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 retrieves a summary but doesn't clarify if this is a read-only operation, whether it affects the session state, what format the output takes, or any limitations (e.g., session must be active). This leaves significant gaps for a tool that likely interacts with session data.

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 a complete summary') and adds necessary detail ('with all steps and analysis'). There is no wasted wording, 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 has no parameters and no output schema, the description is minimally adequate but lacks depth. It doesn't explain what a 'thinking session' entails, the format of the summary, or how it integrates with sibling tools. For a tool in a complex environment with many siblings, more context 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. Baseline is 4 for zero parameters, as it avoids 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 verb ('Get') and resource ('complete summary of the current thinking session'), specifying it includes 'all steps and analysis'. However, it doesn't differentiate from siblings like 'reset_thinking' or 'sequential_thinking', which are related but distinct 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 implies usage for retrieving a summary of a thinking session, but provides no explicit guidance on when to use this tool versus alternatives (e.g., 'reset_thinking' to clear the session or 'sequential_thinking' for step-by-step processing). No prerequisites or exclusions 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds valuable context about the tool's safety profile ('safely shutdown') and its intended use for 'problematic instances.' However, it doesn't disclose important behavioral traits like what specific resources get cleaned up, whether the operation is reversible, what permissions are required, or any rate limits. The description provides some behavioral context but leaves significant 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 perfectly concise with just two sentences that each earn their place. The first sentence establishes the tool's identity and core functionality, while the second provides crucial usage guidance. There's zero wasted language, and the information is front-loaded with the most important details first.

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 potentially destructive operation (cleanup/shutdown) with no annotations and no output schema, the description should provide more complete context. While it mentions safety and workflow dependencies, it doesn't explain what 'clean up resources' entails, what happens to data, whether the operation can be undone, or what the tool returns. For a tool that modifies system state, this represents significant gaps in contextual information.

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 input schema has 100% description coverage, with the single parameter 'force' well-documented in the schema itself. The tool description doesn't mention any parameters or add semantic meaning beyond what the schema provides. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no parameter information 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 with specific verbs ('safely shutdown' and 'clean up') and identifies the target resource ('problematic instances'). It distinguishes itself from sibling tools by focusing on cleanup operations rather than diagnosis, monitoring, or project management functions. However, it doesn't explicitly differentiate from 'project_shutdown_instance' which appears to be a sibling tool with similar shutdown 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 clear contextual guidance by specifying 'Use after instance_diagnosis identifies issues,' establishing a workflow dependency. This gives the agent explicit direction about when to invoke this tool. However, it doesn't mention when NOT to use it or provide alternatives for similar cleanup scenarios, which prevents a perfect 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 the full burden. It discloses the tool performs both diagnosis AND repair (a behavioral trait), which implies it can modify instances. However, it lacks details about what 'repairs' entail (e.g., destructive changes, permissions needed, side effects) or response format. The description adds some value but 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 highly concise and well-structured: two sentences that efficiently convey purpose and usage. The first sentence establishes it as a diagnostic tool with priority guidance, and the second clarifies scope. Every word earns its place with zero waste.

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 has no parameters (simplifying context) but no annotations or output schema, the description is moderately complete. It covers the core purpose and usage but lacks details on what 'diagnoses and repairs' specifically involve, potential impacts, or return values. For a repair tool with no structured safety hints, more behavioral disclosure 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 with 100% schema description coverage (empty schema). The description doesn't need to explain parameters, so it appropriately doesn't mention any. A baseline of 4 is applied since no parameters exist, and the description doesn't incorrectly suggest 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: 'Diagnoses and repairs existing Visum instances' with the specific verb 'diagnoses and repairs' and resource 'existing Visum instances'. It distinguishes from creation tools but doesn't explicitly differentiate from all siblings like 'visum_health_check' or 'project_health_check' which might have overlapping diagnostic functions.

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 clear usage context: 'Run this first when encountering errors' and specifies it's for existing instances 'instead of creating new ones'. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the many sibling tools, such as distinguishing from 'visum_health_check' or 'project_health_check'.

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, the description carries full burden but provides minimal behavioral insight. It mentions 'optional save' but doesn't disclose what 'close' entails (e.g., whether it terminates processes, frees resources, or requires specific permissions), nor does it cover error handling or side effects like data loss if save is false.

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 ('Close a project TCP server') and adds a concise modifier ('with optional save'). There is no wasted verbiage, making it highly focused 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?

