Xcode MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
Most tools have distinct purposes, but there is some overlap between list_directory and list_project_files, as both list files, though one is general and the other project-specific. Tools like analyze_file and trace_app are clearly differentiated for static analysis vs. performance tracing.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern using snake_case, such as analyze_file, boot_simulator, and build_project. There are no deviations in naming style, making the set predictable and easy to parse.
Tool Count4/5With 18 tools, the count is slightly high but reasonable for an Xcode server covering project management, building, testing, debugging, and simulator operations. It might feel a bit heavy, but each tool appears to serve a specific function in the domain.
Completeness4/5The toolset provides good coverage for Xcode workflows, including project setup, building, testing, debugging, and simulator control. Minor gaps might include tools for code signing or managing provisioning profiles, but core operations are well-represented.
Average 3.1/5 across 18 of 18 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 issues responded to in the last 6 months
- No commit activity data available
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool uses 'actool' but doesn't disclose behavioral traits like whether it's read-only or destructive, permission requirements, error handling, or output format. This leaves significant gaps for a compilation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste, clearly stating the action and tool used. It's appropriately sized for a simple tool, though it could be more front-loaded with key details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a compilation tool. It lacks details on what the compilation entails, success/failure outcomes, or how it integrates with other tools, failing to compensate for the missing structured data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (catalogPath and outputDir) adequately. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool compiles an asset catalog using 'actool', which is a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'build_project' or 'run_xcrun' that might also involve compilation processes, making the purpose somewhat vague in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It doesn't mention prerequisites, when-not scenarios, or how it relates to sibling tools like 'build_project' that might handle broader compilation tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Boots') but doesn't describe what happens during booting (e.g., startup time, state changes, error conditions), whether it requires specific permissions, or what the output looks like. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a mutation tool (implied by 'Boots') with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., side effects, error handling), output format, or usage context. The agent must rely heavily on the tool name and schema alone, which is insufficient for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'udid' fully documented in the schema. The description adds no additional semantic context beyond implying that a UDID identifies the simulator, which is already covered by the schema. This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Boots') and the target resource ('an iOS simulator identified by its UDID'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'shutdown_simulator' or 'list_simulators', but the verb 'Boots' implies a specific startup operation distinct from shutdown or listing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the simulator must exist or be in a shutdown state), when not to use it, or how it relates to sibling tools like 'shutdown_simulator' or 'list_simulators'. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool performs a build operation, implying mutation (e.g., compiling code), but doesn't disclose behavioral traits such as execution time, side effects (e.g., generating binaries), error handling, or dependencies on other tools. This leaves significant gaps for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Builds the active Xcode project') and specifies key parameters. There is zero waste, making it appropriately sized and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a build operation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral aspects (e.g., what 'builds' entails, output location, success/failure indicators) and doesn't compensate for the absence of structured data, making it inadequate for safe agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both parameters ('configuration' and 'scheme') well-documented in the schema. The description adds no additional meaning beyond implying these parameters are required for the build, matching the baseline score when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Builds') and target ('the active Xcode project'), specifying the verb and resource. It distinguishes from siblings like 'run_tests' or 'compile_asset_catalog' by focusing on full project builds, but doesn't explicitly differentiate from all alternatives like 'run_xcrun' which might also involve building.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active project set via 'set_project_path'), exclusions, or compare to siblings like 'run_tests' for testing builds. Usage is implied by the action but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions what the tool does but fails to disclose behavioral traits like error handling (e.g., if the path doesn't exist), permissions required, output format (e.g., list structure), or any side effects. This leaves significant gaps for an agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain what the output looks like (e.g., a list of filenames, error messages), nor does it cover behavioral aspects like handling of non-existent paths. For a tool with no structured output or annotations, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'path' parameter fully. The description adds no additional meaning beyond what the schema provides, such as examples of valid paths or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Lists') and resource ('contents of a directory'), and distinguishes it from siblings like 'list_project_files' by specifying it shows both files and subdirectories. However, it doesn't explicitly differentiate from 'list_simulators' or other list tools, keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'list_project_files' or 'analyze_file'. It lacks context about prerequisites, such as whether the directory must exist or be accessible, and doesn't mention any exclusions or specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a listing operation, implying read-only behavior, but doesn't mention potential side effects, permissions needed, rate limits, or what the output format looks like (e.g., list structure, error handling). This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any fluff. