twilize
Server Quality Checklist
- Disambiguation2/5
Many tools have overlapping or unclear boundaries, causing potential confusion. For example, 'csv_to_dashboard', 'hyper_to_dashboard', 'mssql_to_dashboard', and 'mysql_to_dashboard' all perform similar end-to-end dashboard creation from different data sources, making it hard to choose the right one. Additionally, tools like 'inspect_csv', 'profile_csv', and 'suggest_charts_for_csv' have overlapping analysis purposes, and 'add_reference_band', 'add_reference_line', and 'add_trend_line' are closely related visualization additions.
Naming Consistency4/5Most tools follow a consistent verb_noun or verb_preposition_noun pattern (e.g., 'add_calculated_field', 'configure_chart', 'list_dashboards'), which aids readability. However, there are minor deviations like 'csv_to_dashboard' (noun_to_noun) and 'undo_last_change' (verb_adjective_noun), slightly breaking the pattern but not severely impacting usability.
Tool Count2/5With 55 tools, the count is excessive for the server's purpose of Tableau dashboard creation and management. This large number suggests over-fragmentation, such as having separate tools for each data source type (CSV, Hyper, MSSQL, MySQL) instead of a unified approach, which can overwhelm users and increase complexity without clear benefits.
Completeness5/5The tool set provides comprehensive coverage for Tableau workbook and dashboard operations, including data source handling (CSV, Hyper, SQL), schema inspection, chart configuration, layout management, migration, and validation. It supports full CRUD-like workflows from data ingestion to dashboard output, with no obvious gaps in the domain.
Average 3.3/5 across 50 of 55 tools scored. Lowest: 1.9/5.
See the tool scores section below for per-tool breakdowns.
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Tool Scores
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does at a high level without revealing any behavioral traits such as whether it modifies existing charts, creates new ones, requires specific permissions, has side effects, or how it interacts with other tools. This is inadequate for a tool with 29 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence. It's front-loaded with the core action ('Configure') and resource ('dual-axis chart composition'), though this brevity comes at the cost of being under-specified given the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the high complexity (29 parameters, 1 required), no annotations, 0% schema description coverage, and the presence of an output schema, the description is completely inadequate. It doesn't explain what the tool does in practical terms, how to use it, what the parameters mean, or what behavior to expect. The output schema existence doesn't compensate for these fundamental gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 29 parameters have descriptions in the schema. The tool description provides no information about any parameters, not even the required 'worksheet_name' or what the dual-axis configuration entails. This fails to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Configure a dual-axis chart composition' states the general purpose (configuring a dual-axis chart) but is vague about what specifically it does. It doesn't distinguish this tool from sibling tools like 'configure_chart' or 'configure_chart_recipe', nor does it specify what resources it acts upon beyond the generic 'chart composition'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to chart configuration (e.g., 'configure_chart', 'configure_chart_recipe', 'add_reference_line'), there's no indication of when this specific dual-axis configuration tool is appropriate or what prerequisites might be needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without behavioral details. It does not disclose if this is a mutation (likely, given 'add'), permission requirements, side effects (e.g., altering datasource structure), or response behavior (though an output schema exists), leaving significant gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words, making it front-loaded and easy to parse. However, it is overly terse given the tool's complexity (6 parameters, mutation action), bordering on under-specification rather than optimal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 6 parameters, 0% schema coverage, no annotations, and sibling tools, the description is incomplete. It lacks usage context, parameter explanations, behavioral traits, and differentiation from siblings, though the presence of an output schema slightly mitigates the need to describe return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds no parameter information. It does not explain what 'field_name', 'formula', or other parameters mean, their formats, or examples (e.g., formula syntax), failing to provide semantic context beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Add a calculated field') and target ('to the datasource'), which provides a basic purpose. However, it lacks specificity about what a 'calculated field' entails (e.g., derived from existing data) and does not differentiate from sibling tools like 'add_parameter' or 'add_reference_line', making it vague in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing an existing datasource), exclusions, or comparisons to siblings like 'remove_calculated_field' or 'list_fields', leaving the agent without contextual usage cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides zero behavioral information beyond the basic purpose. With no annotations provided, the description carries full burden but fails to disclose whether this is a read or write operation, what permissions are required, whether changes are destructive, what happens to existing chart configurations, or any error conditions. This is completely inadequate for a tool with 23 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded with the essential information about what the tool does.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex configuration tool with 23 parameters, no annotations, and 0% schema description coverage, the description is completely inadequate. While an output schema exists, the description provides no context about the tool's behavior, parameter usage, or relationship to sibling tools. This leaves the agent with insufficient information to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 23 parameters, the description provides no information about any parameters. It doesn't explain what 'mark_type' means, what 'columns' and 'rows' represent, how 'color_map' works, or any other parameter semantics. The description fails completely to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('configure') and target ('chart type and field mappings for a worksheet'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'configure_chart_recipe' or 'configure_dual_axis', which appear to be related chart configuration tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple configuration-related siblings (configure_chart_recipe, configure_dual_axis, configure_worksheet_style), there's no indication of when this specific chart configuration tool is appropriate versus those other options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions configuration but doesn't specify whether this is a read-only or destructive operation, what permissions are required, or how it interacts with the shared registry. This leaves critical behavioral traits undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point without unnecessary words. It's appropriately sized for a basic purpose statement, though it could be more informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a configuration tool with 4 parameters, 0% schema coverage, no annotations, and sibling tools, the description is incomplete. It lacks details on behavior, parameters, and usage context. While an output schema exists, the description doesn't provide enough guidance for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 4 parameters are documented in the schema. The description adds no parameter information beyond what's implied by the tool name, failing to compensate for the schema gap. Parameters like 'recipe_args' and 'auto_ensure_prerequisites' remain unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'configures a showcase recipe chart through the shared recipe registry,' which provides a clear verb ('configure') and resource ('showcase recipe chart'). However, it lacks specificity about what configuration entails and doesn't differentiate from sibling tools like 'configure_chart' or 'configure_dual_axis,' making it somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions, leaving the agent with no usage direction beyond the basic purpose statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is an 'Add' operation, implying a mutation, but doesn't clarify permissions needed, whether changes are reversible, side effects, or response format. For a tool with 7 parameters and no annotation coverage, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized and front-loaded, clearly stating the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, mutation operation), lack of annotations, and 0% schema description coverage, the description is incomplete. While an output schema exists, the description doesn't compensate for missing behavioral context or parameter semantics, making it inadequate for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 7 parameters have descriptions in the schema. The tool description adds no information about parameters beyond their names implied by context. It doesn't explain what 'action_type', 'fields', or other parameters mean, leaving semantics