GitHub PR Issue Analyser

Server Quality Checklist

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

Latest release: v19.3.5
Disambiguation3/5
Several tools are unrelated to the core GitHub PR/Issue domain (e.g., choose, github_pr_issue_analyser_ui, search_prefab_components), causing confusion. Core tools are mostly distinct, but the presence of Prefab UI tools blurs the server's purpose.
Naming Consistency4/5
Most tools follow a consistent verb_noun pattern (e.g., create_issue, get_pr_diff). A few outliers like choose and github_pr_issue_analyser_ui break the pattern, but overall naming is predictable.
Tool Count3/5
With 24 tools, the count is high but not excessive. However, the scope includes many non-GitHub tools (UI builder, search components), making the set feel bloated for the stated purpose of PR/Issue analysis.
Completeness3/5
Core PR/Issue operations are present (create, read, update, comments, reviews), but missing close/delete functionality. Additionally, tools like get_repo_stars_since and get_user_activities are tangential, leaving gaps in focused analysis.
Average 3.3/5 across 20 of 24 tools scored. Lowest: 2.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 28 commits in the last 12 weeks
- Last stable release on August 12, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
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?
Annotations already indicate the tool is not read-only, not destructive, and not idempotent. The description adds no additional behavioral context beyond 'creates', such as side effects, permissions, or tag type. With annotations present, the bar is lower, but the description still fails to add value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but at the expense of essential detail. It is not verbose, but it sacrifices clarity for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 4 required parameters and an output schema, the description is severely incomplete. It does not mention what the output contains, any prerequisites, or how to construct valid inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the four parameters (repo_owner, repo_name, tag_name, message). The agent receives no help understanding what each parameter means or how to format them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Creates' and the resource 'a new tag', which distinguishes it from sibling tools like 'create_issue' or 'create_pr'. However, it lacks specificity about the type of tag (e.g., Git tag) and does not clarify the tool's purpose beyond the name itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'create_release' (which also involves tags). There are no examples, conditions, or exclusions 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 (readOnlyHint=false, destructiveHint=false) indicate a non-destructive mutation, but the description only confirms 'creates' without mentioning side effects, required permissions, or impact on existing data. No additional behavioral context is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but overly brief for a tool with 9 parameters. It lacks structure or prioritization of key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 5 required) and lack of parameter descriptions, the one-sentence description is insufficient. While an output schema exists, the description does not provide enough context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description offers no explanation of any of the 9 parameters (e.g., draft, prerelease, make_latest). With 0% schema description coverage, the description does not compensate, leaving parameter semantics entirely opaque.
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 'Creates a new release,' which is a specific verb and resource. It distinguishes from sibling tools like create_issue and create_pr, but lacks additional context such as the platform (e.g., GitHub releases).
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 on when to use this tool versus alternatives like create_tag or create_pr. No prerequisites or scenarios are mentioned, leaving the agent unaware of appropriate usage contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states 'merges' without disclosing behavioral traits such as side effects (e.g., closing the PR, updating branch), failure conditions (merge conflicts), or required permissions. Annotations provide minimal safety info (readOnlyHint false, destructiveHint false), so description should compensate but does not.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it sacrifices critical information for brevity. It is front-loaded but does not earn its place as it omits needed detail. A slightly longer description would improve utility without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 params, output schema), the description is severely incomplete. It does not mention the merge process, return value, prerequisites, or limitations. The presence of an output schema is not leveraged in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no meaning to the 6 input parameters. With 0% schema description coverage, the description should explain parameters like commit_title, commit_message, and merge_method, but it fails to do so. Parameter names are self-explanatory, but the description does not clarify usage or required vs. optional fields.
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 'Merges a specific pull request' clearly states the verb and resource, and is distinct from sibling tools (no other merge tool). However, it lacks specificity about the merge scope (e.g., into base branch) and does not differentiate from other PR action tools beyond the action itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives. Does not mention prerequisites (e.g., write access, mergeability) or scenarios where it should be avoided. Sibling tools like update_pr_branch could be confused without 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?
Description provides no behavioral details beyond what annotations already convey. No mention of authentication, rate limits, or error conditions. Annotations do provide idempotent and non-destructive hints, but the description adds nothing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, but at the cost of omitting essential usage details. A single sentence is efficient but insufficient.
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?
Description is incomplete. With 7 parameters and no param descriptions, the agent lacks context for correct usage. Output schema may help but is not described. The tool is under-specified.
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?