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of listing files in an Xcode project, no annotations, and no output schema, the description is insufficient. It doesn't explain return values, error conditions, or how it interacts with sibling tools, leaving significant gaps for the agent to understand the tool fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for both parameters in the input schema. The description adds no additional parameter semantics beyond what the schema already provides, such as examples or constraints. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lists') and resource ('all files within an Xcode project'), making the purpose immediately understandable. However, it doesn't distinguish this tool from the sibling 'list_directory' tool, which might also list files in a directory context, so it misses full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'list_directory' or 'get_active_project'. It lacks context about prerequisites (e.g., needing an Xcode project) or exclusions, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the basic read operation but lacks critical details: it doesn't mention file size limits, encoding considerations, error handling for non-existent files, or whether it returns raw text or structured data. For a file I/O tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently communicates the core functionality without unnecessary words. It's front-loaded with the essential information and contains no redundant or verbose elements.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of file reading operations and the absence of both annotations and an output schema, the description is insufficient. It doesn't address what format the content is returned in (text, binary, encoding), size limitations, or error scenarios. For a tool that interacts with file systems, more behavioral context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the parameter 'filePath' is fully documented in the schema. The description adds no additional parameter information beyond what's already in the schema, which is acceptable given the high schema coverage. This meets the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Reads') and resource ('contents of a file within the active Xcode project'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'analyze_file' or 'list_project_files', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'read_file' over 'analyze_file' or 'list_project_files', nor does it specify prerequisites like requiring an active project. This leaves the agent with insufficient context for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool launches LLDB but doesn't describe what happens during execution (e.g., whether it blocks, requires user input, outputs debug info, or has side effects). For a tool that likely interacts with system processes, this lack of behavioral context is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's front-loaded with the core action ('launches') and resource ('LLDB debugger'), making it easy to parse. Every word earns its place, achieving optimal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of launching a debugger (which may involve system interactions, output handling, or dependencies), the description is inadequate. With no annotations, no output schema, and minimal behavioral context, it leaves critical gaps. The agent lacks information on what the tool returns, how errors are handled, or what execution entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'lldbArgs' documented as 'Optional LLDB arguments.' The description doesn't add any meaning beyond this—it doesn't explain what valid arguments are, provide examples, or clarify the argument format. With high schema coverage, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('launches') and resource ('LLDB debugger'), making the purpose immediately understandable. It distinguishes from siblings like 'run_tests' or 'trace_app' by specifying the debugger tool. However, it doesn't explicitly differentiate from all potential debugging-related tools, keeping it at a 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (e.g., needing a project set up), when to prefer this over other debugging tools, or what scenarios it's designed for. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool executes tests but doesn't describe what this entails—e.g., whether it runs all tests or specific ones, if it requires a simulator (like 'boot_simulator'), what output or errors to expect, or if it's a blocking/long-running operation. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core action and target, making it easy to parse quickly. Every part of the sentence earns its place by conveying essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of test execution in Xcode (which can involve simulators, dependencies, etc.), no annotations, no output schema, and a simple but incomplete description, this is inadequate. The description doesn't cover behavioral aspects, error handling, or integration with sibling tools, making it incomplete for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with one optional parameter 'testPlan' documented as 'Optional name of the test plan to run.' The description adds no additional parameter semantics beyond this, so it meets the baseline of 3 by not contradicting the schema but doesn't provide extra value like examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Executes tests') and the target ('for the active Xcode project'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'build_project' or 'trace_app' which might also involve project execution, leaving room for ambiguity about when to choose this specific tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an active project via 'get_active_project' or 'set_project_path'), exclusions, or comparisons to siblings like 'run_lldb' or 'trace_app' for debugging-related testing. This lack of context makes it harder for an AI agent to select the right tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose execution environment, error handling, permissions needed, or output format, which are critical for a command 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste, front-loading the core action. It's appropriately sized for the tool's scope, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of executing Xcode tools, lack of annotations, and no output schema, the description is incomplete. It doesn't cover execution context, result handling, or error cases, leaving significant gaps for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the two parameters. The description adds no additional meaning beyond implying execution via 'xcrun', which is minimal value over the schema's details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('executes') and resource ('a specified Xcode tool via xcrun'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'run_lldb' or 'run_tests' which also execute commands, missing full distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It doesn't mention prerequisites like having Xcode installed, or compare to siblings like 'run_lldb' for debugging or 'run_tests' for testing, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the basic action without behavioral details. It doesn't disclose whether this changes global state, requires specific permissions, has side