AtomGit MCP Server

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes, but there is some overlap between 'get_user_repositories' and 'get_user_repository' which could cause confusion, and 'create_pull_request_comment' vs 'create_pull_request_reply' might be ambiguous without clear context. Overall, the tools are well-differentiated by resource and action.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case, such as 'create_issue', 'get_issue_details', and 'list_repository_issues'. The naming is predictable and uniform throughout the set, making it easy for agents to understand and use.
Tool Count3/5
With 22 tools, the count is on the higher side for a Git repository server, bordering on heavy. While it covers many operations, it might be overwhelming or redundant, such as having separate tools for 'get_user_repositories' and 'get_user_repository'.
Completeness5/5
The tool set provides comprehensive coverage for managing issues, pull requests, labels, repositories, and branches in AtomGit. It includes CRUD operations for issues and pull requests, label management, and repository/branch queries, with no obvious gaps for core workflows.
Average 2.9/5 across 22 of 22 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 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 Mulan Permissive Software License, Version 2.
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 states 'Create a comment' which implies a write operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what happens on success/failure. For a mutation tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for the tool's function, making it easy to parse quickly. Every word contributes directly to stating the purpose.
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 a mutation tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on parameters, behavior, output, and differentiation from siblings. The agent would struggle to use this tool correctly without additional context or trial-and-error.
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 description coverage is 0%, so the schema provides no parameter details. The description adds no information about parameters like 'repoOwner', 'repo', 'pull_number', or 'body' (e.g., format, examples, constraints). It fails to compensate for the low coverage, leaving all 4 parameters undocumented in meaning.
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 'Create a comment on a pull request' clearly states the action (create) and target (comment on a pull request), which is better than a tautology. However, it doesn't distinguish this tool from its sibling 'create_pull_request_reply' or 'create_issue_comment', leaving ambiguity about when to use each. The purpose is understandable but lacks 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?
No guidance is provided on when to use this tool versus alternatives like 'create_pull_request_reply' or 'create_issue_comment'. The description implies usage for pull request comments but doesn't specify context, prerequisites, or exclusions. Without annotations or explicit instructions, the agent has minimal direction.
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 implies a read-only operation ('Get'), but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling (e.g., for invalid inputs), or what happens if the pull request doesn't exist. The description is minimal and lacks context beyond the basic action.
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 appropriately sized for a simple tool and front-loaded with the core action, though it could benefit from more detail without sacrificing conciseness.
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 moderate complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'details' include, how to interpret parameters, or behavioral aspects like safety and errors. For a tool that fetches specific data, more context is needed to guide effective use.
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 schema description coverage is 0%, so the description must compensate. It adds no meaning beyond the schema—it doesn't explain what 'owner', 'repo', or 'pull_number' represent (e.g., GitHub username, repository name, PR identifier), their formats, or constraints. With 3 undocumented parameters, this is a significant gap.
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 'Get details of a specific pull request' clearly states the verb ('Get') and resource ('pull request'), but it's vague about what 'details' entails. It distinguishes from siblings like 'get_pull_request_comment' by focusing on the pull request itself rather than its comments, but doesn't specify scope (e.g., metadata, diff, reviews) or differentiate from 'get_issue_details' for pull requests that are also issues.
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 specific pull request number), contrast with 'get_issue_details' for pull requests that are issues, or indicate when other tools like 'get_pull_request_comment' might be more appropriate for comment-specific details.
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 ('create') but doesn't describe what this entails—whether it requires specific permissions, what happens on success/failure, if it's idempotent, or any rate limits. For a mutation tool with zero annotation coverage, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a basic tool definition and front-loads the core action and resource, 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 (3 parameters with nested objects, no output schema, and no annotations), the description is incomplete. It doesn't cover parameter meanings, behavioral traits, or usage context, leaving the agent with insufficient information to reliably invoke this tool. For a creation tool with multiple parameters, more guidance is needed.
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 schema description coverage is 0%, meaning none of the parameters are documented in the schema. The description adds no information about parameters beyond implying a repository context. It doesn't explain what 'owner', 'repo', or the nested 'body' object fields mean, leaving the agent to guess parameter semantics from the schema structure alone.
