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 mentions the technologies (tree-sitter, Jina embeddings) but doesn't describe key behaviors: whether this is a long-running or resource-intensive operation, what happens on failure, if it creates persistent files, or what the output looks like. For a tool that likely involves file processing and API calls, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Build a vector index for semantic code search') and adds technical context ('using tree-sitter and Jina embeddings') without unnecessary details. Every word 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of building a vector index (involving file processing, embeddings, and potential API calls), no annotations, and no output schema, the description is insufficient. It lacks information on behavioral traits, output format, error handling, or dependencies. For a 4-parameter tool with no structured safety or output info, it should provide more context to be complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain how 'file_patterns' interact with the workspace or default behaviors). With high schema coverage, the baseline is 3, and the description doesn't compensate with extra insights.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Build'), the resource ('a vector index'), and the purpose ('for semantic code search'), while distinguishing it from siblings like 'semantic_search' (which likely queries an existing index) and 'clear_vector_index' (which removes an index). It also mentions the specific technologies used ('tree-sitter and Jina embeddings'), which adds precision.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for creating a search index, but it doesn't explicitly state when to use this tool versus alternatives like 'semantic_search' (for querying) or 'clear_vector_index' (for removal). It also doesn't mention prerequisites (e.g., needing files in the workspace) or exclusions. The context is clear but lacks explicit guidance on tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool 'delete[s] all index files', which implies destructive behavior, but doesn't specify whether this is irreversible, what permissions are required, whether it affects search functionality, or what happens after deletion (e.g., empty state vs. error). The description is minimal and lacks important 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and target, making it immediately understandable. Every word earns its place in conveying the essential operation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'clear' means operationally, what happens to dependent functionality (like semantic_search), whether the tool returns confirmation or status, or what recovery options exist. The high-risk nature of this operation demands more contextual guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents the single 'confirm' parameter. The description adds no additional parameter information beyond what's in the schema. This meets the baseline of 3 when schema coverage is complete, though the description doesn't enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('clear', 'delete') and target resource ('vector index', 'all index files'), distinguishing it from sibling tools like 'build_vector_index' or 'vector_index_status'. It precisely communicates a destructive operation on the vector index system.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 'build_vector_index' for rebuilding or 'vector_index_status' for checking status. It mentions no prerequisites, warnings about data loss, or scenarios where this operation is appropriate versus other maintenance approaches.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('find class definitions'), but doesn't describe how it behaves—e.g., whether it searches recursively, returns partial matches, handles errors, or has performance constraints. This leaves critical behavioral traits unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded and directly states the tool's purpose without unnecessary elaboration, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., file paths, code snippets, or structured data), error conditions, or search scope. For a tool with 2 parameters and no structured behavioral hints, more context is needed for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 itself. The tool description adds no additional meaning beyond the schema, such as explaining how 'class_name' matching works or what 'file_pattern' syntax is accepted. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Find class definitions by name'. It specifies the verb ('find') and resource ('class definitions'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'find_function' or 'semantic_search', 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'find_function' for functions, 'grep' for general text search, or 'semantic_search' for content-based queries. Without this context, an agent might struggle to choose appropriately.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 'finds' files, implying a read-only operation, but doesn't mention potential side effects, performance implications, or output format. For a tool with no annotation coverage, this is inadequate, as it omits key behavioral details like whether it searches recursively or respects file permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is 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 appropriately sized and front-loaded, with every part contributing to clarity, earning a top score for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., file paths, metadata), how results are ordered, or any limitations (e.g., search depth). For a tool with no structured output information, the description should provide more context to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal value beyond the input schema, which has 100% coverage. It mentions 'glob syntax' and provides examples like '*.py', but the schema already describes 'pattern' with similar examples. Since schema coverage is high, the baseline is 3, and the description doesn't significantly enhance parameter understanding beyond what's in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Find files by name pattern using glob syntax.' It specifies the verb ('Find'), resource ('files'), and method ('by name pattern using glob syntax'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'list_files' or 'grep', which limits the score to 4 instead of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_files' (which might list all files without filtering) or 