effects (e.g., loading project settings), or what happens on failure (e.g., invalid path). For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation operation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral traits, error handling, or output expectations, which are crucial for an agent to use it correctly in an Xcode context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'projectPath' fully documented in the schema as 'Path to the .xcodeproj directory for the desired project.' The description adds no additional meaning beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Sets') and the resource ('active Xcode project'), specifying it requires a path to a .xcodeproj directory. It distinguishes from siblings like 'get_active_project' by indicating a setter function, but doesn't explicitly contrast with 'set_projects_base_dir' which might handle a different type of path setting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It doesn't mention prerequisites (e.g., needing an Xcode environment), when not to use it, or how it relates to siblings like 'set_projects_base_dir' or 'get_active_project' for context switching.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action 'Sets', implying a mutation, but doesn't describe effects like persistence, permissions needed, error handling, or whether changes are reversible. This is a significant gap for a tool that modifies system state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity as a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, return values, error conditions, and differentiation from siblings, making it inadequate for safe and effective use by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't add any parameter-specific information beyond what's in the input schema, which has 100% coverage and fully documents the 'baseDir' parameter. According to the rules, with high schema coverage (>80%), the baseline is 3 even without extra param details in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Sets' and the resource 'base directory where your Xcode projects are stored', making the purpose specific and understandable. However, it doesn't explicitly differentiate from the sibling tool 'set_project_path', which appears related but has a different name, leaving some ambiguity about when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 the sibling 'set_project_path' or other configuration tools. It lacks context about prerequisites, timing, or exclusions, leaving the agent to infer usage based on 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?
No annotations are provided, so the description carries full burden. It mentions the action ('captures') and tool ('xctrace'), but lacks critical behavioral details: whether it's read-only or destructive (e.g., modifies app state), permission requirements, output format (e.g., trace file location), or error handling. For a tool with potential side effects, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It front-loads the core action ('Captures a performance trace') and includes essential context ('using xctrace'). Every word earns its place, making it highly concise and well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool with potential complexity. It doesn't explain what the trace output is (e.g., a file, data structure), how to access results, or behavioral risks. For a performance tracing tool, this leaves critical gaps in understanding its full context and usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear parameter descriptions in the schema. The description adds no additional parameter semantics beyond implying 'appPath' targets an application and 'duration' sets trace time. Since the schema already documents these well, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('captures a performance trace') and resource ('of an application'), specifying the method ('using xctrace'). It distinguishes from siblings like 'run_tests' or 'analyze_file' by focusing on performance profiling rather than execution or analysis. However, it doesn't explicitly differentiate from all siblings (e.g., 'run_xcrun' could also involve tracing), keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an iOS/macOS app), exclusions (e.g., not for web apps), or compare to siblings like 'run_tests' for functional testing. Without such context, an agent might misuse it in inappropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool performs static analysis but does not describe what happens during execution (e.g., whether it modifies the file, requires network access, has rate limits, or outputs results to a log). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to understand at a glance. There is no wasted verbiage or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of static analysis (which can involve detailed outputs and potential side effects), the description is incomplete. There are no annotations to clarify behavior, no output schema to explain return values, and the description lacks details on execution context (e.g., dependencies, error handling). For a tool with no structured support, the description should provide more operational context to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the single parameter 'filePath' documented as 'Path to the source file to analyze.' The description does not add any additional meaning beyond this, such as file format requirements or path resolution rules. With high schema coverage, the baseline score of 3 is appropriate, as the schema adequately defines the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('analyzes') and resource ('a source file'), specifying the tool used ('Xcode's static analyzer') and the goal ('for potential issues'). It distinguishes from siblings like 'read_file' (which reads content) or 'run_tests' (which executes tests) by focusing on static analysis rather than execution or simple I/O.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., requires Xcode installation), exclusions (e.g., not for binary files), or comparisons to siblings like 'build_project' (which might include analysis) or 'run_lldb' (for dynamic analysis). Usage is implied only by the action itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool retrieves information (implying read-only), but doesn't disclose behavioral traits such as error handling (e.g., if no project is active), performance characteristics, or what 'detailed information' includes. This leaves gaps for an AI agent to understand how to invoke it correctly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that is front-loaded with the core purpose ('Retrieves detailed information'). There is no wasted text, and every word earns its place by specifying the action and target clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple read operation with no parameters) and lack of annotations and output schema, the description is minimally adequate. It states what the tool does but doesn't explain the return values or potential errors. For a tool with no structured output, more detail on what 'detailed information' entails would improve completeness, but it's not entirely incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100% (since