partial or complete, what happens to unspecified fields, error handling, or response format. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
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 a single, efficient sentence that states exactly what the tool does without unnecessary words. It's appropriately sized and front-loaded with the essential information. Every word earns its place.
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?
For a mutation tool with 9 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't address important contextual aspects like required permissions, partial vs complete updates, error scenarios, or what the tool returns. The agent lacks critical information needed to use this tool effectively.
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 schema has 100% description coverage, so all parameters are documented in the structured schema. The description adds no additional parameter information beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.
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 the action ('Update') and resource ('existing work item in Azure DevOps'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'create-work-item' beyond the obvious 'update' vs 'create' distinction, nor does it mention other potential update-related tools that might exist.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like needing an existing work item ID), when to use 'create-work-item' instead, or how this differs from other update-related operations that might be available. The agent must infer usage from the tool name alone.
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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