entirely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add an interaction action to a dashboard' clearly states the verb ('Add') and resource ('interaction action to a dashboard'), making the purpose understandable. However, it's somewhat vague about what an 'interaction action' entails and doesn't distinguish this tool from sibling tools like 'add_dashboard' or 'configure_chart', which also modify dashboards. It avoids tautology but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., after creating a dashboard), or exclusions. With many sibling tools for dashboard manipulation, this omission leaves the agent without direction on selecting this specific tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions pausing for warnings, which hints at interactive behavior, but doesn't disclose critical traits like whether it's destructive, what permissions are needed, rate limits, or what happens during migration failures. For a migration tool with 6 parameters, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for the tool's complexity, though it lacks detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, 0% schema coverage, no annotations, and sibling tools with similar names, the description is incomplete. It doesn't explain the migration context, what 'TWB' refers to, or how outputs are handled (though an output schema exists). For a complex migration tool, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for all 6 parameters. It adds no meaning beyond the schema—doesn't explain what 'file_path', 'target_source', 'scope', or other parameters do, their formats, or relationships. This leaves parameters largely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool runs a migration workflow and pauses for warnings, which gives a general purpose. However, it's vague about what exactly is being migrated (TWB files? data sources?), doesn't specify the resource clearly, and doesn't distinguish from sibling tools like 'apply_twb_migration' or 'preview_twb_migration'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'apply_twb_migration' or 'preview_twb_migration'. The description mentions pausing for warnings, which implies interactive use, but doesn't specify prerequisites, when-not scenarios, or explicit alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool adds a parameter but gives no information about permissions required, whether this action is reversible, potential side effects, or what the output looks like. This is inadequate for a mutation 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 1 required) and lack of annotations, the description is insufficient. It doesn't explain parameter meanings, usage context, or behavioral traits, and while an output schema exists, the description doesn't hint at what to expect from the operation, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning none of the 9 parameters are documented in the schema. The description adds no parameter information beyond the tool's name, failing to compensate for the lack of schema documentation. Parameters like 'datatype', 'domain_type', and 'allowed_values' remain unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add a parameter to the workbook' clearly states the action (add) and target resource (parameter to workbook), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'add_calculated_field' or 'add_dashboard' beyond the resource type, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as when to add a parameter versus other workbook components like calculated fields or dashboards. There are no prerequisites, exclusions, or contextual hints mentioned, leaving usage entirely implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states 'Set a custom color palette,' implying a mutation operation, but doesn't disclose behavioral traits such as whether this affects all charts globally, requires specific permissions, is reversible, or has side effects. The mention of built-in palettes adds some context but is insufficient 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the main action, followed by examples. It avoids unnecessary words, but could be more structured by separating custom and built-in usage explicitly. Every sentence adds value, though it's slightly terse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a mutation tool with 3 parameters, 0% schema coverage, no annotations, and sibling tools that might overlap, the description is incomplete. It lacks details on when to use, parameter meanings, behavioral effects, and how it integrates with other tools. The presence of an output schema helps but doesn't compensate for these gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for all three parameters. It only indirectly hints at 'palette_name' by listing built-in options and 'colors' by mentioning 'custom,' but doesn't explain the purpose of 'custom_name' or the relationship between parameters. No details on format, constraints, or usage are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Set a custom color palette') and the resource ('color palette'), making the purpose evident. It distinguishes between custom and built-in palettes by listing examples of built-in ones, though it doesn't explicitly differentiate from sibling tools like 'configure_chart' or 'configure_worksheet_style' that might involve color settings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description mentions built-in palettes but doesn't specify if this tool is for overriding defaults, applying to specific elements, or when to choose custom vs. built-in options. There's no mention of prerequisites or related tools like 'apply_dashboard_theme'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool adds a reference line but doesn't disclose behavioral traits such as whether this is a mutating operation, what permissions are needed, how errors are handled, or what the output contains. The description is minimal and lacks critical behavioral context for a tool with 8 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and includes helpful examples. Every part of the sentence earns its place by clarifying the tool's purpose concisely.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, no annotations, 0% schema coverage) and the presence of an output schema, the description is incomplete. It doesn't explain parameter usage, behavioral implications, or provide context for when to use the tool. The output schema may cover return values, but the description lacks necessary operational details for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'constant, average, median, etc.', which loosely relates to the 'formula' parameter, but doesn't explain any of the 8 parameters (e.g., 'worksheet_name', 'axis_field', 'value', 'scope'). The description adds minimal meaning beyond the schema, failing to address the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add a reference line') and the target ('to a worksheet'), with examples of line types ('constant, average, median, etc.'). It distinguishes from siblings like 'add_reference_band' or 'add_trend_line' by specifying reference lines, though it doesn't explicitly contrast them. The purpose is specific but could be more differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'add_reference_band' or 'add_trend_line'. The description mentions types of reference lines but doesn't specify contexts or prerequisites for use. Usage is implied only by the tool name and description, with no explicit when/when-not instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions that styling is applied to 'all zones in a dashboard,' which implies a mutation operation affecting multiple components. However, it doesn't disclose critical behavioral traits like whether this operation is reversible, what permissions are required, whether it overwrites existing styling, or what happens if parameters are omitted. For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that gets straight to the point with zero wasted words. It's appropriately sized for a tool with 4 parameters and no annotations, and it's front-loaded with the core purpose. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a mutation tool with 4 parameters, 0% schema description coverage, no annotations, and an output schema (which reduces the need to describe return values), the description is incomplete. It lacks behavioral context (e.g., permissions, reversibility), parameter details, and usage guidelines. The presence of an output schema helps, but the description doesn't provide enough information for an agent to use the tool confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the 4 parameters have descriptions in the schema. The description mentions 'background' and 'font,' which loosely correspond to 'background_color' and 'font_family' parameters, but it doesn't explain what 'title_font_size' does or provide any details about parameter formats, constraints, or defaults. The description adds minimal value beyond the parameter names, failing to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Apply uniform styling (background, font) to all zones in a dashboard.' It specifies the action (apply styling), the target (dashboard zones), and the styling aspects (background, font). However, it doesn't explicitly differentiate from sibling tools like 'configure_worksheet_style' or 'apply_color_palette', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There are several sibling tools related to styling and configuration (configure_worksheet_style, apply_color_palette, configure_chart), but the description doesn't mention any of them or specify when this tool is appropriate versus others. It only states what it does, not when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions 'write a migrated TWB plus reports' which implies file creation/output, it doesn't address important behavioral aspects like whether this is a destructive operation, what permissions are required, whether it modifies the original file, error handling, or performance characteristics. The description is minimal and lacks 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that efficiently communicates the core purpose. There's no wasted language or unnecessary elaboration. It's appropriately sized for what it does communicate, though it could benefit from additional context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, 0% schema coverage, no annotations, and complex migration functionality, the description is insufficiently complete. While there is an output schema (which helps with understanding return values), the description doesn't provide enough context about the tool's behavior, parameter usage, or relationship to sibling migration tools to enable effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 5 parameters, the description provides no information about any parameters. It doesn't explain what 'file_path', 'target_source', 'output_path', 'scope', or 'mapping_overrides' mean or how they should be used. The description fails to compensate for the complete lack of parameter documentation in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('apply a workbook migration') and the outcome ('write a migrated TWB plus reports'), providing specific verb+resource information. However, it doesn't differentiate this tool from sibling tools like 'migrate_twb_guided' or 'preview_twb_migration', which appear related to migration workflows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There are several sibling tools that appear related to migration (migrate_twb_guided, preview_twb_migration) and workbook operations, but the description offers no context about when this specific migration application tool is appropriate versus those other options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It implies a mutation ('Apply'), but doesn't disclose whether changes are reversible, if it requires specific permissions, or what happens to unspecified style properties. The description mentions visibility toggles but doesn't clarify if these are additive or replace existing settings.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every word contributes to understanding the tool's scope without redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex mutation tool with 21 parameters, 0% schema coverage, no annotations, and an output schema (which helps but isn't described), the description is inadequate. It doesn't cover parameter meanings, behavioral implications, or usage context, leaving significant gaps for an AI agent to correctly invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 21 parameters and 0% schema description coverage, the description only mentions 4 general categories (background color, axis/grid/border visibility) out of many parameters. It doesn't explain the purpose of parameters like 'pane_cell_style', 'label_formats', or 'axis_style', leaving most parameters semantically undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Apply') and target ('worksheet-level styling'), with specific examples of styling aspects (background color, axis/grid/border visibility). It distinguishes this as a styling tool, but doesn't explicitly differentiate from potential styling-related siblings like 'configure_chart' or 'apply_color_palette'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'configure_chart', 'apply_color_palette', 'add_worksheet'), the description doesn't indicate whether this is for initial setup, updates, or specific worksheet types, nor does it mention prerequisites like needing an open workbook.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It doesn't explain what 'propose' means operationally (e.g., does it generate suggestions, require confirmation, modify files?), what permissions are needed, or what the output contains beyond the existence of an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just one sentence with zero wasted words. It's front-loaded with the core purpose and doesn't include any unnecessary elaboration or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters (2 required), 0% schema coverage, no annotations, but with an output schema, the description is insufficient. While the output schema may document return values, the description fails to explain the tool's behavior, parameter meanings, or usage context needed for effective agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for all 4 parameters, the description provides no parameter semantics whatsoever. It doesn't explain what 'file_path', 'target_source', 'scope', or 'mapping_overrides' represent, their expected formats, or how they influence the mapping proposal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('scan source and target schema') and outcome ('propose a field mapping'), providing a specific verb+resource combination. However, it doesn't differentiate itself from sibling tools like 'inspect_target_schema' or 'migrate_twb_guided' which might involve similar schema analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or when other tools like 'migrate_twb_guided' or 'apply_twb_migration' might be more suitable for mapping-related tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the configuration action without behavioral details. It doesn't disclose if this modifies an existing workbook, requires specific permissions, has side effects (e.g., overwriting connections), or handles errors. The phrase 'Configure' implies mutation but lacks depth on consequences or operational constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. 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.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage, no annotations, and sibling tools for other data sources, the description is incomplete. It doesn't address parameter meanings, usage context, or behavioral traits, though the presence of an output schema mitigates the need to describe return values. For a configuration tool with multiple parameters, more guidance is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'filepath', 'table_name', or 'tables' represent, their formats, or how they interact (e.g., that 'filepath' points to a Hyper file). This leaves all three parameters semantically unclear beyond their schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Configure') and the target ('workbook datasource'), specifying it's for a 'local Hyper extract connection'. It distinguishes from siblings like set_mssql_connection or set_mysql_connection by focusing on Hyper files. However, it doesn't explicitly contrast with other data source tools beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like set_mssql_connection or hyper_to_dashboard. It lacks context about prerequisites (e.g., needing an existing workbook or Hyper file) or when this configuration is appropriate, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states 'configure' without explaining behavioral traits. It doesn't disclose if this is a destructive operation, what permissions are needed, whether it overwrites existing connections, or any rate limits. The description is too vague for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and appropriately sized for what it conveys, though it lacks detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 5 parameters, 0% schema coverage, no annotations, and an output schema (unseen), the description is inadequate. It doesn't explain what configuration entails, the impact on the workbook, error conditions, or return values. The presence of an output schema helps, but the description leaves too many gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what server_host, dbname, username, table_name, or port mean in context, their formats, or relationships. The description fails to provide semantic context beyond the schema's basic titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Configure') and the resource ('workbook datasource'), specifying it's for a Microsoft SQL Server connection. It distinguishes from siblings like set_hyper_connection or set_mysql_connection by naming the specific database type, but doesn't explain what 'configure' entails beyond connection setup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like set_mysql_connection or set_hyper_connection is provided. The description implies it's for setting up an MSSQL connection, but doesn't mention prerequisites, timing, or what happens after configuration.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Configure', implying a write/mutation operation, but doesn't disclose behavioral traits such as authentication requirements, whether this overwrites existing settings, potential side effects, or error handling. The description is minimal and lacks crucial operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero waste, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (a configuration tool with 5 parameters, no annotations, and an output schema), the description is incomplete. It doesn't explain what the tool returns (though output schema exists), lacks parameter details, and omits behavioral context needed for safe and effective use. The minimal description fails to compensate for the lack of annotations and low schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'local MySQL connection' but doesn't explain any parameters (server, dbname, username, table_name, port) or their roles in the configuration. No additional meaning is provided beyond the bare schema, leaving parameters semantically unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Configure') and the target resource ('workbook datasource'), specifying it's for a 'local MySQL connection'. It distinguishes from siblings like 'set_mssql_connection' and 'set_hyper_connection' by specifying MySQL, but doesn't explicitly differentiate from other data source tools beyond the connection type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'set_mssql_connection' or 'set_hyper_connection', nor does it mention prerequisites or context for configuring a workbook datasource. The description implies usage for MySQL connections but lacks explicit when/when-not instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions configuration but does not specify whether this is a read-only or destructive operation, what permissions are required, or how it affects existing connections. This leaves critical behavioral traits unclear for a tool that likely modifies workbook settings.