Gerrit MCP Server

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by GerritCodeReview

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools target distinct actions and resources, but there is minor overlap between query_changes and query_changes_by_date_and_filters, and between delete_draft_comments (all) and delete_draft_comment (single). The descriptions clarify these boundaries, so an agent can generally select correctly.
Naming Consistency4/5
The overwhelming majority follow a verb_noun pattern (query_, get_, list_, delete_, set_, create_, etc.). The notable exception is 'changes_submitted_together', which is a noun phrase rather than a verb-first name, and 'query_changes_by_date_and_filters' is longer but still verb-initial.
Tool Count3/5
With 25 tools, the server sits at the high end of what is typically considered heavy. While each tool has a specific purpose for Gerrit operations, the count is borderline and may feel bloated compared to more focused servers.
Completeness4/5
The server covers the core Gerrit lifecycle well: create, query, get details, modify state, comment, add reviewers, revert, and abandon. However, it lacks a direct 'submit' operation, which is a notable gap for a Gerrit client, and also misses actions like restoring an abandoned change or editing a commit message.
Average 3/5 across 25 of 25 tools scored. Lowest: 2.2/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 2 community issues answered or closed in the last 6 months
- 3 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 Apache 2.0.
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?
Without annotations, the description carries full responsibility for behavioral disclosure. It merely says 'Retrieves', implying a read operation, but gives no details about return format, pagination, permissions, or what 'comprehensive summary' includes. No side effects, rate limits, or output behavior are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded with the action verb, but it is under-specified. While no words are wasted, the single sentence fails to provide enough substance to be considered effective conciseness; it is merely terse.
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 tool has 3 parameters, no output schema, and no annotations, the description is inadequate. It does not explain what 'comprehensive summary' contains, how options or gerrit_base_url influence the result, or what the return value looks like.
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 input schema has 3 parameters with 0% description coverage, and the description adds no meaning beyond the parameter names. 'options' is particularly vague, and there is no explanation of what data each parameter expects or how it affects the retrieval.
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 uses a specific verb ('Retrieves') with a distinct resource ('comprehensive summary of a single CL'), clearly distinguishing it from sibling tools that fetch individual components like commit messages or file lists. The scope ('single CL') differentiates it from query_changes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not state when to use this tool versus alternatives, nor does it mention any prerequisites, exclusions, or situations where a different tool would be preferable.
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 transparency. 'Abandons a change' implies a mutation but does not disclose any side effects, permission requirements, reversibility, or what the result looks like. This is a significant gap for a state-changing operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is extremely short, it is under-specified rather than appropriately concise. For a tool with multiple parameters and no annotations, one sentence is insufficient to guide an agent, making this a case of brevity over substance.
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, output schema, and any parameter explanation, the description provides only a minimal clue about the tool's purpose. It does not cover return values, side effects, or relationships to sibling tools, making it incomplete for an agent to use 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?
Schema description coverage is 0%, and the description does not mention any of the three parameters (change_id, message, gerrit_base_url). An agent receives no additional semantic meaning beyond the raw schema, so the description fails to compensate for the lack of 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 uses a specific verb 'abandons' and a resource 'change', indicating the primary action. It is clear but does not explicitly differentiate from sibling tools like revert_change or set_work_in_progress, which could also be considered alternative actions.
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, and no exclusions or prerequisites are mentioned. The description simply states the action without any contextual usage advice.
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 only repeats the primary action and does not mention side effects, authentication, or error cases, making it insufficient for a creation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no filler, but it is under-specified and lacks structure. It is concise but not optimally helpful, as it adds little beyond the tool name.
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 that there is no output schema and no annotations, the description should cover inputs, outputs, and side effects. Instead, it only states 'Creates a new change in Gerrit,' leaving out all contextual detail needed for correct usage.
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 input schema has 0% description coverage for its six parameters, and the description itself does not explain any of them (e.g., project, branch, topic). Since coverage is zero, the description must compensate but fails to add any parameter meaning.