'grep' (which searches within file contents), nor does it specify prerequisites or exclusions. This lack of contextual usage information results in a low score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states the basic action without behavioral details. It doesn't disclose whether this is a read-only operation, if it searches across files or a workspace, performance considerations, or output format. For a tool with no annotations, this is inadequate as it misses key 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero waste—'Find function definitions by name' is front-loaded and efficiently conveys the core purpose without unnecessary words. It earns its place by being direct and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and a simple input schema, the description is incomplete. It doesn't explain what a 'function definition' includes (e.g., signatures, bodies), the search scope (e.g., current directory, all files), or return values. For a tool in a code-focused server with many siblings, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters ('function_name' as required and 'file_pattern' as optional). The description adds no additional meaning beyond implying the tool uses 'function_name' to find definitions, which aligns with the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Find function definitions by name' clearly states the action (find) and target (function definitions), but it's vague about scope and doesn't distinguish from siblings like 'find_class' or 'grep'. It specifies 'by name' which helps, but lacks detail on what constitutes a 'function definition' or where it searches.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 'find_class' for classes, 'grep' for text search, or 'semantic_search' for broader code queries. The description implies it's for functions by name, but doesn't specify contexts or exclusions, leaving the agent to guess based on tool names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions the use of regular expressions but doesn't specify behavioral traits such as search scope (e.g., recursive directory traversal), performance implications (e.g., large file handling), error handling (e.g., invalid regex patterns), or output format (e.g., line-by-line results with context). This leaves significant gaps for an agent to understand how the tool behaves in practice.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core functionality ('Search for text patterns in files') and adds necessary detail ('using regular expressions'). There's no wasted verbiage, repetition, or unnecessary elaboration—every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a regex search tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., matched lines, file names, line numbers), how errors are handled, or any constraints (e.g., encoding issues, large result sets). For a tool with 3 parameters and significant behavioral nuances, this leaves the agent under-informed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with clear documentation for all three parameters ('pattern', 'file_pattern', 'max_results'). The description adds minimal value beyond the schema, only implying that 'pattern' is a regular expression (which is already stated in the schema's description). It doesn't provide additional context like regex flavor examples or practical usage tips for the parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does 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 ('Search') and resource ('text patterns in files'), and mentions the method ('using regular expressions'). It distinguishes itself from siblings like 'find_files' (which likely searches for files, not content) and 'semantic_search' (which likely uses semantic matching rather than regex). However, it doesn't explicitly contrast with 'string_replace' (which might also use regex for replacement operations).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to prefer 'grep' over 'semantic_search' for pattern matching, or over 'find_files' for file content searches. There's no context about prerequisites, limitations, or typical use cases beyond the basic functionality stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states basic functionality. It doesn't disclose important behavioral aspects like whether this is a read-only operation (implied but not stated), potential performance considerations for large directories, pagination behavior (though max_results is in schema), or what happens with non-existent directories. The description adds minimal context beyond the basic operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a straightforward listing tool and front-loads the essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only listing tool with 3 well-documented parameters and no output schema, the description provides adequate but minimal context. It covers the basic purpose but lacks details about return format, error conditions, or performance considerations that would be helpful given the absence of annotations and output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all three parameters. The description mentions 'filtering options' which aligns with the parameters but doesn't add any meaningful semantic context beyond what's in the schema. 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resources 'files and directories in the workspace', making the purpose immediately understandable. It distinguishes from siblings like 'find_files' by focusing on directory listing rather than pattern-based searching. However, it doesn't explicitly contrast with 'workspace_info' which might also provide file information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for browsing workspace contents with filtering, but doesn't explicitly state when to use this versus alternatives like 'find_files' for pattern matching or 'workspace_info' for workspace metadata. No guidance is provided about when NOT to use this tool or about prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 adds useful context about the 10MB size limit and text file support, which are not in the schema. However, it does not cover other behavioral aspects like error handling, permissions needed, or what happens with non-text files, leaving gaps for a read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core action ('Read file contents') and includes only essential additional details (optional line range and 10MB/text file support). Every part earns its place with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (read operation with optional parameters) and no annotations or output schema, the description is partially complete. It covers key constraints (size and file type) but lacks details on return values, error cases, or performance implications, which would be helpful 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters (file_path, start_line, end_line) with their descriptions. The description adds no additional parameter semantics beyond what the schema provides, such as format details or examples, meeting the baseline score when schema coverage is high.