bitbucket-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct resource and action. Comment tools are differentiated by operation (list/add/inline/reply/edit/delete), and PR views are clearly separated by data type (diff, diffstat, commits, activity, build status). No two tools appear to serve the same purpose.
Naming Consistency3/5
Most tools follow a verb_noun pattern (list_repos, create_pull_request), but there are notable deviations: data-view tools use a noun-first 'pr_' prefix (pr_diff, pr_commits, pr_activity, pr_build_status) and 'pipeline_steps' lacks a verb. The resource is inconsistently called 'pull_request' in some tools and 'pr' in others, and comment actions use varying prepositions (on, to). Still, the names remain readable and understandable.
Tool Count2/5
At 32 tools, the server exceeds the 'borderline' range of 16-25 and feels heavy. While many tools are justified for a Bitbucket API, there is some overlap (e.g., list_commits vs pr_commits) and the PR comment workflow alone accounts for six tools. The count would be more appropriate if consolidated or scoped tighter, such as focusing on core PR operations.
Completeness3/5
The pull request lifecycle is thoroughly covered (create, update, approve, merge, decline, comments, diff, commits, activity, build status). However, repository management is incomplete: there is no create/update/delete repo, and branch operations are limited to listing. These are notable gaps for a Bitbucket integration and could force agents to use external tools.
Average 3.6/5 across 32 of 32 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
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If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must explain behavioral side effects. It merely states 'Request changes' without disclosing that this mutates the PR's review status, notifies the author, or may require specific permissions. For a mutating tool, this is a significant transparency gap.
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?
The description is extremely short, but it wastes space by repeating the parameter list exactly as in the schema. There is no efficient prose that enhances understanding. This is under-specification rather than effective conciseness, as the Args block duplicates structured data without adding 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?
Despite having an output schema, the tool is a mutating operation with no annotations and no parameter descriptions. The description fails to provide critical context such as when the operation is valid, what side effects occur, or what the response represents. The input semantics are incomplete, making the tool difficult to use correctly.
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 parameters. It only lists parameter names (pr_id, workspace, repo) with no additional meaning. It does not clarify which are required, how to obtain the slug, or that workspace and repo have defaults. This provides zero value beyond the schema itself.
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: 'Request changes on a pull request.' The verb 'Request changes' is specific and differentiates from sibling tools like approve_pull_request, merge_pull_request, and decline_pull_request. However, it does not explicitly mention alternatives or contrast with remove_request_changes, so a perfect score is not warranted.
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 (e.g., when a PR is open, when you are a reviewer, or how this differs from remove_request_changes). No prerequisites or contexts are mentioned. This leaves the agent without enough information to decide between this and similar PR review tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full responsibility. It merely states 'Approve a pull request' without disclosing mutating effects, permission requirements, reversibility, notifications, or potential side effects. For a write operation, this is a critical omission.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with a one-line purpose followed by an args list. No terse or redundant language. It loses a point because it is so sparse that it borders on under-specification, but that is more relevant to completeness than 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?
With no annotations and no visible output schema, the description fails to cover critical context: return values, error conditions, permission requirements, or how approval affects the PR workflow. For a mutating tool, this is significantly incomplete.
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 lists parameter names with minimal descriptors ('PR ID number', 'Workspace slug', 'Repository slug') but does not explain requiredness, defaults, or how workspace/repo are resolved when omitted. This adds very little beyond the schema's type information.
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 'Approve a pull request' with a specific verb and resource. This clearly distinguishes the tool from sibling operations like merge_pull_request, decline_pull_request, or request_changes_on_pr.
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 unapprove_pull_request, request_changes_on_pr, or other review actions. It lacks context about prerequisites, workflow placement, 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 of behavioral disclosure. It only says 'Stop' but does not explain cancellation semantics, irreversibility, required pipeline state, or error behavior. This is minimal for a mutating 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 very concise: one clear sentence and a compact arg list. Every element earns its place, with no filler or repetition of schema data.
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?
Despite having an output schema (which could explain return values), the description lacks context about preconditions, side effects, or error conditions. The arg list is clear but does not explain the relationship between workspace/repo and the pipeline, leaving a gap for correct invocation.
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 basic meaning to all three parameters, labeling pipeline_uuid as coming from list_pipelines and workspace/repo as slugs. Schema coverage is 0%, so this is helpful, but it does not clarify the optionality or necessity of workspace/repo, nor how they affect the lookup.
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 a specific action ('Stop a running pipeline') identifying both the verb and the resource. It distinguishes from siblings like trigger_pipeline and list_pipelines, though it does not explicitly mention alternatives or scope limitations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The arg description for pipeline_uuid hints at a prerequisite (from list_pipelines), but there is no stated context, exclusions, or comparison to trigger_pipeline or pipeline_steps.