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 states the verb 'Creates' and the resource 'a new change in Gerrit', which is clear. However, it does not distinguish this tool from siblings that also deal with changes, such as revert_change or query_changes.
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 lacks prerequisites, exclusions, or references to other tools, which is a significant gap given the many sibling functions.
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, the description carries full burden but reveals no behavioral traits: no mention of read-only nature, return format, pagination, authentication, or whether draft comments are included. The phrase 'responding to comments' could mislead an agent into thinking the tool can post responses, which is likely not the case.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at one sentence, but the list of use cases is somewhat redundant (reviewing feedback, reading comments, analyzing comments) and lacks a clear structure. It is not overly verbose, but it could be more direct.
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 that there is no output schema and no annotations, the description should provide more context about return values, scope of comments, and relationship to sibling tools. It does not, leaving significant gaps for an agent to safely invoke and interpret results.
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%, and the description provides no explanation of change_id or gerrit_base_url. Property names are self-explanatory at a basic level, but the description does not clarify formats, defaults, or optionality beyond the schema, so it adds no value.
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 says the tool is 'useful for reviewing feedback, reading comments on a change, analyzing comments, and responding to comments,' which implies listing/reading comments but does not explicitly state 'lists comments for a change.' It lacks a specific verb+resource statement and does not differentiate from sibling tools like list_draft_comments.
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 mention of when to use this tool versus alternatives. It vaguely implies usage for reviewing comments but does not indicate that draft comments should be handled by list_draft_comments or that get_change_details might include comment summaries. No exclusions or alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral disclosure. It only states the action without revealing what 'most recent' means, whether the result is a single change or list, or any limitations. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundancy. However, it is under-specified for the tool's complexity, but as a matter of conciseness it has no waste.
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?
The tool has no annotations, no output schema, and only a minimal description. It does not explain return values, the meaning of 'most recent', or how to specify the user. This is incomplete for an agent to reliably invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description mentions 'for a user' but does not explain the 'user' parameter format (email, username, ID) nor the optional 'gerrit_base_url' parameter. The description fails to compensate for the schema's lack of explanatory text.
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 uses a specific verb ('Gets') and resource ('most recent CL for a user'), clearly indicating the tool's function. However, it does not explicitly distinguish itself from siblings like query_changes or get_change_details, so it falls short of 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 usage guidance is provided. The description does not mention when to use this tool versus alternatives like query_changes, nor does it describe prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the effect without mentioning implications such as whether it is a write operation, if it requires specific permissions, or whether it is reversible. This is insufficient 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no fluff. It front-loads the core purpose effectively. However, it is under-specified, which is more a completeness issue than a conciseness issue, so it earns a good score here.
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 low complexity of the tool (2 params, no output schema), a brief description might suffice, but the complete lack of behavioral context—such as the meaning of 'ready for review,' effects on existing state, or relationship to WIP—makes it incomplete. No annotations or output schema compensate.
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 schema description coverage is 0%, and the description adds no information about the parameters. It does not explain what change_id refers to or how gerrit_base_url is used, leaving the agent to rely solely on parameter names.
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: 'Sets a CL as ready for review.' It uses a specific verb and resource, and implies distinction from the sibling tool set_work_in_progress by referencing the opposite state. However, it does not explicitly differentiate from other related tools or mention alternatives.
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 usage guidance is provided. The description does not indicate when to use this tool, any prerequisites, or exclusions. It does not reference workflow relationships like the opposite of set_work_in_progress, leaving the agent without context for choosing this over alternatives.
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, the description carries the full burden of behavior disclosure, but only states 'searches'. It does not describe the return format, the effect of 'limit' or 'options', how 'gerrit_base_url' is used, or any other behavioral details that would help the agent anticipate side effects or output.
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 sentence, front-loaded with the core action. It contains no filler or redundancy, making it highly concise and easy to parse.