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no unnecessary words, making it highly concise and front-loaded. It efficiently communicates the core purpose without redundancy or structural issues.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, likely a mutation operation) and the absence of annotations, the description is insufficient. It does not explain parameter meanings, behavioral implications, or output details, even though an output schema exists. This leaves significant gaps for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters are undocumented in the schema. The description does not add any semantic details about the parameters (e.g., what 'server' or 'dbname' represent, format expectations, or default behaviors), failing to compensate for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Configure') and the target ('workbook datasource to use a Tableau Server connection'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like set_hyper_connection or set_mssql_connection, which serve similar configuration purposes for different connection types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as set_hyper_connection or set_mssql_connection. The description lacks context about prerequisites, typical scenarios, or exclusions, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Create a dashboard' which implies a write operation, but fails to detail permissions, side effects, or what happens on success/failure. No information on rate limits, idempotency, or response format is included, leaving 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action, making it easy to grasp quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters with 0% schema coverage and no annotations, the description is insufficiently complete—it lacks parameter details and behavioral context. However, the presence of an output schema mitigates the need to describe return values, keeping it from being completely inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining parameters. It mentions 'combining multiple worksheets', which hints at 'worksheet_names', but doesn't clarify the purpose of 'dashboard_name', 'width', 'height', or 'layout'. This leaves most parameters semantically unclear beyond what the schema titles provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a dashboard') and the resource ('combining multiple worksheets'), making the purpose immediately understandable. It distinguishes from siblings like 'add_worksheet' or 'create_workbook' by focusing on dashboard creation with worksheets, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'create_workbook' or 'add_worksheet', nor does it mention prerequisites such as needing existing worksheets. The description only states what it does, not when or why to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the tool adds a reference band but doesn't disclose whether this is a mutating operation, what permissions are needed, if it's reversible (e.g., via 'undo_last_change'), or how it interacts with existing worksheet elements. Some context is implied (e.g., visual modification), but key behavioral traits are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Add a reference band') and specifies the target ('to a worksheet') with clarifying detail ('shaded region'). There is zero wasted verbiage, making it highly concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters with 0% schema coverage and no annotations, the description is incomplete—it doesn't address parameters, behavioral nuances, or usage context. However, an output schema exists (per context signals), so return values needn't be explained. The description covers the basic purpose adequately but leaves significant gaps for a tool with many parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'axis_field', 'from_value/to_value', 'from_formula/to_formula', 'scope', or 'fill_color' mean or how they affect the band. The agent must rely solely on schema property names, which are somewhat descriptive but lack semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add a reference band') and the target resource ('to a worksheet'), specifying it creates a 'shaded region'. It distinguishes from siblings like 'add_reference_line' by specifying a band/region rather than a line. However, it doesn't explicitly differentiate from all visualization-adding siblings (e.g., 'add_trend_line'), keeping it at 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'add_reference_line' or 'configure_chart'. There's no mention of prerequisites, typical use cases, or exclusions. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool analyzes a TWB file but doesn't describe what the analysis entails, whether it's read-only or modifies data, what permissions are required, or what the output includes. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description doesn't need to explain return values. However, with no annotations, 0% schema coverage, and one parameter, the description is minimal and lacks details on behavior, usage context, or parameter semantics. It's adequate for basic understanding but has clear gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one parameter ('file_path') undocumented in the schema. The description adds no information about this parameter, such as what format the file path should be in, whether it's local or remote, or any constraints. It fails to compensate for the lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('analyze') and target resource ('a TWB file'), specifying it's against 'twilize's declared capabilities'. It distinguishes from siblings like 'validate_workbook' or 'profile_twb_for_migration' by focusing on capability analysis rather than validation or profiling. However, it doesn't explicitly contrast with these alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'validate_workbook', 'profile_twb_for_migration', or 'list_capabilities'. The description implies usage for analyzing TWB files against capabilities but offers no context on prerequisites, exclusions, or specific scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool creates a new workbook, implying a write operation, but lacks details on permissions, side effects (e.g., file overwriting), or response format. This is insufficient for a mutation 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is front-loaded with the core action and resource, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is an output schema, the description does not need to explain return values. However, as a mutation tool with no annotations and low parameter coverage, it lacks sufficient context on behavior and usage. The description is minimally adequate but has clear gaps in guidance and transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'template_path' and implies 'workbook_name' through context, but does not explain their semantics (e.g., file formats, naming constraints). This adds minimal value beyond the schema's property titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create a new workbook') and specifies the resource source ('from a TWB or TWBX template file'), making the purpose unambiguous. However, it does not differentiate from sibling tools like 'open_workbook' or 'save_workbook', which involve similar workbook operations but with different intents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing a template file), exclusions, or comparisons to sibling tools like 'open_workbook' (for existing workbooks) or 'save_workbook' (for saving changes).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool describes a capability and its support tier, but doesn't mention whether this is a read-only operation, what permissions are needed, how errors are handled, or what the output format looks like. For a tool with no annotation coverage, this leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that efficiently conveys the core function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description doesn't need to explain return values. However, with no annotations, 2 undocumented required parameters, and a sibling tool ('list_capabilities') that might overlap in function, the description is incomplete. It adequately states the purpose but lacks usage context and parameter guidance needed for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning neither parameter has descriptions in the schema. The tool description doesn't explain what 'kind' and 'name' refer to, their expected values, or how they identify a capability. With 2 required parameters and no schema descriptions, the description fails to compensate for the lack of parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('describe') and resource ('one declared capability and its support tier'), making it easy to understand what the tool does. However, it doesn't differentiate from its sibling 'list_capabilities', which appears to list multiple capabilities rather than describe a single one.