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 pull request in a repository'), making the purpose immediately understandable. It distinguishes this tool from siblings like create_issue or create_pull_request_comment by specifying the pull request resource. However, it doesn't explicitly differentiate from all siblings (e.g., create_pull_request_reply), so it's not a perfect 5.
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 repository, branch permissions), when not to use it, or how it differs from similar tools like create_issue. This leaves the agent with insufficient context for optimal tool selection.
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 implies a write operation ('Reply to') but doesn't specify permissions, rate limits, or response format. This leaves significant gaps in understanding the tool's behavior and constraints.
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 no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose 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 a 5-parameter write tool with no annotations or output schema, the description is incomplete. It lacks details on behavioral traits, parameter meanings, and return values, failing to provide adequate context for effective use.
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 description coverage is 0%, so the description must compensate for 5 undocumented parameters. It mentions 'comment on a pull request' and 'Reply', which hints at comment_id and body, but doesn't explain owner, repo, or pull_number. This adds minimal semantic value 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 the action ('Reply to') and target ('a comment on a pull request'), which is specific and distinguishes it from siblings like create_pull_request_comment. However, it doesn't explicitly differentiate from create_issue_comment, which might be similar for issue contexts, leaving slight ambiguity.
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, such as create_pull_request_comment for top-level PR comments or create_issue_comment for issue comments. It lacks context about prerequisites or exclusions, offering minimal usage direction.
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. It states it 'gets details' but doesn't disclose behavioral traits like whether it's a read-only operation, what permissions are required, error handling, or the format of returned details. This leaves significant gaps for a tool with 4 parameters.
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. It's front-loaded with the core purpose, 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 4 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It lacks details on usage context, parameter meanings, behavioral expectations, and return values, making it inadequate for effective tool selection and invocation.
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 description coverage is 0%, so the description must compensate, but it adds no parameter information. It doesn't explain what 'owner', 'repo', 'pull_number', or 'comment_id' mean or how to obtain them, leaving all 4 parameters undocumented beyond their types in 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 the verb 'Get' and the resource 'details of a specific pull request comment', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_pull_request_details' or 'get_issue_details', which follow similar patterns for different resources.
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 a specific comment ID or how it differs from other 'get' tools in the sibling list, such as 'get_pull_request_details' for broader pull request information.
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 action ('assign users') but doesn't describe what happens on success/failure, whether it overwrites existing assignees, if it requires specific permissions, or any rate limits. This leaves significant gaps for a mutation 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 communicates the core purpose without unnecessary words. It's appropriately sized and front-loaded with the essential information.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, what permissions are needed, or potential error conditions. The agent would need to guess about behavioral aspects beyond the basic action.
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 already documents all four parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, maintaining 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 action ('assign users') and resource ('an issue in a AtomGit repository'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'list_issue_assignees' or 'check_if_user_is_assignable', 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. It doesn't mention prerequisites (like needing repository access), when assignment is appropriate, or how it differs from related tools like 'check_if_user_is_assignable' or 'list_issue_assignees'.
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 the tool 'checks' something, implying a read-only operation, but doesn't clarify what 'can be assigned' means (e.g., permissions, repository access, or issue state). It also omits details like error conditions, rate limits, or response format, leaving significant gaps in understanding the tool's 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, direct sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded with the main action ('Check'), making it easy to parse. There is no wasted verbiage, and it fits the tool's simplicity appropriately.
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 moderate complexity (3 parameters, no output schema, no annotations), the description is incomplete. It lacks behavioral details (e.g., what 'can be assigned' entails, error handling), usage context relative to siblings, and output expectations. Without annotations or an output schema, the description should provide more comprehensive guidance to compensate, which it does not.
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 clear parameter definitions (owner, repo, assignee). The description adds no additional semantic context beyond what the schema provides, such as format examples or interdependencies. With high schema coverage, the baseline is 3, as the schema adequately documents parameters without extra description input.
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: 'Check if a user can be assigned to an issue in a AtomGit repository.' It specifies the verb ('check'), resource ('user'), and context ('issue in a AtomGit repository'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_issue_assignees' or 'assign_issue', which would require a 5.