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 provided, so the description must disclose behavioral traits. It only states 'Delete a PR comment' without revealing whether the deletion is permanent, what permissions are required, or how errors are handled. The destructive nature is implied but not elaborated, and there is no mention of reversibility or 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?
The description is extremely concise, leading with a clear one-sentence purpose and followed by a compact parameter list. There is no extraneous text or repetition of schema details, making it efficient 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 absence of annotations and an output schema, the description is too sparse to provide a complete picture. It does not mention error behavior, idempotency, or whether workspace/repo are required in context. For a destructive operation, the agent would benefit from knowing what happens on failure or if the comment does not exist, but such details are omitted.
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 0%, so the description carries the burden of explaining parameters. It lists all four arguments with brief glosses (e.g., 'Comment ID to delete', 'Workspace slug', 'Repository slug'), which adds some clarity beyond the raw schema. However, it does not explain that pr_id is the ID of the containing PR, nor does it note that workspace and repo are optional (defaulting to empty strings), leaving some interpretation to the agent.
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: 'Delete a PR comment.' This is a specific verb (delete) plus resource (PR comment), leaving no ambiguity about the tool's function. It also distinguishes itself from sibling tools like edit_pr_comment or reply_to_pr_comment, 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 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 alternatives. It does not mention exclusions, prerequisites, or scenarios where a different tool might be more appropriate. With many sibling tools for commenting, such as edit_pr_comment and comment_on_pr, this lack of differentiation guidance makes it hard for an agent to choose confidently.
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 behavior on its own. It only mentions parameter defaults, omitting details about error handling, rate limits, authentication, or read-only status. While 'get' implies non-mutating behavior, the description adds minimal transparency beyond the function 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 very concise, with a one-sentence purpose followed by a clean argument list. Every line serves a purpose, and there is no redundant or vague filler.
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 retrieval tool with an output schema, the description covers the basic purpose and parameter semantics. However, it lacks usage guidelines and behavioral context, such as what 'default' refers to or how errors are handled, making it only minimally complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description assigns meaning to both parameters by calling them 'workspace slug' and 'repository slug' and explains that they use defaults. Given the 0% schema description coverage, this is essential. However, it does not specify how defaults are determined, leaving some ambiguity.
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 'Get repository details' clearly states the action and target resource, making the core purpose obvious. However, it does not explicitly differentiate itself from sibling tools like list_repos, though the singular 'repository' and use of repo/workspace parameters imply a single-repo lookup.
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_repos or get_pull_request. The only usage-related note is that workspace and repo slugs default if not provided, but it does not explain the intended context or when to avoid using this tool.
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 for behavioral disclosure, but it only says 'Decline (close without merging)' without explaining side effects (e.g., whether approvals are reset, if notifications are sent, or if the action is reversible). The optional workspace/repo parameters and their defaults are also not clarified, which could mislead an agent into thinking they are required.
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 plus a clean arg list, front-loaded with the purpose. There is no redundancy; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the tool is a mutation with no annotations and a sparse description. It lacks usage context, behavioral side effects, and parameter semantics, making it less complete than expected for a PR-decline operation among many PR-related siblings.
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 lists all three params with minimal definitions ('PR ID number', 'Workspace slug', 'Repository slug'), but these add little beyond the parameter names and do not explain optionality, defaults, or how to obtain the slugs. The requiredness (only pr_id is required) is left to 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 action with a specific verb ('Decline') and resource ('pull request'), and adds 'close without merging' to distinguish it from merge_pull_request. This is unambiguous and aligns with the tool name.
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 use case (when you want to reject a PR without merging) but does not explicitly contrast with alternatives like merge_pull_request or request_changes_on_pr. No exclusions or when-not-to-use guidance is provided, so it relies on the reader to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It merely says 'recent pipelines' without explaining ordering, pagination, the meaning of 'recent', or any authentication requirements. The minimal detail leaves the agent to guess about 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 concise and front-loaded. The first sentence states the purpose immediately, followed by a brief two-line argument list. Every sentence serves a purpose, and there is no extraneous text.
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?
While the tool is relatively simple and has an output schema, the description is thin. It does not specify the upper bound of 'recent', whether results are paginated, or if any filtering options exist. For a straightforward list tool, this is minimally viable but lacks context that would help an agent use it confidently.
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 0%, so the description must compensate. It clarifies that 'workspace' and 'repo' are slugs, providing meaning beyond the bare schema titles. However, it does not explain how these two parameters relate or whether both are required to identify a repository, leaving important gaps.
