GitHub MCP Server Plus

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 targeting specific GitHub resources and actions, but there is some overlap between push_files_content and push_files_from_path (both push multiple files, differing only in input source) and between list_issues and search_issues (both retrieve issues, differing in scope). Descriptions help clarify these distinctions, but agents might occasionally confuse them.
Naming Consistency5/5
All tools follow a consistent verb_noun or verb_noun_preposition pattern (e.g., create_issue, get_file_contents, search_repositories), with no mixing of conventions like camelCase or snake_case variations. The naming is predictable and readable throughout the set.
Tool Count4/5
With 18 tools, the count is slightly high but reasonable for a comprehensive GitHub server covering repositories, issues, files, search, and operations. It avoids being excessive (under 25) and each tool appears to serve a specific function, though some could be consolidated (e.g., the two push tools).
Completeness5/5
The tool set provides complete coverage for core GitHub workflows, including CRUD operations for repositories, issues, files, and branches, along with search across code, issues, repositories, and users. There are no obvious gaps; agents can perform end-to-end tasks like creating repos, managing issues, and pushing code without dead ends.
Average 3/5 across 18 of 18 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues 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 status not available
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

Behavior1/5
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. The description only states what the tool does at a high level ('Search for code across GitHub repositories') without revealing any behavioral traits like authentication requirements, rate limits, pagination behavior, error conditions, or what the search results look like. For a search tool with zero annotation coverage, this is completely inadequate.
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. There's no wasted verbiage or unnecessary elaboration. It's appropriately sized for a basic tool description, though this conciseness comes at the cost of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a search operation with 4 parameters, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what the tool returns, how results are structured, authentication requirements, rate limits, or parameter usage. For a search tool that likely returns complex results, this minimal description leaves the agent with insufficient information to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no information about parameters beyond what's implied by the tool name. With 0% schema description coverage and 4 parameters (q, order, page, per_page), the description doesn't explain what 'q' represents (search query syntax?), what 'order' sorts by, or how pagination works. The description fails to compensate for the complete lack of schema 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 action ('Search for code') and resource ('across GitHub repositories'), which is specific and unambiguous. However, it doesn't differentiate this from sibling tools like search_issues, search_repositories, or search_users, which all perform different types of searches within GitHub.
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 when to choose search_code over other search tools (search_issues, search_repositories, search_users) or when to use it versus browsing tools like get_file_contents. The agent must infer usage from the 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 for behavioral disclosure. While 'Add a comment' implies a write/mutation operation, it doesn't disclose permission requirements, rate limits, whether comments are editable/deletable, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is insufficient.
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 straightforward tool 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?
For a mutation tool with 4 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain parameter meanings, behavioral implications, or what to expect upon execution. The context demands more comprehensive documentation than provided.
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%, meaning all 4 parameters are undocumented in the schema. The description provides no information about what 'owner', 'repo', 'issue_number', or 'body' mean, their formats, or constraints. It doesn't compensate for the complete lack of schema 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 action ('Add a comment') and target resource ('to an existing issue'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'update_issue', which might also handle comments, leaving room for 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 like 'update_issue' or 'create_issue'. It mentions 'existing issue' which implies a prerequisite, but doesn't explicitly state when-not-to-use scenarios or reference sibling tools for different contexts.
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 this is a creation operation but doesn't mention permission requirements, rate limits, what happens on success/failure, or whether it's idempotent. For a write operation 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 with zero wasted words. It's appropriately sized for a basic tool description and front-loads the essential information about what the tool does.
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 7-parameter write operation with no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain return values, error conditions, authentication needs, or parameter semantics, leaving the agent with insufficient context to use the tool effectively.
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?
With 0% schema description coverage for all 7 parameters, the description provides no parameter information beyond what's inferred from the tool name. It doesn't explain what 'owner', 'repo', 'title', 'body', 'assignees', 'milestone', or 'labels' mean or how they should be formatted, failing to compensate for the schema's lack of descriptions.