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'list_capabilities'. The description lacks context about prerequisites, such as needing to know the capability kind and name beforehand, or when detailed information about a specific capability is required.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'summarize' but doesn't explain what the output entails, whether it's a read-only analysis, if it modifies the template, or any performance considerations. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and target, making it easy to parse quickly, though this brevity contributes to gaps in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description doesn't need to detail return values. However, with no annotations, 0% schema coverage, and one parameter, the description is too minimal—it lacks parameter explanations and behavioral context, making it incomplete for effective use despite the output schema support.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. It doesn't mention the 'file_path' parameter at all, failing to explain what it represents (e.g., path to a TWB template file) or any constraints. This leaves the parameter's meaning unclear beyond the schema's basic type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('summarize') and the target ('non-core capability gap of a TWB template'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'describe_capability' or 'list_capabilities', which might cover similar analytical functions, leaving some ambiguity about its unique role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'describe_capability' or 'analyze_twb'. It lacks context about prerequisites, scenarios, or exclusions, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Generate and save' implies a write operation that creates a file, but the description doesn't specify whether this overwrites existing files, requires specific permissions, has side effects, or provides confirmation of success. This is inadequate for a tool with three parameters and no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a tool with a straightforward name and clearly front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there's an output schema (which should document return values), the description doesn't need to explain outputs. However, with three parameters at 0% schema coverage, no annotations, and a write operation implied, the description is too minimal—it should provide at least basic parameter context or behavioral details to be complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the three parameters (output_path, layout_tree, ascii_preview) have descriptions in the schema. The tool description adds no information about what these parameters mean, their formats, or how they interact, failing to compensate for the complete lack of schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate and save') and the resource ('a dashboard layout JSON file'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential siblings that might also generate or save JSON files, though none are obvious in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, dependencies, or context for when this operation is appropriate, leaving the agent with no usage context beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'inspect,' implying a read-only operation, but fails to detail aspects like authentication requirements, rate limits, error handling, or what the inspection entails (e.g., schema format, metadata). This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded with the main action and resource, making it easy to grasp quickly, which is ideal for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is an output schema (which likely describes the return values), the description does not need to explain outputs. However, with no annotations, low parameter coverage, and multiple sibling inspection tools, the description lacks sufficient context on usage, parameters, and behavioral traits, making it only minimally adequate for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, and the tool description does not explain the 'target_source' parameter beyond implying it refers to an Excel datasource. No details on format, examples, or constraints are provided, failing to compensate for the schema's lack of documentation and leaving the parameter's meaning unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('inspect') and resource ('first-sheet schema of a target Excel datasource'), making the tool's function evident. However, it does not explicitly differentiate itself from sibling tools like 'inspect_csv' or 'inspect_hyper', which also inspect data sources, leaving room for ambiguity in tool selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'inspect_csv' or 'inspect_hyper', nor does it mention prerequisites or context for its application. This lack of usage instructions could lead to confusion in tool selection among similar inspection tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool is for 'preview,' implying a read-only or simulation action, but does not clarify if it requires specific permissions, what the preview output entails (e.g., report format), or any side effects like temporary file changes. This leaves significant gaps for a tool with multiple parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it easy to parse. It is front-loaded with the core action, though this brevity contributes to gaps in other dimensions like guidelines and transparency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, 0% schema coverage, no annotations, but an output schema exists, the description is minimally adequate. It states the purpose but lacks details on parameter usage, behavioral context, and differentiation from siblings. The output schema may cover return values, but the description does not fully address the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters are undocumented in the schema. The description adds minimal semantics by mentioning 'workbook migration' and 'target datasource,' which loosely relate to 'file_path' and 'target_source,' but does not explain 'scope' or 'mapping_overrides' or provide usage examples. It fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('preview a workbook migration') and the target ('onto a target datasource'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'apply_twb_migration' or 'migrate_twb_guided', which might handle actual migrations, so it lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'apply_twb_migration' for executing the migration or 'profile_twb_for_migration' for analysis. It also omits prerequisites, like needing a valid workbook file or target source, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'profile,' suggesting a read-only analysis, but doesn't clarify if it's safe, what permissions are needed, or if it modifies the workbook. It also lacks details on output format, error handling, or performance implications. The description adds some context ('before migration') but is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's front-loaded with the core purpose and avoids unnecessary details. Every word contributes to the tool's intent, making it appropriately sized for its content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, but with an output schema), the description is incomplete. It states the purpose but lacks parameter guidance and behavioral details. The presence of an output schema means the description doesn't need to explain return values, but it should still cover usage and parameters more thoroughly. It's minimally adequate but has clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The tool description doesn't mention any parameters, leaving all three parameters (file_path, scope, target_source) undocumented. It fails to compensate for the low schema coverage, offering no guidance on what these parameters mean or how to use them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Profile workbook datasources and worksheet scope before migration.' It specifies the verb ('profile'), resource ('workbook datasources and worksheet scope'), and context ('before migration'). However, it doesn't explicitly differentiate from sibling tools like 'analyze_twb', 'preview_twb_migration', or 'validate_workbook', which appear related to workbook analysis and migration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance by mentioning 'before migration,' implying it should be used as a preparatory step. However, it doesn't specify when to use this tool versus alternatives like 'analyze_twb' or 'preview_twb_migration,' nor does it outline prerequisites or exclusions. No explicit alternatives or detailed context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions that the tool 'recommends templates' and returns 'ranked template recommendations', which gives basic behavioral insight. However, it lacks details on what 'templates' entail (e.g., visualization templates, dashboard layouts), how recommendations are generated, performance characteristics, or any limitations. For a tool with no annotations, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured sections for Args and Returns. There's no wasted text, and each section serves a purpose. However, the formatting with separate sections could be slightly more integrated, but it remains efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters with 0% schema coverage and no annotations, but with an output schema present, the description is moderately complete. It covers the basic purpose, parameters, and return value, but lacks depth in behavioral context and parameter details. The output schema likely documents the return structure, so the description doesn't need to explain return values further. However, for a tool with no annotations and poor schema coverage, more elaboration on usage and parameters would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters with brief explanations: 'csv_path: Path to the CSV file', 'chart_types: Comma-separated chart types (optional)', and 'sample_rows: Rows to sample for inference'. This adds meaning beyond the schema's titles, but it's minimal—lacking details on format constraints, valid chart types, or sampling implications. With 3 parameters and no schema descriptions, this partial compensation is insufficient for full clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Recommend templates for a CSV file' with the specific verb 'recommend' and resource 'templates for a CSV file'. It distinguishes from siblings by specifying 'no active workbook needed', which differentiates it from workbook-related tools like 'create_workbook' or 'open_workbook'. However, it doesn't explicitly differentiate from the sibling tool 'recommend_template' (without '_for_csv'), which might handle different input types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context with 'no active workbook needed', suggesting this tool is for standalone CSV analysis rather than workbook operations. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'suggest_charts_for_csv' or 'recommend_template', nor does it mention prerequisites or exclusions. The guidance is present but limited to a single contextual note.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the action is to 'Add a trend line,' implying a mutation, but doesn't disclose behavioral traits such as permissions required, whether it modifies the worksheet in place, error conditions, or side effects. The description lacks context on what happens to existing trend lines or how the addition integrates with the worksheet.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and key details (trend line types). There is no wasted verbiage, and it directly communicates the essential information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage and no annotations, the description is incomplete—it only partially addresses one parameter ('fit'). However, an output schema exists, so return values needn't be explained. For a mutation tool with multiple parameters, more detail on usage and behavior would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions the types of trend lines (linear, polynomial, log, exp, power), which relates to the 'fit' parameter, but doesn't explain other parameters like 'worksheet_name', 'degree', 'show_confidence_bands', or 'exclude_color'. The description adds some value for 'fit' but leaves most parameters undocumented, resulting in a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add a trend line') and the target resource ('to a worksheet'), with specific mention of the types of trend lines available (linear, polynomial, log, exp, power). It distinguishes from siblings like 'add_reference_line' or 'add_reference_band' by specifying trend lines, but doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing worksheet with data), exclusions, or comparisons to similar tools like 'configure_chart' or 'add_reference_line' for related visualizations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool adds a worksheet but does not mention whether this is a mutation, requires specific permissions, affects existing worksheets, or has side effects like saving changes. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description does not need to explain return values. However, with no annotations, 1 parameter at 0% schema coverage, and complexity from sibling tools, the description is incomplete—it lacks behavioral details and usage context, making it only adequate for basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, but the description does not add any parameter semantics beyond implying a 'worksheet_name' is needed. It does not explain the parameter's role, constraints, or format, so it only meets the baseline for minimal compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Add a new blank worksheet') and the target resource ('to the workbook'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'create_workbook' or 'list_worksheets', which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'create_workbook' for initial workbook creation or 'list_worksheets' for viewing existing ones. It lacks context on prerequisites or exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool opens a workbook for editing, implying mutation, but doesn't specify permissions, side effects, or error handling. The mention of 'in-place worksheet editing' adds some context, but it's insufficient for a mutation tool, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description doesn't need to explain return values. However, as a mutation tool with no annotations and incomplete parameter guidance, it lacks details on behavioral aspects like permissions or side effects. The description is adequate but has clear gaps in context for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, but the description doesn't add any parameter details beyond what's implied by the tool name. It mentions 'workbook (.twb or .twbx)' which hints at the file type for 'file_path,' but doesn't explain format, constraints, or examples. With one parameter and low coverage, this provides minimal compensation, aligning with the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Open an existing workbook') and the resource type ('.twb or .twbx files'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'create_workbook' or 'save_workbook', which would be needed for a score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions 'for in-place worksheet editing,' which implies a context of editing, but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'create_workbook' or 'save_workbook,' nor does it specify prerequisites or exclusions. This lack of clear usage instructions limits its helpfulness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool performs a removal operation but doesn't disclose whether this is destructive, reversible, requires specific permissions, or has side effects. The description adds minimal context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values), no annotations, and a simple single parameter, the description is minimally adequate. However, for a mutation tool with 0% schema coverage, it should provide more behavioral context about the removal operation's effects and constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'field_name' implicitly ('calculated field') but doesn't explain what constitutes a valid field name, format requirements, or how to identify existing calculated fields. The description adds some meaning but doesn't fully compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('remove') and resource ('previously added calculated field'), providing a specific verb+resource combination. It distinguishes from siblings like 'add_calculated_field' by indicating removal rather than addition, though it doesn't explicitly mention other removal alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., that a calculated field must exist), exclusions, or contextual triggers, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool saves a file and explains the .twbx extension for packaging, which adds some context. However, it lacks critical details: whether this overwrites existing files, requires specific permissions, has side effects on the workbook state, or handles errors. For a mutation tool with zero annotation coverage, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with two sentences that efficiently convey the core action and an important detail about extensions. Every sentence adds value without redundancy, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which likely covers return values), the description doesn't need to explain outputs. However, as a mutation tool with no annotations and incomplete parameter guidance, it leaves gaps in behavioral context. It's adequate for basic understanding but lacks depth for 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.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter semantics beyond the input schema, which has 0% description coverage (only 'output_path' with no details). It doesn't explain what 'output_path' should include (e.g., file path format, extensions). With 1 parameter and low schema coverage, the description fails to compensate, but the baseline is 3 since it's a single parameter tool with minimal complexity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Save the workbook as a TWB file') and specifies the resource (workbook), making the purpose evident. It distinguishes from siblings like 'create_workbook' or 'open_workbook' by focusing on saving. However, it doesn't explicitly differentiate from all siblings (e.g., 'export_rules' might be vaguely similar), so it's not a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an open workbook), exclusions, or comparisons to other tools like 'validate_workbook' or 'analyze_twb'. Usage is implied but not explicitly stated, leaving gaps 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.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'List' but does not specify what the output includes (e.g., format, structure), whether it's a read-only operation, or any constraints like rate limits. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks details on behavioral aspects like output format or usage context, which could be helpful despite the structured data, making it only partially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description does not add parameter details, which is acceptable here as there are no parameters to explain, aligning with the baseline for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and the resource ('twilize's declared capability boundary'), making the purpose understandable. However, it does not explicitly differentiate this tool from its siblings like 'describe_capability' or other list tools, which slightly limits its clarity in context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'describe_capability' or other listing tools in the sibling set. It lacks context about prerequisites, timing, or exclusions, leaving usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'List' implies a read-only operation, it doesn't disclose important behavioral aspects like whether this returns all dashboards or is paginated, what format the output takes, or any authentication/rate limit considerations. The mention of 'worksheet zones' adds some context but is insufficient for a mutation-free tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place, with no redundant information or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (which handles return values) and no parameters, the description is reasonably complete for a simple list operation. However, as a read operation with no annotations, it should ideally mention output format or behavioral constraints to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the baseline is high. The description appropriately doesn't discuss parameters since none exist, and the 'in the current workbook' context provides useful semantic framing beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('dashboards and their worksheet zones'), with the scope 'in the current workbook' providing useful context. However, it doesn't explicitly differentiate from sibling tools like 'list_worksheets' or 'list_capabilities', which would require more specific comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (including other list operations), there's no indication of prerequisites, timing, or comparison to similar tools like 'list_worksheets' or 'list_capabilities'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it lists worksheet names, but doesn't mention any behavioral traits such as whether it's read-only, what format the output is in, if there are rate limits, or if it requires specific permissions. This leaves significant gaps for an agent to understand how to interact with it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that directly states the tool's function without any unnecessary words. It's front-loaded and efficiently communicates the essential information, making it easy for an agent to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is adequate for basic understanding. However, it lacks details on behavioral aspects (e.g., output format, error handling) and usage context, which could be important for an agent to operate correctly in a workflow with many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. This aligns with the baseline expectation for zero-parameter tools, where the description adds value by clarifying the action without redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and resource ('worksheet names in the current workbook'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_dashboards' or 'list_fields', which would require mentioning it's specifically for worksheets within a workbook context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance by implying it's for listing worksheets in a workbook, but it doesn't specify when to use this tool versus alternatives (e.g., 'list_dashboards' for dashboards) or any prerequisites like needing an open workbook. No explicit when/when-not instructions are included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('List all available fields') but does not describe output format, pagination, sorting, error conditions, or dependencies (e.g., requires a datasource to be loaded). This leaves significant gaps for an agent to understand how the tool behaves in practice.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any fluff. It is front-loaded with the core action and resource, making it easy to parse. Every word earns its place, adhering to ideal conciseness standards.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks context about behavioral aspects (e.g., what 'available fields' includes, error handling), which would help an agent use it correctly. The output schema mitigates some gaps, but the description could be more informative for a tool in a complex environment like workbook management.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's purpose. A baseline of 4 is applied as it avoids unnecessary details while being complete for a parameterless tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all available fields in the current workbook datasource'), making the purpose specific and unambiguous. It distinguishes itself from siblings like 'list_dashboards' or 'list_worksheets' by focusing on fields within a datasource, not other workbook components.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing an open workbook), exclusions, or related tools like 'profile_data_source' or 'inspect_target_schema' that might overlap in functionality. Usage is implied but not explicitly defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds some behavioral context by describing templates as 'user-editable YAML files' and listing components like 'layout zones' and 'suitability criteria', which helps understand the data structure. However, it lacks details on permissions, rate limits, or error handling, leaving gaps for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, with three short paragraphs that efficiently cover purpose, template details, and return format. Each sentence adds meaningful information without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, output schema exists), the description is reasonably complete. It explains the resource (templates), their format (YAML files), key attributes, and the return type. However, with no annotations, it could benefit from more behavioral details like data freshness or access constraints to fully compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately avoids discussing parameters, focusing instead on the tool's output and context. It adds value by explaining what templates are and what the listing includes, compensating for the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List all templates in the gallery with suitability rules.' It specifies the verb ('List'), resource ('templates in the gallery'), and scope ('with suitability rules'). However, it doesn't explicitly differentiate from sibling tools like 'list_dashboards' or 'list_worksheets' beyond the resource type, missing full sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It mentions what the tool does but offers no context about prerequisites, timing, or comparisons with sibling tools like 'recommend_template' or 'diff_template_gap'. This lack of usage context leaves the agent without clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'undo' and 'restoring previous workbook state,' which implies mutation reversal, but does not disclose behavioral traits like permissions needed, whether it's reversible itself, rate limits, or error conditions. This leaves significant gaps for a mutation-related tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that is front-loaded with the core action ('Undo the last mutating operation') and adds necessary detail ('restoring the previous workbook state'). There is zero waste or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete. It explains the purpose and effect, but as a mutation-related tool with no annotations, it could benefit from more behavioral context (e.g., limitations or side effects) to be fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description does not add param info beyond the schema, but with no params, a baseline of 4 is appropriate as it adequately addresses the lack of inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('undo') and the resource ('last mutating operation'), specifying it restores the previous workbook state. It distinguishes from siblings by focusing on reversal rather than creation, configuration, or analysis operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after a mutating operation but does not explicitly state when to use it versus alternatives (e.g., save_workbook or reset_rules). It provides some context but lacks explicit exclusions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool analyzes data shape and returns prioritized suggestions, which is useful. However, it doesn't mention behavioral traits like whether it's read-only (likely, but not stated), performance considerations (e.g., large file handling), or error conditions (e.g., invalid CSV). It adds some context but misses key 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded: the first sentence states the purpose, followed by analysis details, parameter explanations, and return value. Every sentence adds value without redundancy. It's appropriately sized for a tool with 4 parameters and complex functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (data analysis and suggestion generation), no annotations, and an output schema (which covers return values), the description is mostly complete. It explains what the tool does, parameters, and returns. However, it could improve by mentioning prerequisites (e.g., CSV format requirements) or limitations (e.g., supported chart types), slightly reducing completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides clear semantics for all parameters: 'csv_path' (path to CSV), 'max_charts' (maximum suggestions, with default behavior), 'sample_rows' (rows to sample), and 'rules_yaml' (YAML overrides). This adds meaningful context beyond the bare schema, though it could elaborate on format specifics (e.g., YAML structure).