For a mutation tool with no annotations and no output schema, the description is insufficient. It lacks details on what 'close' means operationally, the implications of the save option, potential errors, or return values, leaving significant gaps in understanding the tool's full behavior and outcomes.

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 both parameters. The description adds no additional meaning beyond implying 'save' relates to project preservation before closure, but this is already clear from the schema. Baseline 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.

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

The description clearly states the action ('Close') and resource ('a project TCP server'), making the purpose understandable. It distinguishes from siblings like 'project_open' and 'project_shutdown_instance' by focusing on server closure with optional save, though it doesn't explicitly contrast with all similar 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?

No guidance is provided on when to use this tool versus alternatives like 'project_shutdown_instance' or 'project_status'. The description mentions an optional save feature but doesn't explain when to enable it or what happens if omitted, 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.

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 'execute a command' but doesn't disclose critical behavioral traits: whether this is a read-only or destructive operation, authentication requirements, rate limits, expected execution environment (e.g., Visum context implied by parameter but not described), or what happens on the TCP server. This leaves significant gaps for safe and effective use.

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 wasted words. It's front-loaded with the core action and target, making it easy to parse quickly. Every word 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.

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

Given the complexity of executing code on a TCP server with no annotations and no output schema, the description is insufficient. It lacks details on behavioral risks (e.g., destructive effects), expected outputs, error handling, or how it integrates with sibling tools. For a tool that likely performs significant operations, more context is needed for safe agent 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 fully documents each parameter's purpose. The description adds no additional meaning beyond implying execution in a 'Visum context' (hinted by the 'code' parameter description but not elaborated). With high schema coverage, the baseline score of 3 is appropriate as 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 action ('execute a command') and target ('on a project TCP server'), which is specific and actionable. It doesn't explicitly differentiate from siblings like 'project_execute_analysis' or 'visum_custom_analysis', but the verb+resource combination is unambiguous within the context of project 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?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'project_execute_analysis', 'visum_custom_analysis', and 'visum_create_procedure' that might overlap in executing code or commands, the description lacks any context about appropriate use cases, prerequisites, or distinctions.

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 'ultra-fast performance' and 'automatically generates Python code,' which adds some context beyond basic functionality. However, it lacks critical details: whether this is a read-only or destructive operation, what permissions are required, how errors are handled, or what the output looks like. For a tool that executes analysis and generates code, 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 concise and front-loaded, consisting of two sentences that efficiently convey the core functionality. The first sentence covers the main action and performance, while the second adds the unique code generation aspect. There's no unnecessary verbiage, and every sentence contributes directly to understanding the tool's purpose.

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 executing analysis and generating Python code, with no annotations and no output schema, the description is incomplete. It fails to address key contextual aspects: what the analysis entails, how the Python code is used or returned, what happens to the project instance, or potential side effects. For a tool with this level of functionality, more detail is needed to ensure safe and effective use by an AI agent.

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 input schema has 100% description coverage, providing clear documentation for all three parameters. The description doesn't add any meaningful semantics beyond what the schema already states—it doesn't explain parameter interactions, provide examples beyond the schema's hints, or clarify the 'analysisRequest' format further. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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: 'Execute intelligent analysis on specific project instance' and 'Automatically generates Python code based on analysis request.' It specifies the verb (execute analysis) and resource (project instance) with the unique aspect of Python code generation. However, it doesn't explicitly differentiate from siblings like 'project_execute' or 'visum_custom_analysis,' which 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 many sibling tools like 'project_execute,' 'visum_custom_analysis,' and 'visum_network_analysis,' there's no indication of when this specific analysis tool is preferred, what prerequisites exist, or when not to use it. The mention of 'ultra-fast performance' is a feature hint but not a usage guideline.

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 lacks critical behavioral details. It mentions the output format (CSV) and naming convention, but doesn't disclose whether this is a read-only operation, if it requires specific permissions, potential performance impact for large exports, or error handling. The description adds some context but misses key behavioral traits.

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?

Two concise sentences with zero waste. First sentence states purpose and scope, second sentence specifies output details. The emoji is optional but doesn't harm readability. Perfectly front-loaded with 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 2-parameter tool with no annotations and no output schema, the description adequately covers what the tool does but lacks completeness. It doesn't describe return values, error conditions, or behavioral constraints. The context about excluding Network Editor and file naming is helpful but insufficient for full 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?