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 GitHub repository'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'update_issue' or 'add_issue_comment', 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?
The description provides no guidance on when to use this tool versus alternatives like 'update_issue' for modifying existing issues or 'add_issue_comment' for adding comments. There's no mention of prerequisites, context, or exclusions, leaving the agent with 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 the action ('Get details') but does not disclose behavioral traits like authentication needs, rate limits, error handling, or what details are returned. For a read operation 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 is appropriately sized and front-loaded, 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 the tool's complexity (3 required parameters), lack of annotations, and no output schema, the description is incomplete. It does not explain return values, error cases, or usage context, making it inadequate for effective tool selection and invocation by an AI agent.
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 does not add any meaning beyond the parameter names (owner, repo, issue_number), such as explaining what these represent (e.g., GitHub username, repository name, issue ID) or their formats. It fails to compensate for the low 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 ('Get details') and resource ('specific issue in a GitHub repository'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'list_issues' or 'search_issues', which would require a more specific scope or 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 such as 'list_issues' for multiple issues or 'search_issues' for filtered searches. It lacks explicit context, prerequisites, or exclusions, leaving usage decisions to inference.
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 offers minimal information. It implies a read-only operation ('Get list'), but doesn't specify whether authentication is required, if there are rate limits, how pagination works (given the 'page' and 'perPage' parameters), or what the output format looks like. This is inadequate for a tool with multiple parameters and no structured annotations.
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. It's front-loaded with the core purpose ('Get list of commits'), making it easy to scan and understand quickly. Every word earns its place, achieving optimal 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 complexity (5 parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It doesn't explain parameter meanings, behavioral traits like pagination or authentication, or what the output contains. For a tool that likely returns structured commit data, this leaves significant gaps for an AI agent to use it effectively.
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 5 parameters are documented in the schema. The description only vaguely references 'branch' (implied by 'sha' parameter) and 'GitHub repository' (implied by 'owner' and 'repo'), but doesn't explain what 'sha', 'page', or 'perPage' mean or how they affect the output. It adds minimal value beyond the bare 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 ('Get list of commits') and the resource ('of a branch in a GitHub repository'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from potential sibling tools like 'search_code' or 'get_file_contents' that might also involve repository data, 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 (e.g., authentication needs), compare it to siblings like 'search_code' for finding specific commits, or indicate scenarios where it's preferred over other tools. This leaves the agent with minimal context for 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 full burden for behavioral disclosure but only states the basic action. It doesn't mention whether this is a read-only operation, if it requires authentication, how pagination works (despite 'page' and 'per_page' parameters), rate limits, or what the output format looks like. This leaves critical behavioral traits undocumented.
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 ('List issues in a GitHub repository') and adds essential context ('with filtering options') without any wasted words. 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?
Given the tool's complexity (9 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return values, pagination behavior, authentication requirements, or how to interpret parameters like 'direction' or 'sort'. For a listing tool with rich filtering options, more context is needed to use it effectively.
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 only vaguely mentions 'filtering options' without explaining any of the 9 parameters. It doesn't clarify what 'owner', 'repo', or other parameters mean, their formats (e.g., 'since' as timestamp), or how filtering works with arrays like 'labels'. The description adds minimal value beyond the bare 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 ('List') and resource ('issues in a GitHub repository') with scope ('with filtering options'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'search_issues' or 'get_issue', which handle similar resources but with different approaches.
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 'search_issues' or 'get_issue'. It mentions filtering options but doesn't specify scenarios where this listing approach is preferred over searching or retrieving individual issues, leaving the agent 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 the full burden of behavioral disclosure. It states the action 'search' but doesn't describe what the search returns (e.g., paginated results, error handling, rate limits, or authentication needs). For a search tool with 5 parameters and no 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 front-loads the core purpose without unnecessary words. It's appropriately sized for a search tool, 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 complexity of 5 parameters (including enums for 'order' and 'sort'), 0% schema description coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain the search behavior, result format, or parameter usage, leaving critical gaps for an agent to invoke the tool correctly.