No parameter information provided. Schema has 0% description coverage, and the description adds no semantic meaning to the parameters, leaving the agent to infer from names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool updates an existing issue, distinguishing it from create_issue and list tools. However, it does not specify which fields can be updated, which is a minor omission.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines provided. Does not specify when to use this tool versus siblings like update_assignees or update_pr_description, nor any 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?
Annotations indicate the tool is not read-only, not destructive, and not idempotent, but the description adds no additional context beyond 'submits.' It does not explain whether submitting a second review replaces the first, whether it fails on already submitted reviews, or any side effects. The description fails to complement the annotations meaningfully.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise. However, conciseness at the expense of necessary detail is not ideal. It is appropriately front-loaded but lacks the substance needed for an effective tool definition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters (4 required) and an output schema, the description is far too sparse. It does not explain return values, parameter constraints (e.g., enum options), or how the output relates to the submission. The context provided is insufficient for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the tool description does not elaborate on any parameter. It only vaguely mentions 'for a specific pull request,' leaving the purpose of 'event,' 'body,' and required fields entirely unexplained. The description adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Submits a review for a specific pull request,' which provides a specific verb and resource. However, the tool name 'update_reviews' suggests modifying an existing review, while the description implies submission (creation). This slight mismatch prevents a perfect 5, but the purpose is still 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?
The description offers no guidance on when to use this tool versus alternatives, such as add_pr_comments or other review-related tools. No prerequisites or exclusion criteria are mentioned, leaving the agent to infer usage from 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?
Annotations indicate this is not read-only, but the description adds no behavioral context beyond the purely functional. It does not mention side effects (e.g., triggering CI, notifications), required permissions, or potential failures (e.g., merge conflicts). With minimal annotation coverage, the description should carry more weight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one sentence), which is concise but at the cost of omitting essential information. It does not front-load critical usage details, and every sentence should 'earn its place'—here, it barely does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters (6 required) and no parameter documentation, the description is incomplete. While an output schema exists, the lack of parameter guidance and usage context means the agent cannot reliably invoke this tool. The complexity of creating a pull request demands more thorough description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 7 parameters with 0% description coverage, and the tool description does not explain any parameter meaning (e.g., what 'head' and 'base' refer to, or the role of 'draft'). This leaves the agent guessing about parameter semantics.
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 is concise and directly states the tool's function: creating a pull request. It uses a specific verb ('creates') and resource ('pull request'), clearly distinguishing it from sibling tools like 'merge_pr' or 'update_pr_description'.
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 when to create an issue instead of a PR, or prerequisites like branch existence. The presence of many sibling tools makes this lack of guidance a significant gap.
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?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to repeat that. The description adds no extra behavioral details (e.g., output includes title, body, status) beyond the annotation safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and front-loads the purpose, but it is too brief for a tool with 3 parameters and no schema descriptions. It could be expanded with parameter guidance without losing 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 an output schema present, the description doesn't need to detail return values, but it fails to define what 'content/details' includes in relation to siblings. Combined with no parameter help, the completeness is poor.
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%, yet the description offers no explanation of the three required parameters (repo_owner, repo_name, pr_number). The user receives no hints on what values to provide, which is a critical 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 clearly states the verb 'fetches' and the resource 'content/details of a specific pull request'. It distinguishes from siblings like 'get_pr_diff' which fetches only diffs, though it doesn't explicitly differentiate from 'get_pr_linked_issues'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'get_pr_diff' or 'get_pr_linked_issues'. No when-not-to-use or context for selection is given.
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?
Annotations already indicate a mutation (readOnlyHint=false). The description adds no further behavioral detail, such as idempotency, duplicate handling, or side effects. It does not contradict annotations, so a baseline of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but insufficiently informative for a tool with multiple required parameters. It does not earn its place due to lack of helpful detail.
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 5 required parameters, no schema descriptions, and sibling tools that could be confused, the description is incomplete. Even though an output schema exists, the description does not mention return value or expected behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 5 required parameters with 0% description coverage. The description provides no parameter details, forcing the agent to infer from parameter names alone. At a minimum, the description should list or explain key parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'creates' and the resource 'issue', making the basic purpose obvious. However, it does not differentiate from sibling tools like 'update_issue' or 'create_pr', which would benefit from a scope qualifier.
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 on when to use this tool versus alternatives like 'update_issue' for modifications. The description lacks context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating a read operation. The description adds no additional behavioral context beyond the basic action, such as pagination behavior or rate limits, failing to leverage the opportunity to add value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no fluff. It could be more informative while remaining concise, but it is not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, many siblings), the description is insufficient. It lacks information about filtering, pagination, and how it differs from detailed sibling tools like get_pr_content, making it hard for an agent to decide without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 17% schema description coverage, the description must compensate by explaining parameters. However, it mentions none of the six parameters, leaving their meanings and defaults completely undocumented.