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., whether the issue must exist), exclusions, or comparisons to siblings like 'list_issue_assignees' (which lists assignable users) or 'assign_issue' (which assigns a user). This lack of context leaves the agent to infer usage scenarios.
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 tool creates an issue but doesn't mention whether this is a write operation (implied by 'Create'), what permissions are required, how errors are handled (e.g., invalid repository), or what the response looks like (e.g., issue ID, confirmation). For a mutation tool with zero annotation coverage, 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.
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, with every word earning its place by conveying the essential action and target.
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 a 7-parameter mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., permissions, error handling), usage guidelines relative to siblings, and parameter semantics for undocumented fields. The description alone doesn't provide enough context for an agent to confidently invoke this tool without additional inference or trial-and-error.
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 57% (4 of 7 parameters have descriptions: owner, repo, title, body), leaving 3 parameters (assignees, milestone, labels) undocumented in the schema. The description adds no parameter-specific information beyond what the schema provides, so it doesn't compensate for the coverage gap. However, the schema descriptions for the required parameters are clear, justifying a baseline score of 3.
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 a new issue') and target resource ('in a AtomGit repository'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from its sibling 'create_pull_request' or other issue-related tools like 'assign_issue' or 'create_issue_comment', which would require explicit comparison to achieve a score of 5.
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 'create_pull_request' for code changes or 'create_issue_comment' for adding comments to existing issues. It also lacks information about prerequisites (e.g., repository access permissions) or typical use cases, leaving the agent to infer usage context without explicit direction.
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. While 'Create' implies a write operation, it doesn't specify authentication requirements, rate limits, error conditions, or what happens on success (e.g., returns the created comment). For a mutation tool with zero annotation coverage, this is a significant gap.
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 any fluff or redundancy. 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 a mutation tool (creating a comment) with no annotations and no output schema, the description is incomplete. It lacks crucial context like authentication needs, response format, error handling, or how it differs from similar tools. This leaves significant gaps for an AI 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 schema fully documents all four parameters (owner, repo, issue_number, body). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Baseline 3 is appropriate when the schema does 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 ('Create') and target resource ('issue comment in a AtomGit repository issue'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'create_pull_request_comment' or 'create_pull_request_reply', which also create comments but on different resources.
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 issue), exclusions, or comparisons to sibling tools like 'create_issue' (for creating the issue itself) or comment tools for pull requests.
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 like whether it overwrites existing labels, requires specific permissions, handles errors, or has rate limits. This is inadequate for a mutation 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 with zero waste, clearly front-loading the core action. It's appropriately sized for the tool's complexity.
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 no annotations and no output schema, the description is incomplete. It lacks details on behavior, error handling, or return values, leaving significant gaps for an AI agent to operate 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?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond what's in the schema, such as format examples or constraints, meeting the baseline for high 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 ('Add labels') and target ('to an issue in a repository'), making the purpose evident. However, it doesn't differentiate from sibling tools like 'delete_issue_label' or 'get_issue_labels', which would require explicit comparison to earn a 5.
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 'delete_issue_label' or 'get_issue_labels', nor does it mention prerequisites such as issue existence or label availability. The description lacks context for decision-making.
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 ('Remove') but doesn't clarify if this is a destructive operation, what permissions are required, how errors are handled (e.g., if the label doesn't exist), or what the response looks like. For a mutation tool with zero annotation coverage, 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, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action ('Remove') and avoids redundancy, making it easy to parse quickly. Every part of the sentence earns its place by specifying the resource and context.
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 as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., side effects, error handling) and output expectations, which are critical for safe and effective use. While the schema covers parameters well, the overall context for invoking this tool is insufficient.
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 all four parameters (owner, repo, issue_number, name) with details like case-insensitivity. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema does 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 ('Remove') and target ('a label from an issue in a repository'), making the purpose immediately understandable. It distinguishes itself from siblings like 'create_issue_labels' or 'get_issue_labels' by specifying removal rather than creation or retrieval. However, it doesn't explicitly contrast with all siblings (e.g., 'assign_issue' also modifies issues), so it falls short of a perfect 5.
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 existing labels or permissions), exclusions, or comparisons to siblings like 'create_issue_labels' for adding labels. Without such context, 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.