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?
The description is severely under-specified for a tool with 4 parameters, no annotations, and no output schema. It lacks essential context such as query syntax, result limits, configuration options, and how it relates to sibling tools, making it inadequate for reliable 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?
The description only hints at the 'query' parameter ('query string') and completely ignores 'limit', 'options', and 'gerrit_base_url'. Since schema description coverage is 0%, the description fails to compensate for the missing parameter explanations, leaving most parameters underspecified.
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 function: searching for CLs (change lists) based on a query string. It uses a specific verb and resource, and implies a free-form query input, which differentiates it from the more structured sibling query_changes_by_date_and_filters, though not explicitly.
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 usage guidance is provided. The description does not indicate when to use this tool versus alternatives such as query_changes_by_date_and_filters or get_change_details. There is no mention of prerequisites, contexts, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states the state change but omits behavioral details such as whether the change must be open, whether the message parameter is used to notify, whether the action is reversible, or any permission requirements. Since annotations are absent, this minimal statement carries full burden and 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?
Single sentence, direct, and free of extraneous content. It is appropriately concise for a simple state-changing 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?
The description is adequate for stating the core action but fails to explain parameter roles or output behavior. Given no output schema and no usage guidance, the tool context is incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description makes no reference to any parameters. With schema coverage at 0%, the description provides no additional meaning for message, change_id, or gerrit_base_url, forcing the agent to rely solely on names.
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 identifies the action ('Sets'), the resource ('a CL'), and the target state ('work-in-progress'). It distinguishes the tool from sibling set_ready_for_review, which performs the opposite action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage 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 like set_ready_for_review or abandon_change. The description offers no context on prerequisites or typical workflow placement.
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?
There are no annotations, so the description carries the full burden. It only states 'suggests reviewers' without disclosing whether the operation is read-only, how the query is interpreted, what ranking criteria apply, or what the output contains. This leaves safety and side-effect behavior ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is succinct and front-loaded, with no filler. However, it could be restructured to include key behavioral context without becoming verbose.
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 six parameters, no output schema, and no annotations, a single sentence is insufficient to guide correct invocation. Important aspects like expected output, parameter interactions, and whether suggestions mutate anything are missing.
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 input schema has six parameters with 0% description coverage. The description mentions only 'query' and 'change', adding minimal meaning for those two parameters; 'limit', 'exclude_groups', 'reviewer_state', and 'gerrit_base_url' are not explained at all.
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 uses a specific verb 'suggests reviewers' and identifies the resource ('a change') and input ('a query'). It clearly distinguishes from sibling 'add_reviewer' by focusing on recommendation rather than modification, but it does not elaborate on the returned reviewer list or ranking.
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 siblings like 'add_reviewer' or 'query_changes'. There are no use-case scenarios, exclusions, or conditions 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?
No annotations are present, so the description carries the full burden of behavioral disclosure. It only states the core function, omitting any details about side effects, prerequisites, input behavior, output format, or limitations. 'Computes and lists' hints at a read-only operation but doesn't go further.
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, focused sentence that conveys the essential purpose without unnecessary words. It is front-loaded with the verb and clearly structured, 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?
The tool has three parameters, no output schema, and no annotations, yet the description provides only one sentence. It fails to define what 'changes submitted together' means, how options affect behavior, or what the result contains, making it incomplete for practical use.
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?
With 0% schema description coverage, the description must compensate by explaining parameters, but it does not mention change_id, options, or gerrit_base_url. The only implicit reference is 'a given CL' mapping to change_id, but without definition, the agent is left guessing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb ('Computes and lists') and resource ('changes that would be submitted together with a given CL'). This distinguishes it from sibling tools like query_changes or get_change_details, which either search broadly or fetch a single change.
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 does not provide any when-to-use guidance or mention alternatives. It implies a specific use case (finding changes submitted together) but offers no explicit context, exclusions, or comparison with the many sibling 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention return format, whether files include deletions/renames, or any auth/permission requirements. The description only states the basic action without additional 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 a single concise sentence with no filler words. It directly states the action and target resource, earning every word.