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 ('List') and the resource ('recent pipelines (builds) for a repository'). It distinguishes itself from sibling tools like trigger_pipeline, stop_pipeline, and pipeline_steps, which perform different operations.
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 usage guidance beyond the basic naming of the tool. It does not mention when to use this tool versus alternatives, nor does it specify any prerequisites or conditions. The only context is that it lists pipelines for a repository.
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 merely says 'List all comments', implying a read operation but offering no details about pagination, ordering, inclusion of inline comments, or response structure. This is minimal 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 extremely concise, with a one-sentence purpose followed by a simple list of arguments. It is front-loaded and contains no unnecessary words, making it highly efficient.
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 has a clear purpose, parameter list, and an output schema exists to describe return values. However, it lacks usage context, behavioral details, and a note that workspace and repo are optional with defaults. For a simple listing tool, it is minimally viable 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?
The schema has 0% description coverage, so the description must compensate. It does provide brief explanations for each parameter (pr_id: PR ID number, workspace: Workspace slug, repo: Repository slug), adding meaning beyond the schema's type-only fields. However, it does not mention that workspace and repo have defaults or clarify formats, so it is adequate but not comprehensive.
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 'List all comments on a pull request', using a specific verb (List) and a distinct resource (comments on a PR). This differentiates it from siblings like delete_pr_comment, comment_on_pr, and reply_to_pr_comment.
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 alternatives like pr_activity or pr_diff. It only states what it does, leaving the agent to infer the appropriate context without any exclusions or prerequisites.
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 only says 'Get the full diff' with no disclosure of auth requirements, error behavior, output format, or any side effects. It gives minimal behavioral information beyond what the name implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one main sentence plus a structured Args list. There is no fluff, and the purpose is front-loaded. Every sentence contributes to understanding the tool.
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 read tool with an output schema, the description is minimally complete: it identifies the action and lists parameters. However, it omits context about which parameters are required (beyond schema), defaults, and how the diff is returned (e.g., unified/patch format). It also lacks any guidance on when to choose this over similar PR tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions for properties (0% coverage), and the description compensates by listing each arg with a short explanation: 'pr_id: PR ID number', 'workspace: Workspace slug', 'repo: Repository slug'. This adds basic meaning (e.g., format hints), but it does not clarify optionality, defaults, or how workspace/repo are resolved, leaving gaps.
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 'Get the full diff of a pull request' uses a specific verb ('Get') and resource ('full diff of a pull request'), clearly distinguishing it from siblings like pr_diffstat (which gets diff statistics) and get_pull_request (which gets PR metadata). The word 'full' also clarifies the 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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention pr_diffstat, pr_commits, or get_pull_request, nor does it give context on prerequisites or typical scenarios. The Args list only documents parameters, not 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 the full burden of behavioral disclosure. It only states the action and does not disclose side effects, permissions, reversibility, or behavior when the user hasn't approved. The phrase 'your approval' gives minimal context but 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 brief and front-loaded with a clear purpose sentence, followed by a minimal arg list. It is free of unnecessary prose, though the arg list largely duplicates information already present in the schema.
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, single-purpose mutation with an output schema, the description covers the core action and args. However, it omits any mention of preconditions, side effects, or required vs optional parameters, leaving the agent with incomplete context for a state-changing 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%, so the description must compensate. It lists three args with terse explanations ('PR ID number', 'Workspace slug', 'Repository slug') that add little beyond the property names and types. It also fails to indicate that workspace and repo are optional (they have defaults) or clarify what a slug means.
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 opens with 'Remove your approval from a pull request,' which is a specific verb+resource phrase that precisely describes the action. It clearly distinguishes this from sibling tools like approve_pull_request, request_changes_on_pr, and merge_pull_request.
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 action itself implies the use case (withdrawing your approval), but the description provides no explicit guidance on when to choose this over other PR state-change tools or mention alternatives. There are no exclusions or contextual preconditions, so usage guidance is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does not mention that this is a write operation that will replace the comment body, nor does it discuss permissions or reversibility. The phrase 'existing PR comment' only implies it does not create new comments.
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 parts: a clear one-line purpose and a concise argument list. It is front-loaded and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple input schema and an output schema (per context signal), so the description need not return values. It fully documents all parameters, but lacks usage guidelines and behavioral caution, which leaves some contextual 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?
The schema has 0% description coverage, so the description compensates by listing each parameter with brief semantics, e.g., 'body: New comment text' and 'workspace: Workspace slug'. This adds meaning beyond the bare titles, but omits details like defaults or relationships between parameters.
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 'Edit an existing PR comment' with a specific verb and resource. It distinguishes itself from sibling tools like delete_pr_comment and comment_on_pr.