Schema description coverage is 100%, so the schema fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., doesn't clarify 'maxRowsPerTable' behavior for partial exports). Baseline 3 is appropriate 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 specific action ('Export all Visum tables to CSV files'), identifies the resource ('Visum tables'), and distinguishes from siblings by specifying 'except Network Editor' and contrasting with 'project_export_visible_tables' which likely exports only visible tables. The emoji adds visual emphasis but doesn't detract from clarity.

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 context by mentioning 'except Network Editor' and the output location ('project directory'), but doesn't explicitly state when to use this vs. alternatives like 'project_export_visible_tables' or 'project_export_graphic_layout'. No guidance on prerequisites (e.g., project must be open) or exclusions is provided.

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 and does well by disclosing key behavioral traits: the multi-step workflow, format differences (raster vs vector), paper format support, and the critical requirement that 'SVG requires Visum GUI visible.' It also mentions scalability and editability of SVG. Missing details include error handling, performance expectations, or file size implications.

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?

Well-structured with emoji, workflow steps, and format details in a single paragraph. Every sentence adds value (workflow, format specs, GUI requirement). Could be slightly more concise by integrating the workflow into the main sentence, but overall efficient.

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 complex tool with 9 parameters and no output schema, the description provides good context: workflow, format differences, and GUI dependency. It compensates well for the lack of annotations. Minor gaps include no mention of error cases or what the output looks like (though format is specified).

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 9 parameters thoroughly. The description adds minimal parameter semantics beyond the schema—it mentions paper formats and SVG requirements which are covered in schema enums/descriptions. 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 specific action ('Load a Graphic Parameter file (.gpa) and export the network view as PNG/SVG') and distinguishes it from siblings like 'project_export_all_tables' or 'project_export_visible_tables' by focusing on graphic layout export rather than data tables. The emoji and workflow steps reinforce the visual/graphic nature of this tool.

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 clear context with a workflow (list files, select layout, export) and format guidance (PNG vs SVG, paper formats). However, it doesn't explicitly state when NOT to use this tool or name specific alternatives among the sibling tools, though the workflow implies 'project_list_available_layouts' as a prerequisite.

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 effectively describes key behaviors: it exports to CSV files, maintains exact column order, includes sub-attributes like formula columns, and operates on visible tables from a layout file. However, it doesn't mention potential side effects, error handling, or output specifics, leaving some 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.

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

The description is appropriately sized and front-loaded, starting with the core purpose and key features. The workflow section is useful but slightly lengthens the text; every sentence adds value, though it could be more streamlined by integrating the workflow more succinctly.

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 (exporting tables with specific attributes), no annotations, and no output schema, the description does a good job covering purpose, usage, and key behaviors. However, it lacks details on output format (e.g., CSV structure, file naming), error cases, or permissions, which would enhance completeness for a mutation tool.

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 input schema already documents both parameters (projectId and layoutFile) adequately. The description doesn't add any additional semantic details about these parameters 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.

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

The description clearly states the specific action (export tables to CSV files), the resource (tables visible in a Global Layout), and distinguishes it from sibling tools like project_export_all_tables by specifying 'ONLY tables visible in a Global Layout' and maintaining exact column order with sub-attributes. This provides precise differentiation from alternatives.

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 explicitly provides a step-by-step workflow that indicates when to use this tool (after listing layouts with project_list_available_layouts, selecting a layout, and loading it with project_load_global_layout). It also implicitly distinguishes from project_export_all_tables by focusing on visible tables only, offering clear contextual guidance.

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. While 'check health' implies a read-only diagnostic operation, the description doesn't specify what 'health' means in this context, what metrics are examined, whether authentication is required, or what the output format looks like. 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.

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

The description is extremely concise at just 6 words, which is efficient for such a simple operation. However, this brevity comes at the cost of completeness - it's so minimal that it lacks important contextual information that would help an agent use the tool effectively.

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 tool with no annotations, no output schema, and multiple similar sibling tools, the description is insufficiently complete. It doesn't explain what constitutes 'health' in this context, what the output looks like, or how this differs from other status-checking tools. The agent would need to guess about the tool's behavior and appropriate use cases.

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 the single parameter 'projectId' clearly documented in the schema. The description doesn't add any additional semantic context about the parameter beyond what the schema already provides, such as format requirements or valid values. The baseline score of 3 reflects adequate but minimal parameter documentation.

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 states the tool checks health of a specific project instance, which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'project_status', 'project_instances_status', or 'visum_health_check', leaving ambiguity about what distinguishes this health check from other status-related 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?

No guidance is provided about when to use this tool versus alternatives. With multiple sibling tools that seem related to project status/health (project_status, project_instances_status, visum_health_check), the description offers no context about what makes this tool the right choice or when other tools would be more appropriate.