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 explicitly states 'Lists open pull requests or issues.' This clearly identifies the action (list) and the resource (open PRs/issues), distinguishing it from sibling tools that create, update, or merge PRs/issues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not indicate when to use this tool over alternatives like get_pr_content or get_pr_diff, nor does it mention any prerequisites or filtering capabilities.
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?
Annotations already indicate readOnlyHint=false, so the description's confirmation that this is a write operation adds little value. The description does not disclose any additional behavioral traits such as notification side effects, comment formatting constraints, or whether the operation is idempotent, which would be useful for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no fluff. However, it is too brief to fully serve the agent's needs, lacking essential context such as sibling differentiation. It is front-loaded but could be expanded slightly to include usage hints without becoming overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate for a basic 'add comment' action. However, the lack of differentiation from the inline comment sibling and the omission of parameter semantics make it incomplete for an agent to reliably select and invoke the tool without further context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should compensate by explaining parameter meanings or constraints. It does not, though the parameter names ('repo_owner', 'repo_name', 'pr_number', 'comment') are reasonably self-explanatory. Missing details like required format for the comment string or numerical range for pr_number reduce clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and object ('Adds a comment to a specific pull request'), making the tool's purpose immediately understandable. However, it does not differentiate this tool from its sibling 'add_inline_pr_comment', which could cause confusion in selecting the correct tool for adding general vs inline comments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the sibling 'add_inline_pr_comment' or any prerequisites (e.g., required permissions). This lack of context forces the agent to rely solely on the tool name to infer usage, increasing the risk of selecting the wrong tool.
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?
The description adds context about upstream changes, which is beyond the annotations (idempotentHint=true, readOnlyHint=false). However, it does not explain what happens during the update (e.g., merge vs rebase) or potential side effects like conflicts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence, but it could include more useful information without becoming overly verbose. It is missing critical details, making it less effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters and an output schema, the description is too brief. It omits details about the optional parameter, output behavior, and when to use the tool. The existence of an output schema is not referenced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any parameters (e.g., the purpose of expected_head_sha). The schema provides types and required flags but no semantic meaning.
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 ('updates'), the resource ('pull request branch'), and what it does ('with latest upstream changes'). This is specific and distinguishes it from siblings like merge_pr or create_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 given on when to use this tool versus alternatives like merge_pr or update_reviews. It does not mention prerequisites, scenarios, 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?
Description aligns with readOnlyHint annotation, but adds no extra behavioral context beyond what annotations already provide. No mention of rate limits, permissions, or branch specification.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundant information. Efficiently conveys the core functionality.
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?
Adequate for a simple fetch tool with output schema present, but misses critical detail: which branch's latest commit? Agent might assume default branch, but this is not explicit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the purpose of repo_owner or repo_name parameters. The agent receives no additional meaning 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 clearly states the tool fetches the SHA of the latest commit, with a specific verb and resource. It distinguishes from sibling tools, none of which focus on this exact operation.
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 on when to use this tool vs. alternatives like get_pr_content or get_pr_diff. No context about prerequisites or conditions.
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?
Annotations indicate idempotentHint=true and readOnlyHint=false. The description does not contradict annotations but adds minimal behavioral context (e.g., no mention of overwriting behavior or auth requirements).
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?
Single sentence, no wasted words. However, it may be too terse for a tool with four parameters and no parameter descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with four required parameters and no output schema details, the description is incomplete. It does not explain whether assignees are replaced or appended, nor does it specify scope (works for both issues and PRs directly).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no parameter-specific meaning beyond 'assignees for an issue/PR.' The four required parameters are not explained, leaving the agent to guess their purpose.
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 updates assignees for issues or pull requests, using a specific verb and resource. It distinguishes itself from sibling tools like update_issue or create_issue.
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 on when to use this tool versus alternatives (e.g., update_issue). No mention of prerequisites or context, leaving the agent to infer usage.
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?
Annotations already declare readOnlyHint=true, so the description's mention of using GraphQL API adds minimal extra context. No further behavioral details (e.g., pagination, rate limits) are provided.
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 with no extraneous information. Every word is necessary and the description is well front-loaded.
