ContextBridge

by Vatsal212005

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

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

Latest release: v0.9.1
Disambiguation4/5
Tools separate cleanly into read-only GitHub queries, mutation requests, approval actions, and telemetry. A few telemetry tools (get_audit_summary vs get_evaluation_summary) could be confused, but descriptions clarify their distinct sources. No two tools appear to do the same operation.
Naming Consistency4/5
Most tools follow verb_noun snake_case (list_repositories, create_issue, get_workflow_runs). Two exceptions: server_info and health lack verbs, and github_connection_status is a noun phrase. Consistency is strong overall but not perfect.
Tool Count3/5
27 tools is above the comfortable range. The count is inflated by four telemetry tools that could arguably be combined. However, the server covers multiple subdomains (GitHub reads, mutation requests, approval execution, system health), so the count is defensible albeit heavy.
Completeness3/5
Read-only GitHub coverage is broad (repos, issues, PRs, commits, code, workflows, file contents). Mutation coverage is limited to issues (create, comment, label, close, reopen) with no PR mutations or issue editing. The human-approval workflow is well-defined, but the lack of broader write operations creates noticeable gaps for a GitHub-oriented server.
Average 3.7/5 across 27 of 27 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only reveals that DRY_RUN simulates without contacting GitHub. It does not state that normal execution will modify GitHub, what the side effects are, whether authentication is required, or what the output represents. This is insufficient for a high-risk execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that communicates the core purpose and a key behavior. There is no unnecessary elaboration; every word contributes value. It is well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the presence of an output schema, the description is incomplete for an execution tool. It does not explain the action lifecycle, prerequisites (e.g., action must be pending), or the meaning of normal execution. The DRY_RUN mention without a corresponding parameter undermines completeness. For a tool that likely modifies GitHub, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter, action_id, with 0% description coverage. The description fails to explain action_id or how to obtain it. Worse, it introduces 'DRY_RUN' as a behavior but the schema has no such parameter, creating ambiguity. The description does not compensate for the missing schema documentation and actually adds confusion.
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: it executes exactly one human-approved action. The verb 'execute' and resource 'human-approved action' are specific, and the tool name aligns with this purpose. It distinguishes itself from read-only tool siblings by implying a mutating action, which is evident from context.
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 is provided on when to use this tool versus alternatives. It does not mention that pending actions can be listed via list_pending_actions or that get_pending_action provides details. The only hint is the DRY_RUN mode, which is a simulation behavior, but not a clear 'when to use' directive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the read-only nature and the UTF-8 constraint, which are useful. However, it omits details about max_chars truncation, behavior for binary files, error handling, or what 'accessible' means in terms of 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, concise sentence that front-loads the core purpose without wasted words. It is appropriately small and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the tool's complexity (dual file/directory behavior, optional ref, max_chars limit) is not addressed. One line is insufficient for a 5-parameter tool, and key behaviors and parameters remain undocumented.
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 five parameters with 0% description coverage. The tool description does not explain the meaning of owner, repo, ref, max_chars, or how path selects between file and directory listing. It adds no value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads UTF-8 text files or lists directory contents in a GitHub repository, using specific verbs and a clear resource. It is easily distinguishable from sibling tools like search_code, get_repository, and list_repositories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, such as whether to prefer search_code for code search or get_repository for metadata. The phrase 'in an accessible GitHub repository' hints at prerequisites but provides no explicit exclusions or 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?
The description explicitly states 'Read-only,' which is a key behavioral trait, and mentions the authenticated token scope. Since no annotations are provided, this adds useful context. However, it omits other potential behavioral details like default ordering or pagination, which may be partially covered by the output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two sentences, front-loaded with the core action and scope, with no filler words. Every sentence earns its place, making it highly concise and well-structured.
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 read-only list tool with an output schema, the description covers safety and authentication scope but lacks usage guidelines and any parameter explanations. Given the absence of annotations and 0% parameter coverage, the description is not fully complete for an agent to confidently select and invoke the tool across likely scenarios.
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 does not mention any of the four parameters (sort, direction, visibility, max_results). With 0% schema description coverage, the description completely fails to compensate or add semantic meaning to these parameters, leaving the agent to rely solely on parameter names and enums.