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 delete_pr_comment or reply_to_pr_comment. It simply states the action and lists parameters without exclusions 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?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It does not explicitly state that this is a read-only operation, nor does it mention ordering, pagination, result limits, or any side effects. The only behavioral hint is 'defaults to all' for the branch parameter, which is more parameter semantics than behavioral 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 extremely concise: a one-line purpose followed by a structured argument list. It is front-loaded with the main action and contains no unnecessary words or repetition. Every sentence and argument 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?
The description covers the essential purpose and all parameters, and an output schema exists, so return structure is not required. However, 'recent' is undefined, with no mention of how many commits are returned or their ordering. It also lacks any context on limitations or alternatives, making it a minimum viable description rather than a complete one.
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, with all parameters as generic strings and empty defaults. The description compensates fully by explaining each parameter: 'branch' is optional and defaults to all, 'workspace' is a slug, and 'repo' is a slug. This provides clear meaning beyond the schema, fully covering the gap.
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 'List recent commits, optionally filtered by branch' – a clear verb+resource+scope. However, it does not explicitly distinguish itself from the sibling tool 'pr_commits', which also lists commits (for a pull request). The context of workspace/repo/branch parameters implies repository-wide commits, but the lack of explicit sibling differentiation keeps it from 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 gives no guidance on when to use this tool versus alternatives like pr_commits or browse_source. It only states its function and parameters, with no mention of ideal contexts, exclusions, or alternatives. This leaves the agent to infer usage on its own.
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 traits on its own. It says 'browse' but does not specify whether this returns file contents, a directory listing, or both. It also does not mention side effects, authentication needs, or error behavior. The description only indicates refs are supported (branch/tag/commit) and that empty path refers to root, which is minimal 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 composed of a single sentence stating the purpose followed by a compact arg list. Every sentence provides necessary information, and the structure is front-loaded with the core function. There is no fluff or repetition of schema defaults; the arg list adds semantics not present in the schema.
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 the core purpose and parameters, and the presence of an output schema means return values need not be explained. However, given no annotations, it omits explicit read-only status or any behavioral caveats. For a simple read-oriented tool, the description is mostly adequate but leaves open whether this is a read-only operation and what 'browse' entails (content vs. listing), which is a notable gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by listing all 4 parameters with brief meanings: path (file or directory path, empty for root), ref (branch/tag/commit, default main), workspace slug, and repo slug. This adds value beyond the schema by clarifying the semantics of 'path' and the default for 'ref'. However, it could go further by explaining relationships (e.g., workspace/repo format) or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Browse repository source files at a specific ref (branch/tag/commit)'. This uses a specific verb ('browse') and resource ('repository source files'), distinguishing it from sibling tools like list_repos or list_branches. The ref scope adds precision about what is being accessed.
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 explicit usage guidance or exclusions. It only states what the tool does, not when to choose it over alternatives. With 31 sibling tools covering repos, branches, PRs, and pipelines, the description could mention that it is for reading source files rather than metadata or modifications, but no such guidance is given.
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 full burden. It does not disclose side effects, permission requirements, or what happens on success. The close_source parameter hints at merge behavior, but the tool's own behavior is opaque—for example, whether it validates branches or requires certain permissions.
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 one sentence plus a compact argument list. Every line provides useful information; no fluff. It is well-structured and easy to scan.
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 8 parameters and no annotations, the description is incomplete. It lacks usage context, prerequisites (e.g., workspace/repo must be valid), and behavioral expectations. The output schema exists so return values need not be explained, but the tool's role in the PR workflow is not contextualized.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description includes an Args list with concise explanations for each parameter, clarifying formats (e.g., comma-separated UUIDs) and defaults (e.g., dest_branch default 'main'). This adds significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Create a new pull request.' This is a specific verb plus resource, clearly distinguishing it from sibling tools like update_pull_request or merge_pull_request. The action is unambiguous and the resource is named.
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 vs alternatives. It only states the basic action; no mention of prerequisites, exclusions, or when to prefer another PR tool. The need to specify workspace and repo is implied but not explained.
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 read-only nature, authentication requirements, pagination, sorting, or potential errors. The verb 'list' implicitly suggests a read operation, but no explicit behavioral traits 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise, with one clear sentence and a brief args list. Every word adds value and the structure is front-loaded with the purpose. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and has an output schema, so return values are covered elsewhere. However, the description lacks context about the meaning of 'slug' values, whether parameters are required despite defaults, and potential edge cases. It is minimally viable but leaves room for confusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. The 'Args:' section adds meaning by defining workspace as 'Workspace slug' and repo as 'Repository slug', which clarifies what each parameter represents. However, it does not elaborate on optionality or defaults, leaving some gaps.