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Read file contents') and resource ('file'), distinguishing it from siblings like 'list_files' (which lists metadata) and 'write_file' (which modifies content). It also specifies the optional line range capability, making the purpose explicit and differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for reading text files up to 10MB with optional line ranges, but does not explicitly state when to use this tool versus alternatives like 'view_code' or 'grep'. It provides some context (file type and size limit) but lacks explicit guidance on exclusions or named alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions framework detection and test execution but doesn't describe what happens during execution (e.g., output format, error handling, side effects), whether it requires specific project structure, or how it interacts with the workspace. 'Run tests' implies execution but lacks behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that communicates the core purpose with zero waste. It's appropriately sized for a tool with good schema documentation and gets straight to the point without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter execution tool with no annotations and no output schema, the description provides minimal but adequate context about what the tool does. It covers the 'what' but lacks details about execution behavior, results format, or integration with the workspace environment. The schema handles parameter documentation well, but behavioral aspects are underspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 4 parameters. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. The baseline score of 3 reflects adequate but not enhanced parameter understanding when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as 'Run tests using detected testing frameworks' with specific examples (pytest, jest, maven). It uses a clear verb+resource pattern but doesn't explicitly differentiate from sibling tools like 'find_class' or 'view_code' which are inspection tools rather than execution tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. While it mentions detection of frameworks, it doesn't specify prerequisites, appropriate contexts, or when not to use it. The sibling tools include various code inspection and manipulation tools, but no testing alternatives are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions 'vector embeddings' but doesn't explain what this entails—e.g., whether it requires pre-built indexes, how results are ranked, or if there are rate limits. For a search tool with no annotation coverage, this is a significant gap 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.

Is 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 details. It's appropriately sized and wastes no words, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of semantic search and the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like indexing requirements, result format, or error handling. For a tool with 4 parameters and no structured output info, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema, such as explaining how 'query' interacts with embeddings or the impact of 'filter_type'. 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.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Search for code using natural language descriptions with vector embeddings.' It specifies the verb ('search'), resource ('code'), and method ('natural language descriptions with vector embeddings'), which is specific and informative. However, it doesn't explicitly differentiate from siblings like 'grep' or 'find_class', which would require a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like 'grep' (for text-based search) or 'find_class'/'find_function' (for exact matches), nor does it specify contexts where natural language search is preferred. This leaves the agent without clear usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions 'with validation' which suggests error checking or constraints, but doesn't explain what validation entails (e.g., file existence checks, permission requirements, backup creation, or what happens on failure). For a mutation tool that modifies files, this is a significant gap in safety and 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that communicates the core functionality without unnecessary words. It's appropriately sized and front-loaded with the essential action. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a file mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'validation' means, what happens on success/failure, whether files are backed up, or what permissions are required. The context signals show 4 parameters and no output schema, yet the description provides minimal operational guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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 4 parameters. The description adds no parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Replace occurrences of a string in a file with validation.' It specifies the verb ('replace'), resource ('string in a file'), and includes an important qualifier ('with validation'). However, it doesn't explicitly differentiate from sibling tools like 'write_file' or 'grep' that might have overlapping functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. With siblings like 'write_file' (general file writing), 'grep' (searching), and 'read_file' (reading), there's no indication of when this specific string replacement tool is preferred. The mention of 'validation' hints at a use case but doesn't define boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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. While 'check' implies a read-only operation, it doesn't specify what 'status' includes (e.g., health, size, last update), whether it requires permissions, or what happens on failure. This leaves significant gaps for a tool with zero 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.