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 uses the verb 'List' with the resource 'repositories' and specifies the scope as 'accessible to the authenticated GitHub token.' This distinguishes it from sibling tools like get_repository, which targets a single repository. The purpose is specific and non-tautological.
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_repository. The phrase 'List repositories' implies a broad enumeration, but there is no explicit statement of when to use it, what scenarios it suits, or any 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?
No annotations are present, so the description carries the burden. It mentions 'immutable' and 'local', implying a non-destructive read, but does not disclose permissions, side effects, or the meaning of 'summarize'. This is minimal but not entirely absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no unnecessary words. It front-loads the core function and is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema and simple optional parameters, the description provides adequate coverage of the tool's purpose but does not explain the parameter effects or the relevance of 'immutable local'. It is sufficient for a simple read tool but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention 'hours', 'all_time', or 'recent_limit'. It fails to explain how these parameters affect the summary or result, offering no compensation for the lack of 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 uses a specific verb ('summarize') and resource ('immutable local audit stream'), clarifying that it returns recent events. This effectively distinguishes it from sibling tools like get_evaluation_summary or get_recent_tool_calls.
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_recent_tool_calls or get_evaluation_summary. The description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states 'Read-only' and 'Requires Actions: read', conveying that this operation has no side effects and needs a specific permission. This adds valuable safety context beyond a bare 'List' statement, though it omits details like pagination or result ordering.
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: two short sentences totaling 14 words. The core action is front-loaded in the first sentence, and the permission/read-only notes are valuable additions. 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with seven parameters, the description remains minimal. It covers the core list operation but ignores the five optional filter parameters (actor, event, branch, status, max_results). With no annotations and 0% schema coverage, the agent lacks essential input semantics. The presence of an output schema helps with returns but does not compensate for the missing input guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, leaving all seven parameters (owner, repo, actor, event, branch, status, max_results) without semantic explanation in the schema. The description also fails to elaborate on any of these parameters, so the agent cannot infer their meaning or usage beyond their names and types. No compensation for the schema gap is 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?
The description clearly states the tool's function: 'List GitHub Actions workflow runs for a repository.' It uses a specific verb ('List') and a distinct resource ('GitHub Actions workflow runs') with a clear scope ('for a repository'). This distinguishes it from sibling list tools like list_repositories and list_commits.
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 relative to alternatives. It mentions a permission requirement ('Requires Actions: read') and read-only nature, but does not explain contexts in which this tool is preferred over other list tools, nor does it mention any exclusions or alternative tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It explicitly states 'Read-only', which informs the agent that the tool will not mutate data. This is a valuable behavioral trait. However, it does not disclose other potential traits like pagination or rate limits, though these are partially covered by the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence that clearly states the purpose and a brief note on safety. It is front-loaded and every word earns its place. It avoids unnecessary verbosity while still conveying the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 8 parameters, 3 enums, and no annotations, yet the description provides only the most basic purpose. It does not explain filtering options, default behaviors, or when to use which parameters. With an output schema present, return values are known, but the overall usage context is insufficient for a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, and the description adds no parameter semantics. It does not explain what base, head, sort, state, direction, or max_results do, nor does it clarify owner and repo beyond the schema's own titles. The description fails to compensate for the lack of 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 tool lists pull requests for a GitHub repository, with a specific verb and resource. It distinguishes from the sibling tool get_pull_request by indicating a list operation rather than a single item fetch. The addition of 'Read-only' further clarifies 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 like get_pull_request. It does not mention filters or scenarios that would select this tool, nor does it give any exclusions. No explicit usage context is provided beyond the basic listing purpose.
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 of behavior. 'Read-only' is a useful safety hint, but it does not disclose what happens on missing issue, rate limits, or authentication needs. It adds some context beyond the name, but not full 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?
Single sentence, 8 words, front-loaded with the action and resource. No filler or redundant material.
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?
Output schema exists to cover return values, and description covers purpose and read-only nature. However, it lacks usage guidance, edge-case behavior, and any notes on when not to use it. For a simple getter it's adequate but minimal.
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 description must compensate. It mentions 'repository and number' but does not elaborate on owner vs repo, or the exact meaning of issue_number. Parameter names are somewhat self-explanatory, but the description adds minimal value beyond the schema structure.
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 'Get one GitHub issue by repository and number', which is a specific verb and resource that distinguishes it from siblings like search_issues (search) or get_repository (repo). The read-only nature is also mentioned.