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 simple list operation with no output schema or annotations, the description is minimally adequate but lacks important context about the return value (e.g., file paths, statuses) and boundary cases like what 'modified' includes. It does not fully prepare an agent to interpret results, but given the tool's simplicity, it is borderline acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain either parameter. 'change_id' and 'gerrit_base_url' are only defined by their names, with no added meaning about how they relate to the 'CL' mentioned. The description leaves parameter usage entirely to schema inference.
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 'Lists all files modified in the most recent patch set of a CL' uses a specific verb (lists) and resource (files modified in a CL's latest patch set), clearly distinguishing it from sibling tools like get_file_diff or get_change_details. It precisely communicates the operation's scope.
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 (e.g., get_file_diff for individual file contents, get_change_details for overall CL info). The description only states what it does, leaving the agent to infer appropriate usage from the name and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It states the destructive scope ('ALL draft comments') but does not mention irreversibility, permission requirements, or effects on published comments. The 'ALL' emphasis provides some warning, but key details are missing.
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 with a clear verb and object. It is extremely concise with no redundant 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's destructive nature, lack of annotations, and 0% schema description coverage, the description is too sparse. It omits parameter explanations, behavioral caveats, and differentiation from the singular variant, making it incomplete for confident invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the meaning of `change_id` or `gerrit_base_url`. It only mentions 'a CL', which loosely hints at change_id but does not map parameters explicitly, leaving the agent to infer crucial details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Deletes'), the resource ('ALL draft comments'), and the scope ('on a CL'), distinguishing it from the singular `delete_draft_comment` sibling by emphasizing 'ALL'.
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 explicit guidance on when to use this tool versus the singular `delete_draft_comment` or other alternatives. It implies usage through 'ALL' but does not state when not to use it or describe exclusions.
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, the description carries the burden of behavioral disclosure. It states the action ('gets') and scoping ('current patch set') but does not mention read-only nature, return format, error conditions, or any side effects. Minimal behavioral context beyond the name.
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 with no fluff. It is appropriately sized and front-loaded with the core action and resource.
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?
The tool has no output schema, and the description fails to explain what is returned or when to use it. The simple schema limits complexity, but the description is insufficiently complete for an agent to fully understand the tool's behavior and prerequisites.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the parameters change_id or gerrit_base_url. It only refers to 'a change,' offering no additional meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets the commit message of a change from the current patch set. This distinguishes it from siblings like get_change_details or query_changes, which serve different purposes.
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 when needing the commit message from the current patch set, but it does not explicitly mention when not to use it or suggest alternatives. Context is clear but lacks explicit guidance or exclusions.
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 for behavioral disclosure. It reveals only that a comment is posted (implying a write operation) but does not mention whether it is published or draft, side effects like notifications, permission requirements, or reversibility. This is a significant gap 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, well-structured sentence that immediately states the action and target. There is no fluff or redundancy; every word contributes to the core meaning. It is appropriately concise for a tool with a clear 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 tool has 7 parameters (4 required), no annotations, and no output schema, the description is too sparse to be considered complete. It omits important behavioral context, return behavior, and any relationship to sibling tools like post_draft_comment. A more capable description would clarify the difference between posting a review comment and a draft comment, and what happens after posting.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description does not explicitly map any parameters. It hints at 'specific line', 'file', and 'CL', which faintly suggests line_number, file_path, and change_id, but it fails to clarify the role of message, labels, unresolved, or gerrit_base_url. Parameter meaning is almost entirely left to the schema, which itself lacks descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('posts') and resource ('review comment on a specific line of a file in a CL'), clearly distinguishing it from sibling tools like post_draft_comment or list_change_comments. It is immediately obvious what action the tool performs and on what target.