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 is simple (1 param, output schema exists, annotations provided), the description is minimally adequate but does not explain what the search returns or how it compares to similar tools. The output schema likely fills some gaps, but the description could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'username' has 0% schema description coverage, and the description only says 'by username' without adding format, constraints, or examples. This fails to compensate for the missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search', the resource 'GitHub user', and the method 'by username using GraphQL API'. This distinguishes it from sibling tools like 'get_user_activities' which may have different scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'get_user_activities' or other search tools. The description does not mention prerequisites, limitations, 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?
Annotations already indicate the tool is not read-only and not destructive; the description adds the specific behavioral detail that it creates an inline comment on a line, but does not disclose side effects like notifications or 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 single, front-loaded sentence of 15 words with no unnecessary information, earning its place efficiently.
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 description fails to explain return values or behavior for invalid inputs. For a mutable tool with 6 required parameters and no parameter descriptions, additional context is needed for proper agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description provides no additional meaning for any of the 6 parameters. While parameter names like 'line', 'path', and 'comment_body' are somewhat self-explanatory, there is no guidance on format (e.g., markdown for comment_body) or constraints (e.g., valid line numbers).
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 specifies the verb 'adds', the resource 'inline review comment', and the context 'to a specific line in a file within a PR', which distinguishes it from the sibling tool 'add_pr_comments' that likely adds general 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to comment on a specific line in a PR file, but does not explicitly state when to use this tool versus alternatives like 'add_pr_comments' for general comments, nor does it mention prerequisites 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?
Annotations (readOnlyHint=true, destructiveHint=false) already signal safety. Description adds specific output type ('diff/patch') but omits details like format or size limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb, no extraneous 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?
Simple tool with 3 clear parameters and an output schema, so description is largely sufficient. Could mention authentication or access requirements, but overall complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% with no descriptions. Parameter names are self-explanatory but description adds no further meaning 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 action ('fetches') and the resource ('diff/patch of a specific pull request'), distinguishing it from sibling tools that handle PR content, comments, or merging.
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 on when to use this tool vs alternatives like get_pr_content (for PR body) or merge_pr. Lacks context for when a diff is needed versus other PR data.
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?
Annotations already declare readOnlyHint true, and the description adds that it returns issues for auto-closing. However, it could detail whether all linked issues or only those with specific keywords are returned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence efficiently conveys the core purpose. No redundant information, every word earns 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?
Given an output schema exists, the description adequately covers what is returned. It could mention prerequisites like PR existence or linking keywords, but overall sufficient for a retrieval 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?
With 0% schema description coverage, the description does not explain parameters at all. The parameter names are self-explanatory, but no additional semantics are provided.
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?
Description clearly states the tool returns issues auto-closed on PR merge, with a specific verb and resource. It distinguishes from sibling tools like get_pr_content or get_pr_diff by targeting linked issues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like list_open_issues_prs or get_pr_diff. The description only states what it does, not the context for use.
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?
Annotations provide readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds 'Updates' which is consistent, but does not disclose additional behavioral traits beyond what annotations already indicate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core purpose with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has five parameters and many sibling tools, the description lacks contextual completeness; it does not mention prerequisites or clarify partial update behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description partially compensates by mentioning 'title' and 'description' corresponding to new_title and new_description, but does not explain the repo_owner, repo_name, and pr_number 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 it updates the title and description of a specific pull request, using a specific verb and resource, and distinguishes from sibling tools like merge_pr or add_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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided; there is no mention of when to use this tool versus alternatives among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations mark the tool as read-only. The description goes far beyond by detailing pagination limits (50 per page, max pages), truncation detection, and the effect on the 'overall' field (downgraded to 'unknown' on partial results). This is rich behavioral context beyond what annotations provide.
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 paragraph that starts with the main action, then efficiently explains pagination behavior and truncation handling. Every sentence adds necessary detail without fluff.
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 algorithm well, but lacks parameter descriptions. With 3 simple required params and an output schema, the completeness is adequate but not thorough. The missing param documentation reduces the score.
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 has 3 parameters with 0% description coverage. The description does not describe repo_owner, repo_name, or pr_number individually. Although their meaning is somewhat inferable, for full clarity the description should provide at least brief explanations.
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 precisely states it returns CI check runs and commit status for a pull request's HEAD commit. This clearly differentiates it from sibling tools like get_pr_diff or create_pr, which have 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 when to use the tool (to get CI status), but lacks explicit guidance on when not to use it or alternatives. Among siblings, no other tool provides status checks, so differentiation is less critical, but still no usage context.
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?
Despite no annotations, the description details the UI card, button clicking, and the resulting 'I selected:' message format. It also mandates stopping after calling. It does not cover edge cases like option limits but is transparent for the main behavior.