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 vs alternatives like search_issues or get_pull_request. The description implies you need a repo and issue number, but does not state exclusions or provide context for choosing this tool over others.
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?
The description discloses important behavioral traits: arguments are redacted (privacy/security) and metadata includes timing/error details. Since no annotations are provided, this information adds value beyond the tool name and helps set expectations about output content.
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 starts with the action verb and efficiently communicates the tool's purpose. There is no redundancy or extraneous detail, making it easy to 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?
The description gives a solid overview of the tool's function and output, and an output schema is present. However, given the absence of annotations and parameter descriptions, the description is not fully complete for effective invocation, especially regarding the filter parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the tool description must explain the parameters. It does not mention limit, status, or tool_name at all; it only describes the output. The description fails to convey what these filters do, leaving the agent without essential usage 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 clearly states the verb 'Return' and the resource 'recent local MCP tool executions', specifying exactly what is included (redacted arguments, timing/error metadata). This effectively distinguishes it from sibling tools like get_tool_metrics which focus on aggregates rather than individual executions.
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, and does not mention any exclusions or specific use cases. Without any contextual cue, an agent may not know whether to choose this tool over get_audit_summary or get_tool_metrics for a given query.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It conveys that the tool is a read-only operation returning metrics, but does not disclose potential behaviors like required permissions, data aggregation details, or any side effects. For a simple telemetry read tool, this is minimally adequate but lacks 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 a single, well-structured sentence that front-loads the action and specifies key details without wasteful words. Every word contributes meaning.
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 relatively simple and has an output schema, so return value details are not required. However, the lack of parameter semantics and usage differentiation makes the description incomplete for an agent to fully understand when and how to use it.
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 does not explain the 'hours' or 'all_time' parameters. The agent must rely on parameter names and defaults to infer meaning, which is a significant gap for correct invocation.
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 ('Return') and resource ('tool-call success, failure, latency, and per-tool metrics'). It also specifies the source ('local telemetry'), making it distinct from sibling tools like get_recent_tool_calls or get_audit_summary.
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 get_recent_tool_calls or get_audit_summary. The description does not mention any exclusions or preferred contexts, leaving the agent to infer from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions 'lightweight' and 'health check' but does not describe the output format, safety guarantees (e.g., read-only), latency characteristics, or any potential side effects. The read-only nature is implied but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action 'Return' and clearly specifies the object. Every word contributes to clarity, with no wasted 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 tool's simplicity and existence of an output schema, the description is adequate but minimal. It does not explain when to call this tool or what 'healthy' means, and it lacks behavioral context such as safety or typical use cases. However, the output schema likely covers return values, and the tool is straightforward.
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 the schema already covers everything. The description adds no parameter information, but none is needed. Baseline for zero-parameter tools is 4, and this description satisfies that.
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 returns a lightweight health check for the ContextBridge process, using a specific verb and resource. It distinguishes itself from sibling tools like server_info and github_connection_status by focusing on process health rather than server details or connection status.
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 server_info or github_connection_status. The description implies it is for checking process health, but it lacks explicit context, exclusions, or alternative recommendations.
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 reveal a key trait: the action is queued rather than executed immediately, and is subject to human approval. However, it omits other potentially important details such as required permissions, side effects, or what happens after approval, leaving a moderate 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core purpose and immediately notes the approval-queue behavior. Every word earns its place, with no unnecessary detail or repetition.
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 tool's main purpose and its most distinctive behavior (queuing for approval), and an output schema exists to document return values. However, given that parameter descriptions are entirely absent and usage guidance is only implicit, the description leaves some gaps for an agent to fully invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any parameters. The parameter names (owner, repo, issue_number, body) are self-explanatory, but the tool description adds no explicit meaning or usage guidance, so it fails to compensate for the lack of 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 tool 'Request an issue comment', which is a specific verb+resource combination. It also distinguishes itself from siblings like create_issue or add_labels by noting it 'queues exact action for human approval', indicating a different execution model.
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 should be used when a comment needs to be queued for human approval, but it does not explicitly mention alternatives or when not to use it. The context is clear enough for basic selection, but no direct exclusions or sibling comparisons are 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?