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 implies a read-only operation ('Get status'), but doesn't specify details like whether it requires authentication, how it handles errors, what the return format is, or if there are rate limits. This is a significant gap 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 unnecessary words. It's front-loaded and wastes no space, 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 'status' entails (e.g., what data is returned), how 'active' is defined, or any behavioral traits like error handling. For a tool with no structured data to rely on, this leaves too many gaps for effective agent 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 input schema has 0 parameters with 100% coverage, so no parameter information is needed. The description appropriately doesn't discuss parameters, and since there are none, it doesn't need to compensate for any gaps. This meets the baseline for tools with no 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 action ('Get status') and target resource ('all active project instances'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'project_status' or 'project_health_check', which might have 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 like 'project_status' or 'project_health_check' from the sibling list. It lacks context about use cases, prerequisites, 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.

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 effectively describes the tool's behavior: it lists files, shows specific metadata (filename, size, full path), and operates on Global Layout files in the project directory. However, it doesn't mention potential limitations like pagination, error conditions, or file format validation.

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 perfectly concise with two sentences that each earn their place. The first sentence states the core functionality, and the second provides critical usage guidance. No wasted words, and the information is front-loaded appropriately.

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 no annotations and no output schema, the description provides good context about what information is returned (filename, size, full path) and the workflow purpose. However, without an output schema, it could benefit from more detail about the return format structure, though the description does specify the key data points.

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 'projectId' parameter. The description doesn't add any additional semantic context about this parameter beyond what's in the schema. The baseline score of 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 specific action ('List all Global Layout files'), resource ('.lay' files in project directory), and output details (filename, size, full path). It explicitly distinguishes this tool from its sibling 'project_load_global_layout' by stating it should be used BEFORE loading a layout to show available options.

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 explicit guidance on when to use this tool ('ALWAYS use this before loading a layout to show available options to the user') and implicitly distinguishes it from the sibling 'project_load_global_layout' tool. It clearly establishes the workflow sequence.

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. It discloses that the tool loads a layout into an opened project (implying a mutation/write operation) and mentions file existence requirements, but lacks details on permissions needed, error handling, or what happens if the layout fails to load. It adds some context but not comprehensive behavioral traits.

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?

Two sentences with zero waste: the first states the purpose and constraints, the second provides critical usage guidance. It's front-loaded with the core action and efficiently includes essential prerequisites without redundancy.

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 mutation tool with no annotations and no output schema, the description is reasonably complete: it covers the action, prerequisites, and file requirements. However, it lacks details on error cases or return values, which would be helpful given the tool's complexity. Sibling context is well-addressed via the project_list_available_layouts reference.

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 both parameters (projectId and layoutFile). The description adds marginal value by emphasizing the layout file must exist and can be a full path or filename, but doesn't provide syntax or format details beyond what the schema specifies. Baseline 3 is appropriate 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 specific action ('Load a Global Layout') and resource ('.lay file into an opened Visum project'), distinguishing it from siblings like project_list_available_layouts (which lists layouts) and project_export_graphic_layout (which exports layouts). It specifies the file format (.lay) and context (opened project).

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?

Explicitly states when to use this tool ('ALWAYS use project_list_available_layouts first to show available options to the user'), providing clear prerequisites and distinguishing it from the sibling tool that lists layouts. It also specifies the file location requirement ('must exist in the project directory or provide full path').

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 and adds valuable behavioral context beyond the basic 'open' function. It discloses that the tool 'Creates dedicated TCP server for ultra-fast communication' and provides error-handling guidance. However, it doesn't mention potential side effects like resource consumption or whether multiple instances can be opened simultaneously.

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 efficiently structured with three sentences that each serve distinct purposes: declaring the tool's role, describing a key behavioral trait, and providing error-handling guidance. It uses emojis and formatting effectively without unnecessary verbosity.

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 single-parameter tool with 100% schema coverage but no annotations or output schema, the description provides good context about the tool's behavior and usage. It could be more complete by explaining what 'opening' entails (e.g., whether it loads into memory, starts a session) or describing potential return values, but it adequately covers the essential information for tool selection and invocation.

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 'projectPath' parameter. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3 for adequate coverage through structured data alone.

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: 'opening Visum projects' with the specific action 'open, load, or launch' and resource 'Visum project'. It distinguishes from siblings by being the 'DEFAULT TOOL' for this function, differentiating from other project-related tools like 'project_close' or 'project_execute'.