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 the action ('Get details') but doesn't describe what 'details' include (e.g., title, status, comments), whether it's a read-only operation, error handling, or any rate limits. For a tool with 3 parameters and no annotations, this leaves significant behavioral gaps, though it's not misleading.
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 redundancy. It's appropriately sized for a simple lookup tool, front-loaded with the core action, and wastes no words. This exemplifies conciseness with zero 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 moderate complexity (3 parameters, no output schema, no annotations), the description is incomplete. It lacks details on return values (what 'details' entail), error cases, or behavioral context. Without annotations or output schema, the description should compensate more to guide the agent effectively, but it does not, leaving gaps in understanding the tool's full behavior.
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 clear parameter descriptions (e.g., 'Repository owner', 'Repository name', 'Issue number'). The description adds no additional meaning beyond the schema, such as format examples or constraints. With high schema coverage, the baseline is 3, as the schema adequately documents parameters without extra help from 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 verb ('Get details') and resource ('specific issue in a AtomGit repository'), making the purpose unambiguous. It distinguishes from siblings like 'list_repository_issues' (which lists multiple issues) by focusing on a single issue, though it doesn't explicitly name alternatives. The specificity earns a 4, as it's clear but lacks explicit sibling 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 issue number), exclusions, or comparisons to siblings like 'get_issue_labels' or 'list_repository_issues'. Without such context, the agent must infer usage from the tool name and parameters alone, which is minimal guidance.
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 'Search for' but doesn't clarify if this is a read-only operation, what permissions are needed, how results are returned, or any rate limits. This is inadequate for a tool with multiple parameters and no output schema.
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. It's front-loaded with the core purpose, 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 (4 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain return values, error conditions, or behavioral traits, leaving significant gaps for the agent to operate 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?
Schema description coverage is 100%, so the schema fully documents all 4 parameters. The description adds no additional meaning beyond implying a search functionality, which is already covered by the schema. Baseline 3 is appropriate as the schema handles parameter documentation.
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 verb ('Search for') and resource ('AtomGit org repositories'), making the purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'get_user_repositories' or 'get_repository_labels' beyond the resource type, 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?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, exclusions, or comparisons to sibling tools like 'get_user_repositories', leaving the agent to infer usage from context 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it 'Get all labels' but doesn't describe what 'all' entails (e.g., pagination, rate limits, authentication needs, or return format). For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond its basic purpose.
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 is front-loaded and wastes no space, making it easy to parse quickly. Every word earns its place by conveying essential information.
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 behavioral complexity. It doesn't address key aspects like return format (e.g., list of label objects), pagination, error handling, or authentication requirements. For a read operation that might involve multiple items, more context is needed to ensure proper usage.
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%, with both parameters ('owner' and 'repo') well-documented in the schema. The description adds no additional parameter information beyond what the schema provides, such as examples or edge cases. Given the high schema coverage, a baseline score of 3 is appropriate as the description doesn't compensate but also doesn't need to.
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 verb 'Get' and resource 'all labels in a repository', making the purpose immediately understandable. It distinguishes from siblings like 'get_issue_labels' (which is issue-specific) and 'get_label_by_name' (which retrieves a single label), though it doesn't explicitly mention these distinctions. The description is specific but could be more precise about sibling 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 when to choose this over 'get_issue_labels' (for issue-specific labels) or 'get_label_by_name' (for a single label), nor does it specify prerequisites like repository access. Usage is implied by the name but not explicitly stated.
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. 'Search' implies a read operation, but the description doesn't mention authentication requirements, rate limits, pagination behavior (beyond what's in the schema), error conditions, or what constitutes a 'search' versus a simple listing. This leaves significant gaps for an agent to understand how the tool behaves.
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 gets straight to the point with zero wasted words. It's appropriately sized for a search/list tool and front-loads the essential information 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?
For a search tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what constitutes a successful search, what format results return, how pagination works in practice, or how the 'username' and 'search' parameters interact. The agent would struggle to use this tool effectively without trial and error.
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?