Is 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, with every word earning its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'status' entails, what format the response uses, or any behavioral nuances. For a tool with no structured data support, this leaves too much ambiguity for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema description coverage is 100%, so there's no need for parameter explanation in the description. The baseline for zero parameters is 4, as the description appropriately avoids unnecessary parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does 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 ('check') and resource ('vector index for semantic search'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'semantic_search' or 'build_vector_index', which would require a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to check status versus building or clearing the index, nor does it explain how this differs from 'semantic_search' or other search-related tools in the sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions 'with context' but doesn't specify what that entails (e.g., line numbers, surrounding code, or metadata). It fails to address key aspects like read-only nature, error handling, or output format, which are crucial for a tool with multiple parameters and no 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.

Is 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 ('View specific code sections with context') earns its place by conveying the essential action and scope, 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain the return values, error conditions, or how 'context' is provided, leaving significant gaps for an AI agent to understand the tool's behavior and output fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond implying that parameters like 'span_ids' or line numbers help view 'specific code sections with context', but it doesn't clarify interactions between parameters (e.g., how 'span_ids' relates to line ranges). Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'View specific code sections with context' clearly states the tool's purpose with a specific verb ('view') and resource ('code sections'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'read_file' or 'find_class', which might offer overlapping functionality, so it doesn't reach the highest score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as 'read_file' (for full files) or 'find_class' (for specific classes). It lacks explicit context, exclusions, or named alternatives, leaving the agent to infer usage from the tool name and parameters alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 retrieves information (implying read-only), but doesn't clarify permissions needed, whether it's safe to invoke frequently, what 'etc.' includes, or how the information is structured. For a 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Get information about the current workspace') and adds clarifying examples ('path, git status, etc.') without redundancy. It could be slightly more structured by explicitly listing all information types, but it's appropriately sized for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on return values (no output schema) and behavioral context (no annotations). For a tool that likely returns structured workspace metadata, more completeness on output format would be helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does 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%, so there are no parameters to document. The description appropriately doesn't waste space on parameter details, earning a baseline score of 4 for not introducing unnecessary complexity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does 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 ('Get') and resource ('information about the current workspace'), including examples of what information is retrieved ('path, git status, etc.'). It distinguishes from siblings like 'list_files' or 'view_code' by focusing on workspace metadata rather than file operations. However, it doesn't explicitly differentiate from all siblings (e.g., 'vector_index_status' also provides workspace-related status).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or when other tools might be more suitable (e.g., using 'list_files' for file listings or 'vector_index_status' for vector database status). The agent must infer usage from the purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 mentions that parent directories are created if needed, which is useful context, but it fails to disclose critical traits such as whether the operation overwrites existing files, requires specific permissions, handles errors (e.g., invalid paths), or has side effects. 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded, consisting of only two sentences that directly state the tool's action and a key behavioral trait. Every word earns its place, with no redundant or vague language, 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral aspects like overwriting behavior, error handling, or return values, which are crucial for safe and effective use. The description does not compensate for the absence of structured data, leaving significant gaps in understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, meaning the input schema already fully documents both parameters ('content' and 'file_path'). The description does not add any additional meaning beyond what the schema provides, such as format details or constraints. However, since the schema coverage is high, the baseline score of 3 is appropriate as the description does not need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Write content to a file') and resource ('a file'), distinguishing it from sibling tools like 'read_file' (which reads) and 'list_files' (which lists). It also mentions the additional behavior of creating parent directories, which further clarifies its purpose beyond basic file writing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. For example, it does not mention when to use 'write_file' over 'string_replace' (which modifies file content) or 'find_files' (which searches files), nor does it specify prerequisites like file permissions or workspace context. This lack of comparative context leaves usage unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.