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 explicit usage guidance: 'Always use this tool when asked to open, load, or launch any Visum project' and 'If you encounter errors, run 'instance_diagnosis' first!'. It clearly states when to use it (for opening projects) and references an alternative diagnostic tool for error scenarios.

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 states the tool saves a project but doesn't explain what 'save' entails (e.g., overwrites existing data, requires permissions, has side effects like closing the project, or handles errors). For a mutation tool with zero 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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action ('Save'), making it easy to parse. Every part of the sentence contributes to understanding the tool's function, with zero waste.

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 project save operation (a mutation with potential side effects), no annotations, and no output schema, the description is incomplete. It lacks details on behavior, error handling, or what 'save' means in this context (e.g., does it persist changes to a server or file?). For a tool with 2 parameters and significant implications, more context is needed to guide safe and 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 input schema fully documents both parameters ('projectId' and 'saveAs'). The description doesn't add any meaning beyond this, such as clarifying the scope of 'saveAs' (e.g., if it creates a new project or renames the current one). Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 action ('Save') and target ('currently opened project in its TCP server'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'project_export_all_tables' or 'project_close', which also involve project operations, leaving room for ambiguity about when to choose this specific save function.

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 (e.g., a project must be open), exclusions, or comparisons to siblings like 'project_export_all_tables' for saving to files. This lack of context makes it unclear when this is the appropriate choice among related project tools.

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 full burden. It states the action ('shutdown') but doesn't disclose critical behavioral traits: whether this is destructive, requires specific permissions, has side effects, or what happens to the instance (e.g., termination vs. suspension). 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 a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for a simple tool, earning full marks 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 tool's complexity (a mutation operation with potential side effects), lack of annotations, and no output schema, the description is incomplete. It doesn't address what 'shutdown' entails, success/failure indicators, or error conditions, leaving the agent under-informed for safe invocation.

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 no parameter semantics beyond what the schema provides. With 100% schema description coverage (the 'projectId' parameter is fully documented in the schema), the baseline is 3. The description doesn't compensate with additional context like format examples or constraints.

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 'Shutdown specific project instance' clearly states the action (shutdown) and target (specific project instance), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'project_close' or 'instance_cleanup', which might have overlapping functionality, preventing 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. With siblings like 'project_close', 'instance_cleanup', and 'project_start_instance', there's no indication of context, prerequisites, 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. It mentions 'dedicated persistent instance', hinting at resource allocation and state persistence, but lacks details on permissions, side effects, error conditions, or what 'start' entails operationally (e.g., initialization time, costs). This is inadequate 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.

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

The description is a single, efficient sentence with no wasted words. It front-loads 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.

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

For a tool that likely mutates state (starting an instance) with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after starting (e.g., instance state, return values, or errors), leaving critical gaps for an AI 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%, with the single parameter 'projectId' well-documented in the schema. The description adds no additional parameter context beyond implying it's for a 'specific Visum project', 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 clearly states the action ('Start') and the resource ('dedicated persistent instance for specific Visum project'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'visum_launch_project' or 'project_open', which might have overlapping functionality in a Visum context.

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 many sibling tools like 'project_open', 'visum_launch_project', and 'project_shutdown_instance', there's no indication of prerequisites, timing, or distinctions, leaving usage ambiguous.

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. It states it's a read operation ('Get'), implying it's non-destructive, but doesn't disclose any behavioral traits such as authentication needs, rate limits, or what the output format looks like (e.g., list of servers, health status). 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.

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

The description is a single, clear sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and efficiently communicates the core functionality, 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 checking server statuses and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'status' entails (e.g., running, stopped, error codes) or the return format, leaving the agent uncertain about the tool's behavior and output. This is inadequate for a tool that likely returns structured data.

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 the input schema has 100% description coverage (though empty). The description doesn't need to add parameter information, so it meets the baseline expectation for a parameterless tool. No additional semantic value is required or provided.

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 action ('Get status') and resource ('all active project TCP servers'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'project_instances_status' or 'project_health_check' which might overlap in functionality, preventing 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. With siblings like 'project_instances_status' and 'project_health_check' that might offer similar status checks, there's no indication of when this specific tool is preferred or what distinguishes it from them.

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. It states the tool clears and starts fresh, which implies a mutation, but doesn't disclose behavioral details such as whether this action is reversible, what data might be lost, or any side effects on other tools or sessions.

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 no wasted words, effectively front-loading the core action and purpose. It is appropriately sized for a simple tool with no parameters.