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 5 parameters are documented in the schema. The description doesn't add any parameter semantics—it doesn't explain what 'q' represents (e.g., search query syntax), the meaning of 'order', 'page', 'per_page', or 'sort' options. This fails to compensate for the lack of schema 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' and the resources 'issues and pull requests' with the scope 'across GitHub repositories', which is specific and actionable. However, it doesn't explicitly distinguish this tool from sibling tools like 'list_issues' or 'search_code', which would require more precise differentiation 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 such as 'list_issues' (for issues in a specific repository) or 'search_code' (for code search). 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 the full burden of behavioral disclosure. 'Search for users' implies a read-only operation, but it doesn't disclose important behavioral traits like pagination behavior (implied by page/per_page parameters), rate limits, authentication requirements, or what the response format looks like. The description is minimal and lacks behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is maximally concise with a single clear sentence that states the core purpose. There's no wasted language or unnecessary elaboration, making it efficiently front-loaded.
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 5 parameters (one required), no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't provide enough context about how to use the tool effectively, what parameters mean, or what to expect in return. The minimal description doesn't compensate for the missing structured information.
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?
With 0% schema description coverage for 5 parameters, the description provides no parameter information beyond what's implied by the tool name. It doesn't explain what 'q' represents (search query), what the order/sort options mean, or how pagination works. The description fails to compensate for the complete lack of schema descriptions.
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 ('users on GitHub'), providing specific verb+resource pairing. However, it doesn't differentiate from sibling search tools like search_code, search_issues, and search_repositories, which all search different GitHub 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?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention when this search is appropriate versus other user-related operations or how it differs from the other search tools on the server (search_code, search_issues, search_repositories).
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. 'Update an existing issue' implies a mutation operation, but it doesn't specify what happens with partial updates, whether changes are reversible, authentication requirements, rate limits, or error conditions. For a 9-parameter mutation tool, 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 states the core purpose without unnecessary words. It's appropriately front-loaded with the essential information, though this brevity comes at the cost of completeness for such a complex tool.
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, 0% schema coverage, no annotations, and no output schema, the description is severely inadequate. It provides only the basic purpose without addressing parameter meanings, behavioral characteristics, usage context, or return values. The agent would struggle to use this tool correctly without additional documentation.
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?
With 0% schema description coverage and 9 parameters (only 3 required), the description provides no information about any parameters. It doesn't mention that 'owner', 'repo', and 'issue_number' are required identifiers, nor does it explain the purpose of optional fields like 'title', 'body', 'assignees', etc. The description fails to compensate for the complete lack of schema 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 action ('Update') and resource ('existing issue in a GitHub repository'), making the purpose immediately understandable. However, it doesn't differentiate this tool from similar siblings like 'create_issue' or 'get_issue' beyond the basic verb difference, missing an opportunity to clarify scope boundaries.
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 'create_issue' for new issues and 'get_issue' for reading, the agent must infer usage from the verb alone. There's no mention of prerequisites, permissions needed, or typical scenarios for updating versus creating issues.
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 mutation, the description lacks details on permissions required, whether the operation is idempotent, error handling (e.g., if the branch already exists), or 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.
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 GitHub branch creation tool (a mutation with potential side effects), no annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like authentication needs, error cases, or return values, leaving 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?
The description adds no parameter-specific information beyond what's in the input schema, which has 100% coverage with clear descriptions for all four parameters. This meets the baseline of 3, as the schema fully documents the parameters, but the description doesn't enhance understanding with additional context or 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 ('Create') and resource ('new branch in a GitHub repository'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'create_repository' or 'create_pull_request' beyond the obvious resource difference, missing 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. It doesn't mention prerequisites (e.g., needing repository access), when not to use it (e.g., for existing branches), or how it relates to siblings like 'fork_repository' or 'create_pull_request' for branch-related 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. It states the tool can 'create or update' files, implying mutation, but doesn't mention authentication requirements, rate limits, error conditions, or what happens when creating versus updating (e.g., the 'sha' parameter requirement for updates). This leaves significant gaps for an agent to understand 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. There's no wasted language or redundancy, 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?