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 and resource: 'List branches in a repository.' This distinguishes it from sibling tools like list_repos and list_pull_requests by specifying the resource type (branches) and the scope (repository). The verb 'list' is specific and unambiguous.
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?
There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites or context. The description simply states the function without explaining when it is appropriate to call it or exclusions.
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 of behavioral disclosure. It does disclose some behavior by stating the activity log includes 'approvals, comments, updates,' but it does not mention read-only status, pagination, ordering, or any permissions. This is a modest level of transparency, enough to understand basic behavior but lacking depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with a single-sentence summary followed by a brief Args list. Every sentence contributes, and there is no wasted or redundant text.
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 output schema exists, return values are covered. However, the description lacks contextual completeness in guiding tool selection among many siblings. It doesn't explain the relationship to other PR-related tools or provide enough context for an agent to decide when this is the appropriate tool. The description is adequate for a simple read operation but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description's Args section adds necessary meaning. It clarifies that pr_id is a 'PR ID number' and that workspace/repo are 'slugs,' which is useful. However, it does not explain optionality or default behavior (e.g., empty strings for repo/workspace), leaving some gaps.
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 and resource: 'Get activity log for a pull request.' It lists examples (approvals, comments, updates) which distinguishes it from sibling tools like pr_commits or list_pr_comments. This is a specific and clear purpose.
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 does not mention any exclusions or explicitly name sibling tools for similar operations, such as pr_commits for commit history or list_pr_comments for comments. This leaves the agent to infer usage from the vague purpose.
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 says 'Get' which suggests a read operation, but it does not mention permissions, rate limits, error conditions, or that it is safe/read-only. For a tool that might have access restrictions or return varying data, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus a compact parameter list, all front-loaded with the core purpose. There is no fluff or redundant information.
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 has an output schema, return values are adequately covered by structured data. The description provides the essential purpose and parameter meanings, but lacks information about parameter defaults, optionality, or how workspace/repo interact with pr_id. For a simple read tool it is adequate, but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description lists the parameters with brief definitions (pr_id: PR ID number, workspace: Workspace slug, repo: Repository slug). This adds basic meaning beyond the schema's types and titles, but lacks depth like optionality, format, or relationships between parameters.
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 build/pipeline statuses for a pull request, with a specific verb and resource. It is distinct from sibling tools like list_pipelines, which lists pipelines generally, and other PR-related tools that handle diff, comments, or merges.
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 build/pipeline statuses for a specific pull request, but provides no explicit guidance on when to use it vs alternatives or any exclusions. Since the purpose is clear, usage is implied, but alternatives are not mentioned.
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, but it only states the action and parameters. It does not mention read-only status, authentication needs, pagination, or any other behavioral traits. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured: one sentence for purpose, followed by a tidy parameter list. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple PR commit listing tool with an output schema, the purpose and parameters are covered. However, it lacks usage context, prerequisites, and alternative tool references, making it adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters are briefly described: pr_id as a number, workspace and repo as slugs. This adds semantic value beyond the schema, which has zero descriptions. However, the explanations are minimal and do not clarify optionality, defaults, or why workspace/repo are needed.
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: 'List commits in a pull request.' The phrase 'in a pull request' distinguishes it from repository-wide commit listing (e.g., sibling list_commits), making the tool's scope immediately clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like list_commits or pr_diff. It does not mention prerequisites, exclusions, or typical use cases beyond the basic action.
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, and the description does not disclose behavioral traits beyond the basic read-only implication of 'Get'. It does not mention permissions, rate limits, or output format, leaving the burden unmet.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single purpose line and a structured Args list. Every sentence adds necessary information; no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool, the description covers what it does and the parameters. The existence of an output schema means return values are handled elsewhere. However, the lack of any behavioral or prerequisite context, combined with no annotations, leaves some gaps, though not significant for this tool's simplicity.
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 Args section provides human-readable one-line meanings for each parameter (e.g., 'PR ID number', 'Workspace slug'), which adds value over the schema that only lists types and defaults. However, it does not explain where to find these IDs/slugs or clarify that workspace/repo are optional despite defaults.
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 the specific verb 'Get' with the resource 'diffstat (files changed summary)' for a pull request, clearly distinguishing it from sibling tools like pr_diff and pr_commits. The parenthetical explanation makes the term 'diffstat' accessible.
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 a summary of file changes is needed, but it does not explicitly state when to use this tool over alternatives like pr_diff or pr_commits. No exclusion criteria or alternative tool references 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?
Annotations are absent, so the description carries the full burden for behavioral disclosure. It does not mention that triggering a pipeline is a mutating action, may cause builds to run, require specific permissions, or have other side effects. Only the basic action is stated, which is insufficient for a write 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 concise: a one-sentence summary followed by a structured parameter list. No unnecessary words or repetition, and the format is easily parseable by an agent.