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 for a mutation tool. It doesn't explain what 'clear' entails, what 'start fresh' means in practice, or the expected outcome, leaving gaps in understanding the tool's behavior and effects.

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 the schema description coverage is 100%, so no parameter information is needed. The description appropriately doesn't discuss parameters, earning a high baseline score for not adding unnecessary 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 action ('Clear' and 'start fresh') and the target ('current thinking session'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'sequential_thinking' or 'get_thinking_summary', 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 implies usage when wanting to reset a thinking session, but provides no explicit guidance on when to use this tool versus alternatives like 'sequential_thinking' or 'instance_cleanup', nor does it mention any prerequisites or exclusions.

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 describes the tool as engaging in 'step-by-step thinking' and 'creating a chain of reasoning,' which implies a cognitive process, but it doesn't disclose key behavioral traits like whether this is a read-only or mutative operation, how it handles errors, or if there are rate limits. For a tool with 7 parameters and no annotations, 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 appropriately sized and front-loaded, consisting of two concise sentences that directly state the tool's purpose and method. Every sentence earns its place by explaining the core functionality without unnecessary details, making it efficient and well-structured for quick understanding.

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 7 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, usage context, and expected outcomes, which are crucial for an AI agent to effectively invoke this tool. The description does not adequately compensate for the missing 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 all parameters are documented in the input schema. The description adds no specific meaning beyond the schema, such as explaining how parameters interact or providing examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 'Engage in systematic step-by-step thinking to analyze complex problems, make decisions, or explore ideas,' which includes a specific verb ('engage') and resource ('thinking'). However, it doesn't explicitly distinguish this from sibling tools like 'reset_thinking' or 'get_thinking_summary,' which appear related to thinking processes, 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.

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 mentions building thoughts sequentially but doesn't specify contexts, prerequisites, or exclusions, such as when to choose this over 'reset_thinking' or other analysis tools. This lack of explicit usage guidelines limits its helpfulness for an AI agent.

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 describes the verification purpose and what gets returned (total volume, number of links with traffic, confirmation), which is helpful. However, it doesn't mention potential side effects, error conditions, performance characteristics, or authentication requirements. For a verification tool with zero annotation coverage, this provides basic but incomplete behavioral context.

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

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

The description is perfectly concise with three sentences that each earn their place: purpose statement, what it checks, and what it returns. It's front-loaded with the core purpose and wastes no words. The emoji adds visual clarity without distracting from the content.

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 and no output schema, the description provides adequate basic information about purpose and returns, but lacks details about the verification methodology, error handling, or what constitutes 'successful' execution. For a verification tool with 2 parameters and no structured output documentation, it covers the essentials but leaves gaps in behavioral context that would help an agent 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 fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'assignment' which relates to the tool's purpose but doesn't explain how parameters connect to that purpose. With complete schema coverage, baseline 3 is appropriate when the description adds no additional parameter semantics.

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 ('Verify if a PrT assignment has been executed successfully'), the resource involved ('volume data on links'), and distinguishes it from siblings by focusing on assignment verification rather than execution or analysis. It uses precise terminology like 'PrT assignment' and 'volume data on links' that differentiate it from other tools in the list.

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 context ('after assignment execution') but doesn't explicitly state when to use this tool versus alternatives like 'project_execute' or 'visum_network_analysis'. It mentions what the tool checks but provides no guidance on prerequisites or when not to use it. The context is clear but lacks explicit alternatives or exclusions.

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. It describes the configuration action but lacks details on permissions needed, whether changes are reversible, error conditions, or what happens to existing configurations. It mentions the tool's purpose and input options but doesn't fully disclose behavioral traits 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?

Three sentences with zero waste. First sentence states purpose, second provides prerequisite guidance, third explains input alternatives. Every sentence earns its place and the description is appropriately front-loaded with the core functionality.

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 configuration tool with 6 parameters, no annotations, and no output schema, the description covers purpose and usage well but lacks behavioral context about what configuration entails (permissions, side effects, error handling). It's adequate for basic understanding but incomplete for a mutation tool without structured safety information.

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 6 parameters thoroughly. The description adds marginal value by explaining the relationship between dsegset, segmentNumbers, and filterMode as alternatives, but doesn't provide additional syntax or format details beyond what's in the schema. Baseline 3 is appropriate 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 action ('Configure'), the target resource ('demand segments (DSEGSET) on a PrT Assignment procedure'), and distinguishes it from sibling tools by referencing visum_list_demand_segments. It specifies the verb+resource+context precisely.