For a mutation tool with 7 parameters, no annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like authentication, error handling, or the create/update distinction, leaving the agent with incomplete context to use the 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 description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema (e.g., it doesn't explain the relationship between 'sha' and updating files, though the schema hints at this). This meets the baseline expectation when schema coverage is complete.
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 or update') and resource ('a single file in a GitHub repository'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'push_files_content' or 'push_files_from_path', which might have overlapping functionality.
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 to choose this over sibling tools like 'push_files_content', or any constraints on usage. 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?
With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It states the tool creates a pull request but doesn't mention authentication requirements, rate limits, what happens on success/failure, whether it triggers notifications, or if it's idempotent. For a write operation with zero annotation coverage, this leaves critical behavioral traits undocumented.
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 functionality without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly. Every word earns 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?
For a complex write operation with 8 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or behavioral nuances like GitHub-specific constraints. The high parameter count and mutation nature demand more contextual information than provided.
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%, providing clear documentation for all 8 parameters. The description adds no parameter-specific information beyond what's in the schema, so it meets the baseline of 3. However, it doesn't compensate for any gaps since there are none 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 action ('create') and resource ('pull request in a GitHub repository'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like create_issue or create_repository, which would require mentioning it's specifically for code review workflows between 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. It doesn't mention prerequisites (e.g., needing existing branches), contrast with create_issue for non-code changes, or specify when draft vs. regular pull requests are appropriate. Without this context, agents 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Create' implies a write operation, the description doesn't mention authentication requirements, rate limits, what happens on success/failure, or whether this is a destructive operation that creates permanent resources. It lacks essential context for safe and effective use.
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. It's perfectly front-loaded and communicates the core purpose immediately 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 write operation with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after creation (what's returned), authentication needs, error conditions, or how this differs from similar tools like fork_repository. The context signals indicate this is a non-trivial operation that requires more guidance.
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 4 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. This meets the baseline expectation when schema coverage is high.
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 GitHub repository in your account'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'fork_repository' or explain why to use create_repository versus fork_repository when both create repositories.
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 (like authentication), when to use create_repository versus fork_repository, or any limitations (like rate limits or account restrictions).
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. While 'Get the contents' implies a read operation, it doesn't specify whether this requires authentication, rate limits, what happens with large directories, or the format of returned content. For a tool with 4 parameters and no annotation coverage, this is insufficient.
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 for a straightforward tool 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?
For a tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'contents' means (file content vs metadata), how directories are handled, error conditions, or return format. The description should provide more context given the lack of structured information elsewhere.
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 all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema - it doesn't explain relationships between parameters or provide usage examples. 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 action ('Get the contents') and resource ('file or directory from a GitHub repository'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search_code' or 'list_commits' that might also retrieve repository content in different ways.
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 when this tool is appropriate versus using 'search_code' for broader searches or 'list_commits' for commit history, nor any prerequisites or constraints for usage.
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 but provides minimal information. It states this is a search operation but doesn't describe what the search returns (repository metadata, full objects?), authentication requirements, rate limits, error conditions, or whether this is a read-only operation. The agent must infer behavior from the name alone.
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 maximally concise - a single clear sentence that states exactly what the tool does. There's zero wasted language, no redundancy, and it's perfectly front-loaded with the core functionality. Every word earns its place in this minimal description.
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 no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format results come in, what fields are returned, whether there are limitations on search scope, or how results are structured. The agent knows what to search for but not what to expect back or under what constraints the search operates.
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 three parameters thoroughly. The description adds no parameter information beyond what's in the schema - it doesn't explain search syntax examples, typical query patterns, or how results are ordered. The baseline of 3 is appropriate when the schema does all the parameter documentation work.
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 ('GitHub repositories'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling search tools like 'search_code', 'search_issues', or 'search_users' - all of which also search GitHub but for different resource types.