With no annotations, the description carries the burden of behavioral disclosure. It states 'Read-only,' which is a key behavioral trait for an AI agent. However, it does not describe potential errors, authentication requirements, or what happens with an invalid run_id, leaving some transparency gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences, front-loaded with the core action ('Return...') and immediately clarifies read-only status. Every word contributes value, with no redundancy or 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?
Given the tool's low complexity (one optional parameter) and the presence of an output schema, the description is mostly complete. It covers the primary behavior and safety profile, though it could briefly clarify what 'local' means or mention the optional run_id in the description itself for standalone completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides only a parameter name 'run_id' with no description. The description adds meaning by indicating the tool returns the 'latest' summary by default or a 'specified' one via run_id. This helps clarify the optional parameter's purpose, but it is not detailed enough to fully compensate for the 0% schema description coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'the latest or specified local tool-selection evaluation summary,' which specifies both the verb ('return') and the resource. However, it does not explicitly differentiate from sibling tools like get_tool_metrics or get_audit_summary, though the resource itself is distinct.
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 through the 'latest or specified' phrasing, suggesting the tool is for retrieving evaluation summaries with an optional run_id. There is no explicit guidance on when to use this tool versus alternatives or any exclusions, leaving some ambiguity.
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 are present, so the description must disclose behavior itself. It explicitly states 'Read-only', which is a valuable safety trait for an agent selecting the tool. For a simple metadata read, this covers the main behavioral concern, though it omits auth or rate-limit details.
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 short clauses totaling seven words. Every word earns its place; no filler, redundancy, or required context is buried.
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 an output schema exists, so return details need not be in the description. However, missing usage guidance and parameter elaboration create gaps; it is minimally viable but not thoroughly 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 has no descriptions (0% coverage) and the tool description does not explain owner/repo formats or validation. Although the parameter names are intuitive, the description fails to compensate for the complete lack of schema-level documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states verb 'Get' and resource 'metadata for one GitHub repository', clearly distinguishing from sibling list_repositories which would fetch multiple. It's 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?
No direct when-to-use or when-not-to-use guidance. The word 'one' implies a single repository but no alternative is named (e.g., use list_repositories for all repos), leaving the decision partly implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the key behavioral trait of queuing for human approval, which signals that no immediate action occurs. However, it does not reveal other traits such as what happens after approval, how to track the pending action, or any auth requirements, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the action and queueing behavior. There is no fluff, and every word contributes to the intended meaning.
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 the output schema covers return values. However, the description omits integration guidance with the approval workflow, such as referencing sibling tools like list_pending_actions or execute_approved_action. It is complete enough for basic invocation but lacks contextual depth for navigating the full process.
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 adds no meaning to the three parameters (owner, repo, issue_number). While the parameter names are self-explanatory, the description does not compensate for the lack of schema descriptions, making this a low score per the rubric.
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: 'Request reopening of an issue' and differentiates it from sibling tools like close_issue by adding that it 'queues exact action for human approval.' This is a specific verb+resource with a unique behavioral distinction.
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: to request reopening of an issue, and it queues for human approval. However, it does not explicitly state when not to use it or mention alternatives like execute_approved_action or close_issue. The context is clear but lacks explicit exclusions or comparative guidance.
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 carries the full burden and discloses two key behavioral traits: read-only operation and subjection to GitHub code-search limits. This adds value beyond the schema, though it omits details like rate-limit specifics or result shape.
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 sentences, front-loaded with the core purpose and followed by a key constraint. 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.
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 (7 parameters) and lack of annotations, the description is too sparse to be complete. It does not cover query syntax, filter combinations, expected result behavior, or error scenarios. Although an output schema exists, the description alone leaves critical gaps for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description provides no parameter-level semantics. Parameter names are self-explanatory, but the description does not explain how query, repo, owner, path, language, extension, or max_results interact, leaving significant ambiguity for a 7-parameter tool.
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 ('Search') and resource ('code') and adds scope ('visible to the authenticated GitHub token'). This clearly distinguishes it from sibling tools like search_issues and list_repositories.
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 (searching code) but does not explicitly state when to use this tool versus alternatives or provide exclusions. The token-visibility scope offers some situational context, but no direct guidance.
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 are present, so the description carries the burden. 'Read-only' is explicitly stated, which is a valuable behavioral trait for the agent. However, it does not disclose rate limits or other quirks, though the output schema likely covers return structure, making a 4 appropriate.