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?

Explicitly states when to use this tool ('Use visum_list_demand_segments first to see available segments') and provides clear alternatives for input methods (segment codes OR numbers OR filter by mode). This gives comprehensive guidance on prerequisites and parameter 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 mentions using 'verified Visum API' and a specific method discovered on a date, but doesn't disclose critical behavioral traits: whether this is a mutation (likely yes, but not stated), what permissions are needed, whether it's idempotent, what happens on failure, or what the response contains. The API method detail is technical but doesn't help the agent understand behavioral implications.

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 reasonably concise (two sentences) but includes unnecessary technical details ('visum.Procedures.Operations.AddOperation() method discovered on 2025-10-10') that don't help an AI agent select or invoke the tool. The emoji adds visual emphasis but no semantic value. The first sentence is front-loaded with the core purpose, but the second sentence doesn't earn its place for agent decision-making.

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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after creation (does it return a procedure ID? status?), error conditions, or integration with sibling tools. The technical API details don't compensate for missing behavioral context needed for safe and effective tool invocation.

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 parameter semantics beyond what's in the schema - it doesn't explain relationships between parameters, provide examples of valid 'parameters' object contents, or clarify edge cases. Baseline 3 is appropriate 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 creates a Visum procedure, specifying the action (create) and resource (Visum procedure). It distinguishes from siblings by focusing on procedure creation rather than project management or analysis tasks. However, it doesn't explicitly differentiate from potential similar creation tools that might exist.

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 specific procedure types (PrT Assignment, PuT Assignment, etc.), it doesn't explain when to create a procedure versus using other tools like visum_check_assignment or visum_network_analysis. No prerequisites, exclusions, or alternative scenarios 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'access to the active Visum instance' and implies code execution, but fails to disclose critical traits: whether this is a read-only or destructive operation, potential security risks of arbitrary code execution, error handling, or output format. For a tool executing custom code, 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, front-loaded sentence that directly states the tool's purpose without unnecessary words. Every element ('Execute custom Python code', 'with access to the active Visum instance') earns its place by conveying essential information efficiently. There is zero waste or redundancy.

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 executing custom Python code and the lack of annotations and output schema, the description is incomplete. It doesn't address safety, permissions, result handling (e.g., the 'result' dictionary mentioned in the schema), or error scenarios. For a powerful, open-ended tool like this, the description should provide more context to guide safe and 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 thoroughly. The description adds no additional meaning beyond what's in the schema—it doesn't explain parameter interactions, coding conventions, or examples. With high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.

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 action ('Execute custom Python code') and the target resource ('with access to the active Visum instance'), making the purpose immediately understandable. It distinguishes itself from siblings like 'project_execute' or 'visum_network_analysis' by specifying custom code execution rather than predefined operations. 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.

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 (e.g., requires an active Visum instance), exclusions, or compare it to siblings like 'project_execute_analysis' or 'visum_network_analysis'. The agent must infer usage from the purpose alone, which is insufficient 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.

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 'health and status' but doesn't specify what that entails—e.g., whether it's a read-only operation, what metrics are returned, or if it has side effects like logging or alerts. For a tool with zero annotation coverage, this is insufficient to inform safe usage.

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: 'Check the health and status of the VisumPy instance.' It's front-loaded with the core action and resource, with no wasted words or redundancy. Every part of the sentence contributes directly to understanding the tool's purpose.

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 'health and status' means in practice—e.g., expected return values, error conditions, or operational context. For a tool that might involve system diagnostics, more detail is needed to guide an agent effectively.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate. A baseline of 4 is given since the schema fully handles parameters, and the description doesn't 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 tool's purpose: 'Check the health and status of the VisumPy instance.' It specifies the verb ('Check') and resource ('VisumPy instance'), making the action clear. However, it doesn't differentiate from sibling tools like 'project_health_check' or 'instance_diagnosis,' which might have overlapping functions, 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.

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 sibling tools such as 'project_health_check' and 'instance_diagnosis' available, there's no indication of context, prerequisites, or exclusions. This lack of comparative guidance makes it difficult for an agent 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 full burden. It discloses key behavioral traits: deprecated status, obsolescence, and slowness compared to the TCP-based alternative. However, it doesn't mention what the tool actually does behaviorally (e.g., whether it opens a file, starts a process, or requires specific permissions), leaving some gaps.