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 adequately covers purpose and parameters, and an output schema exists, so return details are not needed. However, it lacks usage guidelines and behavioral transparency, making it incomplete for a mutation tool. Overall, it is a minimal but functional description.
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 Args section provides clear, meaningful descriptions for all four parameters, compensating fully for the 0% schema description coverage. It explains branch, custom_pattern (including optionality), workspace, and repo, adding value beyond the schema's bare titles and defaults.
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: 'Trigger a pipeline run for a branch.' This uses a specific verb and resource, and it distinguishes this tool from sibling pipeline tools like list_pipelines, stop_pipeline, and pipeline_steps by focusing on the trigger 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 on when to use this tool versus alternatives, nor are there any prerequisites or exclusions. The description only states the core action, leaving the agent to infer usage context from the tool name and sibling list without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It adds only 'markdown supported' as a behavioral trait, but does not mention permission requirements, side effects (e.g., comment appearing in PR activity), or any rate limits. Given the mutation nature of the tool, this is 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 concise and well-structured: a single purpose sentence followed by a clean Args list. Every line provides necessary information without waste, making it easy for an agent to quickly parse.
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 tool with 4 parameters and no annotations, the description covers purpose and parameter semantics adequately. However, it lacks explicit usage guidance, does not mention return values (though an output schema exists to cover that), and does not address any prerequisites or side effects beyond the action itself. It is adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all four parameters with brief but meaningful explanations (pr_id: PR ID number, body: Comment text (markdown supported), workspace: Workspace slug, repo: Repository slug). This adds value beyond the bare schema definitions, though the explanations are concise and not deeply detailed.
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 'Add a general comment to a pull request,' which uses a specific verb and resource. The phrase 'general comment' distinguishes it from sibling tools like inline_comment_on_pr and reply_to_pr_comment, making the tool's purpose unmistakable.
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 general PR comments ('general comment') but does not explicitly state when to use this tool versus inline_comment_on_pr or reply_to_pr_comment. No exclusions or alternative tool names are mentioned, leaving usage guidance implicit rather than explicit.
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 only states the action ('Get') and lists parameters. It does not disclose whether the operation is read-only, any error conditions, rate limits, or what happens with missing optional params. 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 extremely concise: a one-line purpose statement followed by an Args list. Every word earns its place. It is front-loaded and easy to scan.
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 has an output schema, so the description need not explain return values. However, it lacks guidance on when to use the tool and how workspace/repo relate to pipeline_uuid. For a simple read tool, it is adequate but not complete; it misses optional param details and any post-conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description's Args list adds value by explaining each parameter: pipeline_uuid, workspace slug, repo slug. It clarifies the semantic meaning (e.g., 'slug') beyond the schema titles. However, it does not mention that workspace and repo are optional or have defaults, which the schema shows.
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 'Get steps/stages of a pipeline run' with a specific verb and resource. It distinguishes from sibling tools like list_pipelines (which lists runs) and trigger_pipeline (which triggers runs).
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: you need a pipeline_uuid to get its steps. It does not explicitly state when to use this vs alternatives, nor does it mention any prerequisites or exclusions. Usage context is inferred from the tool name and the args list.
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?
Annotations are absent, so the description should disclose side effects, prerequisites, and edge cases. It only states the action 'remove' without mentioning failure modes (e.g., no existing request-changes), idempotency, permissions, or the effect on reviewers. This is a significant gap for a mutation 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?
A single, direct sentence followed by three labeled parameter lines. It is front-loaded and contains zero filler or redundant information, making it maximally concise while covering the essential action and inputs.
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 straightforward PR operation with an output schema, the description covers the core purpose and parameters. However, it lacks usage context (when to use vs. related tools), error handling, and side-effect transparency, which are needed for confident tool selection. Given the low complexity, this is a minimally adequate package.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description compensates by labeling each parameter in plain language ('PR ID number', 'Workspace slug', 'Repository slug'). This adds meaning beyond the schema's bare type and default values, though it does not specify format constraints or required/optional behavior beyond what the schema already provides.
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 ('Remove') and resource ('your request-changes from a pull request'), clearly distinguishing this from sibling tools like request_changes_on_pr. It also lists the three parameters with brief semantic hints, making the tool's intent unmistakable.
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?
No explicit guidance on when to use or when not to use the tool relative to alternatives. The phrase 'your request-changes' implies ownership, but this is not expanded into clear usage conditions or exclusion scenarios. Context from sibling PR review tools suggests pairing with request_changes_on_pr, but this is only implicit.