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 short sentence with no filler. It is front-loaded with the core purpose and the read-only note, making it maximally concise and well-structured.
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-resource getter, the description is mostly adequate, especially with an output schema present. However, it lacks usage guidance and parameter semantics, leaving the agent to infer those from the tool name and sibling context. It is complete enough to use correctly but has clear gaps.
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 does not compensate by explaining the parameters. While the parameter names are self-explanatory, the description adds no meaning beyond the schema. Given the low coverage, the description should have provided some parameter context but does not.
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 detailed metadata for one GitHub pull request' clearly states the action and resource. It distinguishes from sibling list_pull_requests by specifying 'one' pull request and 'detailed metadata', so the purpose is unambiguous.
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 fetching a single PR's metadata but provides no explicit when-to-use guidance or alternatives. It does not mention when not to use or contrast with list_pull_requests or other similar tools, so the guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the action is destructive and requires human approval, which is important behavioral context. However, it does not explain whether this creates a pending action or how the approval process works, which would be richer transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the essential purpose and a key behavioral constraint. Every word earns its place, with no redundant information.
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 there are 3 straightforward parameters and an output schema exists, the description is mostly complete. It covers the core action and approval requirement, but does not detail the approval workflow or prerequisites (e.g., issue must be open). For a tool with no annotations, this is a minor gap.
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 does not compensate. It does not explain what 'owner', 'repo', or 'issue_number' mean, though 'closure of an issue' implies issue_number identifies the issue. The parameter semantics are largely left to the schema, which only provides names and types.
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: to request closure of an issue. It explicitly uses the verb 'request' and the resource 'issue', distinguishing it from sibling tools like reopen_issue and create_issue. The addition of 'destructive action' also signals the nature of the operation.
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 an issue needs to be closed, but it does not explicitly state when to use this tool versus alternatives such as reopen_issue or direct issue updates. No exclusions or alternative tool references are provided, though the approval requirement hints at a specific workflow.
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 explicitly says 'Read-only,' which is a useful behavioral disclosure, but it does not mention default result limits, result ordering, pagination, time format expectations, or authentication requirements.
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 and adds the key 'Read-only' trait. Every word earns its place with no 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?
The tool has 8 parameters and an output schema, but no annotations. The description covers the basic list-and-filter behavior and read-only safety, yet it omits important operational details such as default max_results, date/time handling, and whether results are sorted. It is minimally viable but not fully complete for a complex tool.
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 must compensate. It lists the general filter categories (branch, path, author, time), which maps to some parameters, but it does not explain the concrete semantics of parameters like max_results, since/until format, branch_or_sha, or the required owner/repo.
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 lists commits in a repository and specifies the filtering dimensions (branch, path, author, time). This distinguishes it from sibling tools like list_repositories, get_repository, and get_commit_status.
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 provides clear context for when to use the tool: to list commits with optional filters. However, it does not explicitly state when not to use it or mention alternative tools, so it falls short of a full 5.
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 carries the burden and explicitly states 'Read-only' and 'safe structured filters', which disclose the non-destructive nature. It also notes 'accessible repositories', clarifying scope. This covers the primary behavioral traits for a search 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 extremely concise: a single sentence that front-loads the core purpose and safety trait. 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.
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 is too minimal for a tool with 8 parameters and no annotations. It lacks guidance on parameter relationships (e.g., repo/owner interplay), max_results effects, or how 'accessible repositories' are determined. The agent may need extra probing to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for parameter meaning. It only mentions 'safe structured filters' without enumerating any of the 8 parameters (repo, owner, query, state, author, labels, assignee, max_results). This leaves the agent to infer filter semantics from param names alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action (search), the resource (GitHub issues), and the scope (across accessible repositories). It distinguishes itself from sibling tools like search_code or get_issue by explicitly targeting issues.
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: it searches issues across accessible repositories using filters. It does not explicitly state exclusions or alternatives, but the resource focus is strong enough to guide selection.
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 full transparency burden. It discloses the read-only nature implicitly by stating it 'checks' and 'returns', but does not explicitly mention that it has no side effects or what happens if authentication fails. The return content is clearly described.
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 wasted words. It directly states what the tool does and what it returns, making it efficient and easy to parse.
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 parameterless status-check tool with an output schema, the description is sufficiently complete. It explains the primary purpose and return content, though it does not address error cases or authentication failure behavior. The output schema likely covers return structure, so this is 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?