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

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

Two sentences with zero waste: the first declares deprecation and alternative, the second explains why (obsolete and slower). It's front-loaded with critical usage guidance and appropriately sized for a deprecated 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 is deprecated with a clear alternative, the description is complete enough for an agent to avoid it. However, with no annotations and no output schema, it lacks details on what the tool originally did (e.g., return values or side effects), which could be useful for legacy contexts.

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 the parameter 'projectPath' fully documented in the schema. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without compensating value.

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 states the tool is deprecated and obsolete, which implies it was used to launch projects, but it doesn't specify what 'launch' entails (e.g., opening, initializing, or starting a project). It distinguishes from sibling 'project_open' by noting obsolescence and slowness, but lacks a clear verb+resource statement for its original purpose.

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?

Explicitly states 'Use 'project_open' tool instead' and provides clear when-not-to-use guidance (deprecated, obsolete, slower). It names the alternative tool directly, making it unambiguous for the agent to avoid this tool in favor of the sibling.

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 indicates this is a read operation ('List') and mentions it operates on 'the loaded Visum project', but doesn't specify whether it requires authentication, has rate limits, returns paginated results, or what format the output takes. It provides basic context but lacks operational 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 perfectly concise with two sentences that each serve distinct purposes: the first states what the tool does, the second provides usage guidance. There's zero wasted language, and the information is front-loaded with the core purpose stated immediately.

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 good schema coverage but no output schema, the description provides adequate context. It specifies the resource scope (demand segments for PrT modes), mentions the project context, and gives clear usage guidance. However, without an output schema, it could benefit from mentioning what the list returns (e.g., segment IDs, names, or codes).

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 both parameters. The description doesn't add any additional parameter semantics beyond what's in the schema descriptions. It mentions 'PrT modes' which relates to the filterMode parameter, but doesn't provide new syntax or format details. The baseline of 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 specific action ('List all available demand segments') and specifies the resource type ('for PrT modes in the loaded Visum project'). It distinguishes from potential siblings by focusing on demand segments specifically, unlike broader tools like visum_network_analysis or visum_network_stats.

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 explicitly states when to use this tool ('Use this before configuring DSEGSET on a procedure') and references a specific sibling tool (visum_configure_dsegset) as the next step. This provides clear contextual guidance for tool sequencing.

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 'detailed statistics and performance metrics' but doesn't specify what these include, whether the analysis is read-only or modifies data, potential performance impacts, or error conditions. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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, well-structured sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the main action ('Analyze') and resource, making it easy to parse. Every part of the sentence adds value.

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 (analysis with parameters) and lack of annotations or output schema, the description is minimally adequate but incomplete. It specifies what the tool does but omits critical details like output format, behavioral traits, and usage context. For a tool with no output schema, it should ideally hint at return values, but it doesn't, leaving 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?

Schema description coverage is 100%, so the schema fully documents both parameters ('includeGeometry' and 'sampleSize') with descriptions and defaults. The tool description adds no parameter-specific information beyond what's in the schema, such as how 'sampleSize' affects results or what 'geometric analysis' entails. 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 tool's purpose: 'Analyze the loaded Visum network with detailed statistics and performance metrics.' It specifies the verb ('analyze'), resource ('loaded Visum network'), and output type ('detailed statistics and performance metrics'). However, it doesn't explicitly differentiate from sibling tools like 'visum_network_stats' or 'visum_custom_analysis', which might offer similar 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. It doesn't mention prerequisites (e.g., a network must be loaded), exclusions, or comparisons to sibling tools like 'visum_network_stats' or 'visum_custom_analysis'. The agent must infer usage from the tool name and context 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on traits like whether it's read-only, requires specific permissions, has rate limits, or what the output format might be. This is a significant gap for a tool that likely returns data, making it inadequate for informed use.

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 key action and resource. It wastes no words and is appropriately sized for the tool's simplicity, earning full marks 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 complexity (a data-fetching tool with no annotations and no output schema), the description is incomplete. It doesn't explain what 'comprehensive network statistics' entails, the return format, or any behavioral constraints. This leaves the agent with insufficient information to use the tool effectively in context.

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 the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, so it meets the baseline for a parameterless tool. No additional semantics are required, but it doesn't compensate for any gaps since there are none.

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 action ('Get') and resource ('comprehensive network statistics from the loaded Visum project'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'visum_network_analysis' or 'visum_health_check', which might also involve network-related operations, 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. It doesn't mention prerequisites (e.g., a loaded project), exclusions, or compare it to siblings like 'visum_network_analysis', leaving the agent with minimal context for selection.

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