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 this tool is appropriate compared to other search tools (search_code, search_issues, search_users) or when to use it versus browsing repositories through other means. There's no indication of prerequisites, limitations, or typical use cases.
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. It doesn't disclose behavioral traits like authentication requirements, rate limits, whether the fork inherits all branches/tags, what happens if the target organization lacks permissions, or what the response contains. For a mutation tool with zero annotation coverage, this is inadequate.
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 includes essential scope information. Every word earns its place without redundancy.
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, error conditions, or important behavioral constraints. Given the complexity of repository forking (permissions, inheritance, etc.), more context is needed beyond the basic action 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?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples, format details, or edge cases). Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Fork') and resource ('a GitHub repository'), with precise scope ('to your account or specified organization'). It distinguishes from siblings like create_repository (which creates new repos) and other tools that modify existing repos rather than creating forks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying the target ('your account or specified organization'), but doesn't explicitly state when to use this vs alternatives like create_repository or when not to use it. No prerequisites or exclusions are mentioned, leaving some guidance gaps.
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 performs a write operation ('push') but doesn't mention critical behavioral aspects: whether it overwrites existing files, requires authentication/permissions, handles errors, or has rate limits. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves 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, well-structured sentence that efficiently communicates the core functionality without unnecessary words. It's front-loaded with the main action and includes all essential elements: what (push files with content), where (GitHub repository), and how (single commit). Every word earns its place.
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?
For a mutation tool with 5 parameters, 100% schema coverage, but no annotations or output schema, the description is minimally complete. It covers the basic purpose and scope but lacks behavioral details (overwrite behavior, error handling, authentication needs) and output information. Given the complexity of a GitHub file-push operation, more context would be helpful, though the schema handles parameter documentation adequately.
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 all parameters are documented in the schema. The description adds minimal value beyond the schema by implying 'multiple files' (matching the 'files' array parameter) and 'single commit' (related to the 'message' parameter), but doesn't provide additional semantic context about parameter usage, constraints, or relationships. 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('push multiple files with direct content'), the target resource ('to a GitHub repository'), and the operational scope ('in a single commit'). It distinguishes itself from sibling tools like 'push_files_from_path' by specifying 'direct content' rather than file paths, and from 'create_or_update_file' by handling multiple files in one commit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'multiple files with direct content' and 'single commit', suggesting it's for batch updates rather than individual file operations. However, it doesn't explicitly state when to use this tool versus alternatives like 'push_files_from_path' (which likely uses file system paths) or 'create_or_update_file' (which handles single files). The context is clear but lacks explicit comparison guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the batch operation and single-commit behavior, which is useful. However, it lacks details on permissions required, error handling (e.g., if files don't exist), rate limits, or whether it overwrites existing files. For a mutation tool with zero annotation coverage, this leaves gaps in behavioral understanding.
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 with no wasted words. It clearly communicates the tool's function without redundancy or unnecessary elaboration, making it easy 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?
For a mutation tool with 5 parameters and no annotations or output schema, the description is adequate but incomplete. It covers the basic operation but lacks details on behavioral aspects (e.g., side effects, error cases) and doesn't hint at return values. Given the complexity, more context would be beneficial for safe and 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?
Schema description coverage is 100%, so the schema already documents all 5 parameters clearly. The description adds minimal value beyond the schema by implying 'multiple files' and 'filesystem paths,' but doesn't explain parameter interactions (e.g., how 'files' array works) or provide examples. 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('push multiple files'), resource ('from filesystem paths to a GitHub repository'), and scope ('in a single commit'). It distinguishes itself from sibling tools like 'push_files_content' (which likely pushes content directly rather than from filesystem paths) and 'create_or_update_file' (which handles individual files).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'multiple files from filesystem paths' and 'single commit,' suggesting it's for batch operations rather than individual file updates. However, it doesn't explicitly state when to use this tool versus alternatives like 'push_files_content' or 'create_or_update_file,' nor does it mention prerequisites (e.g., authentication, file existence).
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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