The tool has zero parameters, so schema coverage is trivially 100%. The description adds meaning beyond the schema by clarifying the purpose and output (account and rate-limit state), which is useful for an agent despite no parameters needing explanation.
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 ('Check'), names the resource ('GitHub authentication'), and states the return value ('connected account plus rate-limit state'). It clearly distinguishes from siblings like 'health' and 'server_info' by focusing on authentication status.
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 (when needing auth/rate-limit status) but does not explicitly mention alternatives or exclusion conditions. There is no guidance on when NOT to use it or how it differs from similar tools like 'health'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses a key limitation: the tool cannot approve or reject actions, which indicates read-only behavior. However, it does not mention pagination, status filtering specifics, or authentication requirements, leaving some behavioral aspects undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences. The first sentence front-loads the core purpose, and the second adds a critical constraint without any filler 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?
The tool is simple and an output schema exists, so return values need not be described. However, the description omits any explanation of the optional parameters, which is a notable gap given zero schema coverage. The basic purpose and a key limitation are clear, but parameter semantics are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description makes no mention of the 'limit' or 'status' parameters. The agent is left to infer meaning solely from parameter names and defaults, which is insufficient for precise invocation.
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 'List' and names the resource 'human-confirmation actions,' clearly identifying this as a read-only enumeration tool. The second sentence distinguishes it from approval/rejection tools by stating it cannot do those, which differentiates it from siblings like execute_approved_action.
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?
The description explicitly states 'This tool cannot approve or reject them,' which is a clear when-not guideline. It implies that listing is the intended use, and that approval/rejection must be done elsewhere, making the usage context 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?
No annotations are provided, so the description carries full behavioral burden. It discloses that the tool returns information, which implies a non-mutating read operation, but it does not explicitly state there are no side effects or detail any permissions or error cases. For a simple informational tool, this is adequate but 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 that is direct and free of filler. It states exactly what the tool does without unnecessary detail, making it easy to parse quickly.
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, no parameters, and the presence of an output schema (which covers return values), the description is nearly complete. It could explicitly mention that no inputs are required and it is a read-only operation, but the overall context is sufficient.
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 takes no parameters, so the schema has 100% coverage by default. Per rubric, a baseline of 4 applies when there are zero parameters, and the description adds no conflicting or redundant 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 uses a specific verb 'Return' and identifies the resource as 'identity and runtime information' for the ContextBridge server. This clearly distinguishes it from sibling tools like 'health' and 'github_connection_status', 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 the tool is used to obtain server identity and runtime details, but it does not explicitly state when to choose this over 'health' or 'github_connection_status'. No alternatives or exclusions are mentioned, so usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states that the action is not executed immediately but rather queued for human approval, which is a critical behavior. However, it does not mention potential failure modes, idempotency, or how to track the queued request, leaving some gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise—two short sentences—with the key information front-loaded. Every phrase adds value: 'Request creation' is the action, 'GitHub issue' is the resource, and 'queues exact action for human approval' explains the critical behavioral nuance.
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 presence of an output schema and sibling tools for pending actions, the description focuses on the most important contextual detail: this tool queues for approval rather than executing directly. It does not elaborate on parameter requirements, but the schema covers required fields, and the output schema likely describes return values. The queueing behavior is the key missing piece that the description supplies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate for parameter meaning, but it does not mention any parameters. The property names (owner, repo, title, body) are self-explanatory, but the description adds no additional context about required vs optional parameters, formats, or validation rules.
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 'Request creation' and the resource 'GitHub issue', and distinguishes this tool from siblings like add_issue_comment and close_issue by focusing specifically on creating a new issue. The phrase 'queues exact action for human approval' further differentiates it from any direct-creation alternative.
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 when to use the tool: when you want to create an issue but need human approval, as it queues the action. It does not explicitly name alternatives or state when not to use it, but the approval context is clear from the wording and sibling tool names like list_pending_actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It discloses an authentication requirement ('Requires Commit statuses: read') and the legacy/combined nature of the data, which are useful behavioral traits. It does not describe rate limits or error behavior, but the read-only nature is clear from 'Get' and the permission.
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, well-structured sentence that front-loads the verb and resource, then adds the permission requirement. 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 3-parameter read tool with an output schema, the description covers the operation, acceptable ref values, and required permission. It could mention a non-mutating guarantee explicitly, but 'Get' and the read permission make that sufficiently clear.