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 front-loaded with purpose and is appropriately sized. It includes necessary usage details without excessive verbosity, though minor redundancy could be trimmed.
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 simple nature of the tool and lack of output schema or annotations, the description is complete. It covers input, behavior, user interaction, and the required post-call waiting instruction.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter. The description adds minimal semantic value beyond what the schema provides, maintaining the baseline score of 3.
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 'Present the user with a set of options to choose from' and explains the interactive card with buttons. It distinguishes itself from sibling GitHub PR/issue tools by being a UI decision tool.
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?
Explicitly says when to use: 'when you need the user to make a decision between discrete alternatives' and instructs to call it proactively. Includes critical instruction to stop and wait. Does not explicitly list when not to use, but context is sufficient.
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?
Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds crucial behavioral context: 'One REST call is made per repo checked — set max_repos conservatively', which discloses potential cost. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no redundancy. Each sentence serves a distinct purpose: purpose, input format and examples, and performance warning. Efficient and well-structured.
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 moderate complexity, the presence of an output schema, and annotations covering safety, the description provides sufficient context including date format, defaults, and a performance consideration. No notable gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It explains the 'since' parameter format and default, and implies the role of 'max_repos'. However, it does not explicitly detail 'username', 'top_n', or provide type info 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 clearly states the verb 'Return' and the resource 'repos owned by username' with a specific action 'received the most new stars since a given date'. This distinguishes it from sibling tools which focus on issues, PRs, releases, etc.
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 explicitly says 'Answers prompts like "which repos gained the most stars in the last 30 days"' and warns about the number of REST calls per repo. This provides clear usage context, though it does not mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description explains query matching (OR-matched), automatic detail modes based on result count, and the detail parameter override. It does not mention read-only nature explicitly but implies it. The behavior is well-covered.
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 front-loaded with purpose and usage, followed by parameter details. It is clear and well-structured, though the parameter descriptions are somewhat repetitive of the schema. Still, no unnecessary information.
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 complexity (4 parameters, output schema provided), the description covers purpose, usage context, parameter behavior, and output modes thoroughly. The output schema exists, so return format details are not needed. The description is complete for an API search tool.
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 coverage is 75%, and the description adds meaningful context for query, detail, and limit beyond the schema. The `components` parameter lacks description in both schema and description, but the description compensates for the other three with usage details like OR-matching and automatic mode.
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 it searches the Prefab component library to look up API details, distinguishing it from sibling tools which are unrelated (GitHub operations). The verb 'search' and resource 'component library' are specific and precise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly advises using this tool before writing component code to find argument names and values, and contrasts it with a separate skill for patterns and layout. However, it does not name the alternative tool or explicitly state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that repo_stars returns cumulative counts, not per-period deltas, which is critical behavioral information beyond annotations. No contradictions with readOnlyHint.
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?
Two concise sentences with front-loaded purpose. Every sentence adds value: purpose and a behavioral caveat. No waste.
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 output schema exists, description need not detail return values. Covers filtering, date formats, and star delta caveat. Missing description for username and max_results, but overall adequate.
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 coverage, description explains org, repo, since/until (including accepted date formats). However, username (required) and max_results are not described, 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?
Clearly states 'Get user activities' with optional filtering by org, repo, and date range. Verb and resource are specific. Distinguishes from siblings like get_repo_stars_since by focusing on activities broadly.
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?
Provides usage context: when to use filters and date formats. Lacks explicit guidance on when not to use this tool vs alternatives, though the repo_stars caveat helps avoid misuse.
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?
No annotations exist, but the description details sandboxed execution, streaming via PrefabApp, variable injection via data, and layout behavior. It lacks mention of error handling or limits, but is otherwise transparent.
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 long but well-structured with headings, code blocks, and bullet-style layout patterns. It could be more concise, but the structure aids readability.
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 complexity (UI generation, reactive state, charts) and lack of output schema, the description covers essential usage patterns, layout constraints, and examples. It is sufficiently complete for an AI agent to use effectively.
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 has only 0% description coverage, so the description must compensate. It thoroughly explains both params: code (Python building component tree) and data (injected variables), with multiple examples and syntax details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Execute Prefab Python code in a sandbox and render the result.' This is a specific verb+resource pair that distinguishes it from sibling tools which are all GitHub operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Extensive guidance is provided: when to use (to create UI), how to structure code using PrefabApp, import components, use reactive bindings, and layout patterns. It also directs users to the `components` tool for component lookups.
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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