With 100% schema description coverage, the schema already documents all four parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain how 'username' interacts with 'search', what 'per_page' and 'page' actually control, or provide examples of search queries. This meets 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 'Search for AtomGit user repositories' clearly states the action (search) and resource (user repositories), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'get_user_repository' (singular) or 'get_org_repositories', which would require more specific 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. With sibling tools like 'get_user_repository' (singular) and 'get_org_repositories' available, there's no indication whether this is for searching across multiple users, filtering repositories, or other specific use cases that would help an agent choose appropriately.
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 tool performs a search but doesn't describe what the search returns (e.g., repository details, a list), how results are formatted, error conditions, or any rate limits. This leaves significant gaps in understanding the tool's behavior beyond the basic action.
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 is front-loaded and wastes no space, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 (a search operation with no annotations and no output schema), the description is insufficient. It doesn't explain what the search returns, how results are structured, or any behavioral nuances, leaving the agent with incomplete context for effective 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, with clear documentation for both required parameters ('owner' and 'repo'). The description adds no additional parameter semantics beyond what the schema provides, such as examples or search behavior details. This meets the baseline of 3 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 ('Search for') and resource ('AtomGit user repository'), making the purpose evident. However, it doesn't explicitly distinguish this tool from its sibling 'get_user_repositories' (plural), which appears to be a similar listing tool, leaving some ambiguity about when to use one versus the other.
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, context, or comparisons to sibling tools like 'get_user_repositories' or 'get_org_repositories', leaving the agent to infer usage based on the name and parameters 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 mentions listing assignees but doesn't describe what the output looks like, whether it's paginated, if authentication is required, or any rate limits. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 gets straight to the point with no wasted words. It's appropriately sized for a simple list operation and front-loads the essential information.
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 no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the return values look like, how many assignees might be returned, or any error conditions. For a tool that presumably returns structured data, more context is needed beyond the basic purpose statement.
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 schema already documents both parameters (owner and repo) adequately. The description doesn't add any additional meaning about the parameters beyond what's in the schema, such as format examples or constraints. This meets 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 verb ('List') and resource ('assignees for a specific issue in a AtomGit repository'), making the purpose immediately understandable. However, it doesn't distinguish itself from sibling tools like 'get_issue_details' which might also provide assignee information, so it doesn't reach the highest 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. There's no mention of prerequisites, when this tool is preferred over sibling tools like 'get_issue_details', or any contextual constraints. It simply states what the tool does without 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?
No annotations are provided, so the description carries full burden for behavioral disclosure. 'List branches' implies a read-only operation, but the description doesn't mention pagination behavior (though parameters suggest it), rate limits, authentication requirements, or what the output format looks like. This leaves significant gaps for an agent to understand how to use it effectively.
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 any wasted words. It's appropriately sized for a straightforward listing operation and gets directly to the point.
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 tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the pagination behavior implied by the parameters, doesn't describe the return format, and provides no context about authentication or rate limits. The agent would need to guess about important operational aspects.
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?
With 100% schema description coverage, the input schema already fully documents all 4 parameters. The description adds no additional parameter context beyond what's in the schema, so it meets the baseline expectation but doesn't provide extra 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 ('List') and resource ('branches in a repository'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get_repository_branch_details', which retrieves details about a specific branch rather than listing all branches.
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_repository_branch_details' and various issue/pull request tools, there's no indication of appropriate contexts, prerequisites, or exclusions for this listing operation.
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 basic action but reveals nothing about permissions required, pagination behavior, rate limits, filtering capabilities, or what data is returned. For a list operation with zero annotation coverage, this leaves 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 that states the core purpose without unnecessary words. It's appropriately sized for a basic list operation and front-loads the essential information.
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 repository issue listing (which typically involves filtering, pagination, and permission considerations), the description is insufficient. With no annotations, no output schema, and a minimal description, it doesn't provide enough context for an agent to understand the tool's behavior and limitations.
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 both parameters clearly documented as 'Repository owner' and 'Repository name'. The description adds no additional parameter information beyond what the schema already provides, so the baseline score of 3 is appropriate.
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 ('List issues') and target resource ('in a AtomGit repository'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from similar sibling tools like 'get_issue_details' or 'list_issue_assignees', 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. With multiple issue-related sibling tools available (get_issue_details, list_issue_assignees, etc.), there's no indication of when this listing function is appropriate versus more specific tools.