there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters, as it doesn't have to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('currently active Xcode project'), specifying it provides 'detailed information'. It distinguishes from siblings like 'list_project_files' (which lists files) or 'set_project_path' (which sets a path). However, it doesn't explicitly contrast with all siblings, so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. For example, it doesn't mention prerequisites like needing an active project or compare to 'list_project_files' for file listings. The description implies usage for getting project details but offers no explicit when/when-not instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool can 'writes or updates' files, implying mutation, but fails to disclose critical behavioral traits such as required permissions, whether changes are reversible, error handling, or any rate limits. The description is minimal and lacks necessary operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that is front-loaded with the core purpose. There is no wasted language, and every word contributes directly to understanding the tool's function, 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a file write/update operation with no annotations and no output schema, the description is insufficient. It does not cover behavioral aspects like error conditions, side effects, or response format, leaving significant gaps for an AI agent to understand how to use the tool effectively in practice.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description does not add any semantic details beyond what the schema provides (e.g., it doesn't explain file path conventions or content formatting). Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('writes or updates'), the target resource ('content of a file'), and the context ('in the active Xcode project'). It uses precise verbs and distinguishes itself from sibling tools like 'read_file' by specifying the opposite operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for file content modification in Xcode projects but does not explicitly state when to use this tool versus alternatives like 'analyze_file' or 'read_file'. It provides context ('active Xcode project') but lacks explicit guidance on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool updates dependencies but doesn't disclose behavioral traits like whether it modifies project files, requires specific permissions, has side effects, or provides output/errors. For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Updates the dependencies') and includes essential context ('Swift project', 'Swift Package Manager', command invocation). 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool performs a mutation (updating dependencies) with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error handling, or behavioral implications, leaving gaps for an AI agent to understand execution outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately omits parameter details, focusing on the tool's purpose. Baseline is 4 for zero parameters, as it avoids unnecessary information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Updates the dependencies') and target resource ('your Swift project using Swift Package Manager'), with the exact command invoked ('swift package update'). It distinguishes from siblings like 'build_project' or 'run_tests' by focusing on dependency management rather than compilation or testing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when updating Swift package dependencies, but provides no explicit guidance on when to use this tool versus alternatives (e.g., 'build_project' for building after updates). It mentions the context ('Swift project using Swift Package Manager') but lacks exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the action ('Shuts down') but lacks details on behavioral traits such as whether this is destructive, requires specific permissions, or has side effects (e.g., stopping associated processes). This is a significant gap for a mutation tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence contributes directly to understanding the tool's function, making it appropriately sized and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple mutation with one parameter) and no annotations or output schema, the description is minimally adequate. It covers the basic action and parameter but lacks completeness in behavioral context, such as error handling or return values, which would be needed for full agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'udid' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints, so it meets the baseline for high coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Shuts down') and target resource ('an active iOS simulator'), distinguishing it from sibling tools like 'boot_simulator' and 'list_simulators'. It precisely identifies the verb and resource without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'an active iOS simulator', suggesting it should be used when a simulator is running. However, it does not explicitly state when not to use it or name alternatives like 'boot_simulator' for starting simulators, leaving some guidance gaps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- 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 of behavioral disclosure. It specifies that the tool invokes a specific command ('xcrun simctl list --json'), which implies it's a read-only operation that fetches data. However, it lacks details on output format (e.g., JSON structure), error handling, or performance considerations like rate limits, leaving some behavioral traits unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose and implementation method. It is front-loaded with the core action and resource, with no wasted words or unnecessary details, 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.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is adequate but has gaps. It explains what the tool does and how it works, but without annotations or output schema, it misses details on behavioral traits like error handling or return format. For a read-only listing tool, this is minimally viable but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here. Baseline is 4 for 0 parameters, as no additional semantics are needed beyond what the schema already indicates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Lists all available iOS simulators') and the resource ('iOS simulators with their details'), including the exact command invoked ('xcrun simctl list --json'). It distinguishes itself from siblings like 'list_directory' or 'list_project_files' by focusing specifically on iOS simulators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to list iOS simulators, but does not explicitly state when to use this tool versus alternatives like 'run_xcrun' (which could run other commands) or other listing tools. No exclusions or prerequisites are mentioned, leaving usage context somewhat implied rather than clearly defined.
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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