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. It says 'Update' but does not disclose side effects, permissions, whether changes are reversible, or what happens if no optional fields are supplied. The arg note 'reviewers: ... to set' hints at replacement behavior but lacks broader context.
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 one-sentence purpose is concise, and the Args block is structured and readable. It is slightly longer than necessary but every line adds value by clarifying parameter meaning, which the schema lacks.
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 their purpose, but omits behavioral details like return value semantics (though an output schema exists), error conditions, or effects of changing destination branch. It is adequate for a straightforward update tool but not fully comprehensive given zero annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the Args block adds meaningful descriptions for every parameter (e.g., 'pr_id: PR ID number', 'reviewers: Comma-separated reviewer UUIDs to set'). This fully compensates for the schema's lack of descriptions and clarifies optionality and format.
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 starts with a specific verb+resource: 'Update a pull request' and enumerates the updatable aspects (title, description, reviewers, destination). This clearly distinguishes it from sibling tools like create_pull_request or merge_pull_request.
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 purpose statement implies use when modifying an existing PR, but no explicit when-to-use or when-not-to-use guidance is provided. It does not reference alternatives like create_pull_request for creation, though the sibling list makes this inferable.
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 carry the behavioral burden. It does add the note that workspace 'uses default if not provided', which explains a defaulting behavior. However, it does not disclose read-only status, permissions, pagination, or potential 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?
The description is extremely concise, with a single sentence for purpose and a brief parameter note. Every word contributes value, and the structure is clean.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description sufficiently covers the main behavior and parameter semantics. It does not address potential ambiguities like what the default workspace is or how to enumerate all repos across workspaces, but these are minor for a basic list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), but the description's 'Args' section explicitly documents the workspace parameter as a 'Workspace slug' and explains the default behavior. This provides meaningful semantic information beyond the bare 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 'List repositories in a workspace' with a specific verb and object. This distinguishes it from sibling tools like get_repo (single repo) and list_branches, making its purpose unambiguous.
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 offers no guidance on when to use this tool versus alternatives such as list_workspaces or get_repo. It does not mention exclusions, prerequisites, or recommended use 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?
With no annotations provided, the description carries the full burden. The verb 'Get' implies a safe read operation, but the description does not disclose any additional behavioral traits such as required permissions, rate limits, or whether 'full details' includes nested objects like comments or reviewers. The output schema may cover return fields, but the description itself is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence followed by a tightly structured Args list. Every word earns its place, with no filler or redundancy. The main intent is front-loaded in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a simple getter tool and an output schema exists, the description is mostly complete for its purpose. It does not explain how to obtain workspace/repo slugs, but such context is likely shared across sibling tools. The output schema presumably details the return structure, so the description need not repeat it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an Args section that provides semantic meaning for all three parameters: pr_id as 'Pull request ID number', workspace as 'Workspace slug', and repo as 'Repository slug'. This compensates for the 0% schema description coverage, adding value beyond the bare property titles.
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 'Get full details of a pull request' clearly states a specific action (get details) on a specific resource (pull request). This distinguishes it from sibling tools like list_pull_requests or pr_diff, 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 this tool is used when you need comprehensive information about a single pull request, as opposed to listing multiple PRs or viewing diffs. However, there is no explicit guidance on when to use this versus alternatives, nor any exclusion criteria.
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, leaving the description to carry the full burden. It only states the action without disclosing side effects (e.g., posting a threaded reply, notifying participants), required permissions, or reversibility. 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?
The description is concise and front-loaded with the core purpose in the first sentence. The Args list is well-structured and each line provides meaningful information without redundancy, making every sentence earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the purpose and all parameters with semantic explanations. An output schema exists, so return values are handled. However, it does not mention prerequisites like the parent comment existing or potential error cases, which are minor gaps for a tool of this simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description includes an Args section that adds semantic meaning beyond the bare schema titles, such as 'parent_comment_id: ID of the comment to reply to' and 'workspace: Workspace slug.' This compensates for the 0% schema description coverage, though it could provide more detail on defaults or constraints.
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 opens with 'Reply to an existing PR comment,' which is a specific verb ('Reply') targeting a resource ('an existing PR comment'). This clearly distinguishes it from sibling tools like comment_on_pr (which likely creates a new comment) and edit_pr_comment (which edits rather than replies).
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 provides clear context by stating the exact scenario: replying to an existing PR comment. This implies when it should be used, but it does not explicitly mention alternatives or when not to use it, such as advising to use comment_on_pr for new top-level comments.
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 transparency burden. It adds the behavioral note that results are filtered by the user's access, but it does not disclose potential pagination, rate limits, or explicit read-only safety. The non-mutating nature is implied by 'List'.