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 gives no guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. It only states the core action, leaving the agent to infer context. No explicit or implied usage direction beyond the action itself.
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, the description must disclose behavioral traits, but it only mentions creating a new CL. It does not state whether the original change is abandoned or modified, whether special permissions are needed, or any side effects/reversibility. This is a mutation tool with insufficient 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 concise sentence ('Reverts a single change, creating a new CL.') with no wasted words. It is front-loaded and directly states the action and outcome.
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?
Although the tool is simple, the description lacks essential context for a mutation tool with no annotations or output schema. It does not explain the result on the original change, the state of the new CL, or how it differs from 'revert_submission' and 'abandon_change', making it under-specified for reliable tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any parameter names or semantics. It fails to compensate for the low coverage, leaving the agent without additional guidance beyond the schema's minimal titles like 'Change Id' and 'Message'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reverts a single change and creates a new CL. This uses a specific verb and resource, and distinguishes from similar siblings like 'revert_submission' (which reverts a submission) and 'abandon_change' (which abandons without creating a new CL).
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 phrase 'a single change' implies use for individual changes rather than a whole submission, but it does not explicitly mention when to use this tool over alternatives or provide exclusions. The guidance is minimal and relies on 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, the description should fully disclose behavior. It merely states the action (extract) but does not describe the return format, behavior when no bug IDs are found, or whether the operation is purely read-only. This leaves significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler words. It is appropriately concise for a simple extraction tool, though it sacrifices detail for brevity.
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?
The tool has no annotations and no output schema, so the description must carry the burden of explaining return values and edge cases. It fails to mention what the output looks like (list, array, empty result) or any error conditions, leaving the description incomplete even for a low-complexity tool.
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%, and the description fails to explain either parameter. It doesn't explicitly link change_id to 'a CL' nor clarify the optional gerrit_base_url. The schema titles alone are insufficient, so the description does not compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Extracts') and resource ('bug IDs from the commit message of a CL'). It unambiguously distinguishes itself from siblings like get_commit_message (which returns the full message) and get_change_details (which returns change metadata).
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: when you need bug IDs from a CL's commit message, use this tool. However, it does not explicitly compare against alternatives (e.g., get_commit_message) or state when not to use it, providing only implicit 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?
No annotations are provided, so the description carries the full transparency burden. It reveals the empty-string deletion behavior, which is helpful, but omits mutation implications such as permissions, overwriting of existing topics, side effects, or response behavior. For a write operation, 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?
Exactly two sentences, no filler, and the most important behavioral note (empty string deletes) is included. Every word earns its place; the description is ideally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is conceptually simple and the description covers its core purpose plus a key edge case. However, it lacks usage context, parameter elaboration, and mutation details, making it only minimally complete for an agent that must invoke it correctly in varied situations.
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. It implicitly references the topic and change_id meanings but does not explicitly explain any of the three parameters, including the optional gerrit_base_url. The context clues are thin and do not fully disambiguate parameter roles.
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 states a clear action verb ('Sets') and specific resource ('topic of a change'), and distinguishes the behavior with the notable edge case of an empty string deleting the topic. This unambiguously differentiates it from sibling tools like set_ready_for_review or set_work_in_progress.
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 gives no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It merely states what it does, leaving the agent to infer usage from the tool's name and sibling 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 must carry the behavioral disclosure burden. It only states the verb 'deletes' without describing permanence, permissions, or side effects. This is minimal for a destructive operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the verb and object. It contains no filler or wasted words.
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?
The description is extremely brief and lacks information about return values, error handling, preconditions, or post-conditions. While the tool is simple, the absence of annotations and output schema makes the description incomplete for an agent to fully understand the behavior.
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 explain parameters. It identifies draft_id as the identifier and implies change_id is the CL, but does not explain the optional gerrit_base_url or provide details on parameter formats or relationships.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool deletes a single draft comment on a CL by draft ID, using a specific verb and resource. The word 'single' distinguishes it from the sibling tool 'delete_draft_comments' (plural).