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 clarification that ref accepts 'a SHA, branch, or tag' adds real value beyond schema property names. Owner and repo are standard and self-explanatory from their names, so the partial compensation is adequate.
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 opens with action verb 'Get,' identifies specific resource ('combined legacy commit-status contexts'), and scopes inputs to SHA/branch/tag. This clearly differentiates from siblings like list_commits or get_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 description implies the tool's use case—retrieving combined commit statuses for a ref—and notes the required permission. It does not explicitly state when to prefer it over alternative tools or mention exclusions, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral transparency burden. It explicitly states 'without changing its state', clearly disclosing the read-only nature of the tool. It also adds context about 'pending/decided action' statuses, but does not cover edge cases like not-found behavior or permission requirements. Overall, the key non-mutating trait is communicated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that is front-loaded with the action ('Inspect'). It contains no filler and every word adds value, making it appropriately concise for a simple getter tool.
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 simplicity of the tool (one parameter, output schema present), the description adequately covers its purpose and behavior. It positions the tool among siblings, though it could mention not-found behavior or state handling. The existing output schema mitigates the need to explain return values, so overall completeness is high.
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 schema has one required parameter, action_id, with zero description coverage. The description's 'by ID' clarifies the parameter's role and adds domain context ('pending/decided action'). Although it does not specify format or examples, the single parameter is intuitive and the description compensates for the lack of schema-level descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Inspect one pending/decided action by ID'. It uses a specific verb ('inspect'), specifies the resource ('pending/decided action'), and the scope ('by ID'), which distinguishes it from listing all actions (list_pending_actions) or executing an action (execute_approved_action).
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 when to use this tool (to view a single action without modifying it) and distinguishes it from actions that change state (like execute_approved_action). However, it does not explicitly name alternative tools or state scenarios where it should be avoided, leaving some room for inference.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description transparently reveals the critical behavior: the tool does not directly add labels but creates a request ('Request existing labels be added') and queues it for human approval. This corrects the potential false assumption from the tool name and is essential for proper use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the verb and resource, then immediately clarifies the approval queue aspect. Every word earns its place, with no redundancy or extraneous detail.
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?
The tool is relatively straightforward with 4 required parameters and an output schema present. The description covers the essential action, the key constraint (existing labels), and the approval-queue behavior. These details are sufficient for an agent to correctly select and invoke the tool, and since an output schema exists, return-value documentation is not necessary.
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 needs to compensate. It adds meaningful semantics for the 'labels' parameter by requiring 'existing labels' (i.e., not creating new ones) and references the 'issue' which maps to issue_number. However, it does not address the owner/repo parameters specifically, leaving some semantic burden on the agent's familiarity with GitHub APIs. Overall, partial compensation.
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 'Request' and clearly identifies the resource: 'existing labels be added to an issue'. It also explicitly distinguishes the tool from direct mutation by noting it 'queues exact action for human approval,' which sets it apart from siblings like 'add_issue_comment' 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys when to use this tool: when you want labels added to an issue. The phrase 'queues exact action for human approval' clearly implies that this tool is for requesting rather than directly executing, which indirectly tells the agent not to use it if immediate application is required. However, no explicit alternatives or exclusion conditions are stated.
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 are provided, so the description carries the full burden. It explicitly discloses that the tool does not change anything, signaling a safe read-only operation. This covers the key safety concern, though it does not mention other potential details like authentication requirements.
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 that is front-loaded with the action and resource, containing no filler words or redundant information. It is exceptionally efficient.
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 no parameters and an output schema present, the description fully covers the tool's behavior. The only relevant contextual detail for an inspection tool—that it is non-mutating—is explicitly stated, making 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 tool has zero parameters, so the baseline score is 4. The description adds no parameter-specific information because none exist, and no compensation is needed given the empty 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 uses the specific verb 'Inspect' and names the resources 'mutation gates and human-confirmation requirements,' making the tool's scope clear. It also states 'without changing anything,' which distinguishes it from sibling mutation tools like execute_approved_action.
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 this tool is for pre-write checks by focusing on mutation gates, providing clear context for when an agent would invoke it. However, it does not explicitly name alternatives or state exclusions, so it falls short of the highest level.
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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