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, front-loaded sentence with no redundant words. Every word contributes to the purpose, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With zero parameters and an output schema provided, the description sufficiently covers what the tool does. There is no need to explain return values because the output schema already documents them, and the tool's simplicity makes the description complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so there are no parameter semantics to document. Per the calibration, zero-parameter tools receive a baseline of 4, and the description does not need to add anything.
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 action ('List') and resource ('Bitbucket workspaces'), and adds the scope qualifier 'you have access to.' This distinguishes it from sibling list tools like list_repos and list_branches.
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 via the access qualifier, but it does not explicitly mention when to use this tool versus alternatives or provide any exclusion criteria. It is a straightforward listing tool, so the context is reasonably inferred.
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 burden. It discloses that close_source deletes the source branch and that strategy uses repo default, which is helpful. However, it doesn't mention mutating nature beyond 'merge', possible reversibility, or required permissions.
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 concise one-liner plus a structured argument list. Every line adds value with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no annotations, the description covers parameters and key behaviors. Output schema exists for return values. It lacks a note on usage context or side effects beyond close_source, so slightly incomplete for a mutating tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description fully compensates by explaining all five parameters. It adds meaningful details: strategy enumerates merge_commit, squash, fast_forward; close_source has default True; workspace/repo are slugs.
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 'Merge a pull request', with a specific verb and resource. It distinguishes from sibling tools like approve_pull_request or decline_pull_request by focusing on merging.
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?
No explicit when-to-use or alternatives are provided. The tool name and description imply it's for merging, but there's no guidance on when not to use it or comparison to related operations like update_pull_request.
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 transparency burden. It discloses the default state filter and accepted state values, which is useful. However, it does not clarify whether workspace/repo are effectively required despite empty defaults in the schema, nor mention pagination or ordering behavior. This is a minor but notable gap for a read-only listing 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 compact and front-loaded: a one-sentence summary followed by a clear Args block. Every piece of information earns its place, with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema covers return values, and the description covers the core function and parameters. However, it omits important invocation details such as whether workspace/repo are required in practice, any pagination/limits, or how the list is ordered. For a simple list tool, this is adequate but not fully complete.
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 input schema has zero descriptions and no enums, but the description fully compensates by explaining each parameter: workspace slug, repo slug, and state with its allowed values (OPEN, MERGED, DECLINED, SUPERSEDED) and default. This provides all necessary semantic meaning beyond the bare 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 opens with 'List pull requests', a specific verb+resource pairing that clearly identifies the tool's function. It also notes the default open-state behavior, which distinguishes it from single-PR tools like get_pull_request and from PR-comment tools like list_pr_comments.
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 provides clear invocation context by listing the required conceptual arguments and the default state ('Default shows open PRs'). It does not explicitly name alternative tools or state when not to use this tool, but the listing intent is unambiguous.
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 behavioral burden. It discloses that the action adds a comment and includes important nuance like 'line number (on the new/right side of the diff)' and markdown support. However, it does not mention permissions, reversibility, or potential side effects beyond the obvious mutation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a one-sentence purpose followed by a compact arg list. Every listed item adds value, and the format is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
All parameters are explained and the output schema handles return values. The tool is well-specified for a straightforward comment action. Some minor gaps exist around explicit usage comparisons to sibling tools and permission prerequisites, but these are not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides clear explanations for all six parameters, including a concrete example for file_path and a note about the line side. This fully makes up 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 opens with a specific verb and resource: 'Add an inline code review comment on a specific file and line in a PR.' It clearly distinguishes this from sibling tools like 'comment_on_pr' by emphasizing the inline, file-and-line-specific nature.
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 clearly implies when to use the tool: when you need to comment on a specific file and line in the diff. It does not explicitly name alternatives or exclusions, but the inline context is enough to differentiate it from general PR comments.
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 full burden. It clearly conveys a read-only, non-destructive action ('check', 'returns') and indicates the output type (authenticated user info). It does not detail error behavior, but for a zero-parameter auth-check tool, the description is sufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short, focused sentences. Every word earns its place, with no redundancy or filler. It front-loads the action and clearly states the return.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, an output schema that details the return format), the description is complete enough for an agent to select and invoke it correctly. It covers both the action and the expected result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is no schema information to augment. The description adds meaningful context by explaining the tool's purpose and result, meeting the baseline of 4 for parameter-less tools.
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 the specific verb 'check' and resource 'current Bitbucket auth', immediately distinguishing it from sibling tools that deal with repos, PRs, pipelines, etc. It clearly states the tool's function and output (authenticated user info).
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 for verifying authentication and obtaining user identity. It does not explicitly name alternatives, but none of the sibling tools serve a similar purpose, so the usage context is clear without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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