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 for deleting one draft comment but does not explicitly state when to use this tool over alternatives, such as delete_draft_comments. It also lacks any prerequisites or context about when deletion is appropriate.
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 must disclose behavioral context. It only says 'Retrieves the diff' and gives no details about permissions, output format, error handling, or side effects. It doesn't even confirm it's a read-only operation beyond the verb itself.
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 concise sentence that effectively communicates the tool's core purpose. No unnecessary words.
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?
The tool has no output schema and no annotations, so the description should clarify what the returned diff looks like and under what conditions it succeeds. It also doesn't mention the optional gerrit_base_url or any prerequisites. The description is under-specified for an agent to use it reliably.
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%. The description does not explain any of the three parameters. While change_id and file_path are somewhat self-explanatory, gerrit_base_url remains opaque. The description adds no meaning beyond the property names.
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 a specific action (retrieves) and resource (diff for a single file within a CL). It distinguishes from siblings like list_change_files (which lists files) and get_change_details (which provides change-level info).
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 the tool is for retrieving a single file's diff, but it does not explicitly contrast it with alternatives or state when not to use it. There is no mention of sibling tools like query_changes or get_change_details.
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?
Although no annotations are provided, the description does reveal a key behavioral trait: it creates new CLs as a side effect. However, it does not disclose whether the original submission is modified or removed, permissions required, or other consequences, leaving much for the agent to infer.
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, concise sentence with no redundant words. It is appropriately front-loaded and every word adds value.
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 three parameters, no annotations, and no output schema, the description is too sparse. It lacks parameter semantics, usage context, and any details about outcomes or side effects beyond the creation of CLs, making it incomplete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no information about the parameters (message, change_id, gerrit_base_url) beyond what the schema already shows. With 0% schema coverage, the description should compensate but does not, leaving the agent to guess parameter semantics from names alone.
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 a specific action ('Reverts an entire submission') on a specific resource, and distinguishes itself from the sibling 'revert_change' by emphasizing 'entire submission' and noting it creates 'one or more new CLs'.
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 such as 'revert_change' or 'abandon_change'. The description simply states what the tool does without discussing appropriate scenarios or exclusions.
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, the description must fully disclose behavioral traits. It only states the basic action ('adds') without mentioning permissions, whether existing reviewers are modified, idempotency, or error behavior. This is minimal 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?
A single, front-loaded sentence that conveys the essential action without any filler. 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 simple mutation tool with no annotations, output schema, or schema descriptions, the description conveys the core behavior but omits important details like accepted state values, return behavior, and usage context. It is minimally adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds some semantics by clarifying that the 'state' parameter controls whether the addition is a reviewer or CC, and that the 'reviewer' can be a user or group. However, it does not clarify 'change_id' or 'gerrit_base_url', leaving those parameters under-explained.
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 uses a specific verb 'adds' with a clear resource 'user or group to a CL' and clarifies the dual role 'reviewer or a CC'. This distinguishes it from siblings like suggest_reviewers, which only suggests rather than adds.
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 the tool is used when you need to add a reviewer or CC to a CL, but it does not explicitly state when to prefer it over alternatives like suggest_reviewers or when not to use it. There is no mention of prerequisites or edge cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden of disclosing behavior. 'Lists' clearly implies a read-only, non-destructive operation, which is adequate. However, it does not disclose additional traits such as whether drafts are only visible to the author or if any special authentication is needed. The description is minimal but 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It clearly states the action and object. While it is sparse, it is appropriately concise for a simple list operation and does not waste words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (simple list operation, two parameters, no output schema), the description is mostly sufficient. It states what the tool does and implies the return is a list of draft comments. However, the lack of an output schema means the description could have clarified the return format or any limitations (e.g., pagination), but this is not critical for such a straightforward operation.