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 mentions a read operation ('Get') but doesn't specify whether authentication is required, rate limits apply, or what the output format is (e.g., list of label names/objects). For a tool with no annotation coverage, 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, efficient sentence that directly states the tool's purpose without any unnecessary words or fluff. It is appropriately sized and front-loaded, making it easy to understand at a glance.
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 the tool's low complexity (simple read operation with 3 parameters) and high schema coverage (100%), the description is minimally adequate but lacks output information (no output schema) and behavioral context like authentication needs. It meets basic requirements but could be more informative for an agent to use it 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 input schema has 100% description coverage, clearly documenting all three parameters (owner, repo, issue_number) with their types and meanings. The description adds no additional parameter information beyond what the schema provides, which is acceptable given the high schema coverage, resulting in a baseline score of 3.
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 all labels') and target resource ('for an issue in a repository'), which is specific and unambiguous. It distinguishes from siblings like 'get_repository_labels' (which gets repository-level labels) and 'get_label_by_name' (which gets a specific label), though it doesn't explicitly mention these distinctions.
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_repository_labels' or 'get_label_by_name', nor does it mention prerequisites such as authentication or permissions. It simply states what the tool does without contextual usage information.
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 the tool retrieves a label but doesn't describe what happens if the label doesn't exist (e.g., error handling), whether it requires authentication, rate limits, or the format of the return value. For a read operation with zero annotation coverage, this leaves significant gaps in understanding the tool's 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 that front-loads the core purpose ('Get a single label by name from a repository'). There is no wasted verbiage, repetition, or unnecessary detail, making it highly concise and well-structured for quick comprehension.
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 the tool's low complexity (a simple read operation), 100% schema coverage, and no output schema, the description is minimally adequate. However, it lacks details on error handling, authentication needs, or return format, which are important for a tool with no annotations. It's complete enough to understand the basic purpose but insufficient for full operational 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?
Schema description coverage is 100%, with all three parameters ('owner', 'repo', 'name') well-documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as examples or edge cases. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, though the description doesn't compensate for any gaps (none exist here).
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 ('a single label by name from a repository'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'get_repository_labels' (which lists all labels) and 'get_issue_labels' (which gets labels for an issue), though it doesn't explicitly name these alternatives. The description is specific but could be more precise about the 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 sibling tools like 'get_repository_labels' (for listing all labels) or 'get_issue_labels' (for labels on an issue), nor does it specify prerequisites or contextual constraints. Usage is implied by the name and description alone, with no explicit when/when-not instructions.
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 it's a read operation ('Get'), which implies non-destructive behavior, but doesn't address authentication needs, rate limits, error responses, or what happens with invalid inputs. For a tool with zero annotation coverage, this minimal description leaves significant behavioral gaps unaddressed.
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 simple lookup tool and front-loads the essential information. Every word earns its place, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 required parameters) and lack of both annotations and output schema, the description is minimally adequate but incomplete. It covers the basic purpose but doesn't address what details are returned, error handling, or integration with sibling tools. For a tool with no structured behavioral or output documentation, the description should do more to compensate.
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 input schema, which has 100% coverage with clear descriptions for all three parameters (owner, repo, branch). Since the schema does the heavy lifting, the baseline score of 3 is appropriate. The description doesn't compensate with additional context about parameter relationships or usage examples.
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 details') and resource ('specific branch in a repository'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'list_repository_branches' by focusing on a single branch rather than listing multiple. However, it doesn't specify what kind of details are returned (e.g., commit info, protection rules), 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. It doesn't mention sibling tools like 'list_repository_branches' for browsing branches or 'get_user_repository' for repository-level details. There's no context about prerequisites, error conditions, or typical use cases, 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.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![atomgit-mcp-server MCP server](https://glama.ai/mcp/servers/kaiyuanxiaobing/atomgit-mcp-server/badges/card.svg)](https://glama.ai/mcp/servers/kaiyuanxiaobing/atomgit-mcp-server)

Score Badge

Copy to your README.md:

[![atomgit-mcp-server MCP server](https://glama.ai/mcp/servers/kaiyuanxiaobing/atomgit-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/kaiyuanxiaobing/atomgit-mcp-server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kaiyuanxiaobing/atomgit-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server