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. It references 'a CL' which provides minimal context for the change_id parameter but does not explain the gerrit_base_url parameter at all. The description adds no substantial meaning beyond the parameter names and types already present in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Lists all draft comments on a CL.' The verb 'lists' is specific and the resource 'draft comments' distinguishes it from sibling list_change_comments (which presumably lists published comments). It is unambiguous and directly conveys the tool's purpose.
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 does not explicitly state when to use this tool versus alternatives. It implies usage through the phrase 'draft comments,' suggesting it is appropriate when viewing unpublished comments, but it lacks explicit exclusions such as 'use list_change_comments for published comments.' Context is present but not explicit 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?
With no annotations, the description carries the full burden. It discloses the draft visibility behavior and explains how to create a threaded reply. However, it omits other behavioral aspects such as authentication requirements, whether existing drafts are overwritten, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences with no filler, front-loaded with the primary action.
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 12 parameters and no output schema or annotations, the description is too sparse. It covers core draft behavior but leaves many parameters and return expectations unexplained.
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 schema has 12 parameters with 0% description coverage, and the description only explains in_reply_to. It does not clarify message, line ranges, character positions, suggestion, unresolved, or gerrit_base_url.
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 identifies the action ('Creates'), the object ('draft review comment'), and the location ('specific line of a file in a CL'). It distinguishes from sibling tools like post_review_comment by emphasizing 'draft' semantics.
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?
It states the draft is only visible to the author until published, implying it should be used for preparatory comments, and explicitly mentions the in_reply_to parameter for threading. However, it does not explicitly name alternatives like post_review_comment or publish_drafts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the main behavioral effect (draft comments becoming visible to other reviewers in one batch), which is helpful. However, it omits details like the irreversibility of the action, permission requirements, or what happens to the draft records afterward, so it is adequate but not rich.
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 two sentences, front-loaded with the action, and every sentence contributes value. It is concise with no filler, and the analogy to the Gerrit UI is a compact way to convey behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple mutation but has four parameters and no output schema or annotations. The description covers the core action but omits parameter semantics and edge cases. It is minimally adequate for an agent to understand the main purpose, but not complete for correct invocation with all parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining the parameters, but it mentions none. The schema itself only provides titles and defaults, not meanings. The labels and message parameters are completely unexplained, leaving the agent without guidance on how to use them.
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 states a specific action ('Publishes all pending draft comments on a CL as a single review') with a clear resource and outcome. It also distinguishes from sibling tools by emphasizing the batch nature ('in one batch') and the Gerrit 'Send' equivalence, making it unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for use: when you have pending draft comments and want to send them as a review. The analogy to clicking 'Send' in Gerrit provides practical guidance, but it does not explicitly name alternatives or exclusions, such as when to use post_draft_comment or post_review_comment instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the default status ('merged'), the conditional behavior of the project filter (only applied if gerrit_base_url is not explicitly provided), and the fallback to a default Gerrit instance. This is valuable context, though it omits return format and error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a concise opening summary followed by an Args list. Each parameter is individually documented because the schema lacks descriptions, so the length is justified. The front-loaded summary gives immediate clarity about the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all parameters and the core search behavior, but it does not explain the return value format, date inclusivity semantics, or pagination behavior when 'limit' is null. With no output schema, this leaves notable gaps for an agent needing to interpret the results correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the Args section in the tool description is the sole source of parameter meaning. It explains all 7 parameters with examples (e.g., date formats), clarifies the default for 'status', and provides crucial conditional logic for 'project' and 'gerrit_base_url'. This fully compensates 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'Searches for Gerrit changes within a specified date range, optionally filtered by project, a substring in the commit message, and change status.' This identifies the specific action, resource, and scope, and the name 'by_date_and_filters' distinguishes it from the sibling 'query_changes' tool.
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 the tool should be used when searching changes by date with optional filters, but it does not explicitly contrast it with alternatives like 'query_changes' or state when not to use it. There is no exclusion guidance, leaving the agent to infer usage from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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