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Suggest chart types and configurations for a CSV file.' It specifies the action (suggest), resource (chart types/configurations), and target (CSV file). It distinguishes from siblings like 'configure_chart' (which configures existing charts) or 'csv_to_dashboard' (which creates dashboards) by focusing on analysis and suggestion rather than creation or configuration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a CSV file and want chart suggestions, but it doesn't explicitly state when to use this tool versus alternatives. For example, it doesn't compare to 'recommend_template_for_csv' (which suggests templates) or 'inspect_csv' (which profiles data). The context is clear but lacks explicit guidance on alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool saves to a file (a write operation) and includes runtime changes, adding useful behavioral context. However, it doesn't mention permissions needed, error handling, or whether the operation is idempotent, leaving 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections are structured but slightly verbose; every sentence earns its place by clarifying parameter behavior and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, 0% schema coverage, but an output schema exists, the description is fairly complete. It covers purpose, parameter details, and output summary. However, as a mutation tool (file write), it could better address safety or error scenarios to be fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It fully explains the single parameter 'output_path', including its purpose, default value ('./dashboard_rules.yaml'), and location context ('current working directory'). This adds significant meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Export') and resource ('current active rules'), specifying the output format ('YAML file'). It distinguishes from siblings like 'get_active_rules' (which likely retrieves but doesn't export) and 'reset_rules' (which modifies rather than exports).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage: exporting rules for future sessions or placement with data files. It mentions runtime changes from 'set_rule()', implying this tool captures dynamic state. However, it doesn't explicitly state when NOT to use it or name alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by detailing the multi-step pipeline behavior (schema inference, chart suggestion, etc.) and output format (.twbx). It mentions default behaviors for parameters but lacks details on error handling, performance, or system requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a purpose statement, pipeline overview, parameter details, and return info. It is appropriately sized but could be slightly more front-loaded; the pipeline details are useful but might be condensed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 8 parameters, 0% schema coverage, and no annotations, the description is quite complete—covering purpose, pipeline, parameters, and returns. The presence of an output schema reduces the need to detail return values, but more behavioral context (e.g., error cases) would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage, the description fully compensates by explaining all 8 parameters in the 'Args' section, providing clear semantics for each (e.g., 'max_charts: Maximum number of charts (0 = use rules default)'). This adds significant value beyond the basic schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Build a complete Tableau dashboard') and resources ('from a Hyper extract file'), including the end-to-end pipeline details. It distinguishes itself from sibling tools like 'csv_to_dashboard' or 'mssql_to_dashboard' by specifying the Hyper file input source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the pipeline explanation and parameter defaults, but does not explicitly state when to use this tool versus alternatives like 'csv_to_dashboard' or 'create_workbook'. No explicit exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses key behaviors: reading CSV files, inferring column types, classifying columns semantically, and returning a summary. However, it doesn't mention performance characteristics, file size limits, error handling, or whether the operation is read-only (though implied by 'inspect').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with purpose statement, parameter explanations, and return description. Every sentence earns its place, though the parameter section could be slightly more concise. It's appropriately sized for a tool with 3 parameters and complex functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (schema inference with classification), no annotations, but with output schema present, the description is reasonably complete. It explains what the tool does, all parameters, and the return format. Could benefit from more behavioral context about limitations or performance, but covers core functionality adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate fully. It provides clear semantic explanations for all three parameters: 'csv_path' as file path, 'sample_rows' for type inference sampling, and 'encoding' for file encoding with default value. This adds substantial value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('inspect', 'return') and resources ('CSV file', 'inferred schema with column classification'). It distinguishes from siblings like 'profile_csv' by focusing on schema inference rather than data profiling, and from 'csv_to_dashboard' by not creating outputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context for analyzing CSV structure before processing, but doesn't explicitly state when to use this versus alternatives like 'profile_csv' or 'inspect_hyper'. It provides clear prerequisites (CSV file path) but lacks explicit exclusions or comparison to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does describe what the tool does (reads Hyper file, maps types, classifies columns) and mentions a prerequisite dependency. However, it doesn't disclose important behavioral aspects like error handling, performance characteristics, file size limitations, or what happens with malformed files. The description adds some value but leaves significant gaps in behavioral understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with a clear purpose statement, provides implementation details in the middle, and ends with parameter and return value explanations. Every sentence earns its place by adding valuable information. The formatting with clear sections (Args, Returns) enhances readability without unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (file inspection with classification), no annotations, and the presence of an output schema, the description does a good job. It explains what the tool does, its parameters, and mentions the return format. The output schema existence means the description doesn't need to detail return structure. The main gap is lack of error/edge case handling information, but overall it's reasonably complete for the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for the lack of parameter documentation in the schema. It successfully explains both parameters: 'hyper_path' as 'Path to the .hyper file' and 'table_name' as 'Specific table to inspect (empty = first table)'. This provides clear semantic meaning beyond the bare schema. The only minor gap is not explaining path format expectations (absolute vs relative).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('inspect', 'read', 'map', 'classify', 'return') and resources ('Hyper extract file', 'schema with column classification'). It distinguishes itself from sibling tools like 'inspect_csv' by focusing specifically on Hyper files rather than CSV files, providing clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use this tool: for inspecting Hyper files to get schema information with column classification. It mentions a prerequisite ('Requires tableauhyperapi') which is helpful guidance. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools, though 'inspect_csv' is an obvious alternative for CSV files.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the multi-step pipeline and output format (.twbx), which adds useful context. However, it lacks details on permissions, error handling, or performance characteristics (e.g., time/complexity for large files), leaving gaps for a tool with significant functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by a concise pipeline overview and detailed parameter explanations. Every sentence earns its place by providing essential information without redundancy, making it efficient for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 7 parameters, no annotations, and an output schema, the description is largely complete. It covers the purpose, pipeline, parameters, and return summary. However, it could improve by addressing behavioral aspects like error cases or limitations, given the absence of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage, the description compensates fully by explaining all 7 parameters in detail. It provides clear semantics for each parameter, including defaults, options (e.g., theme presets), and examples (rules_yaml), adding significant value beyond the basic schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Build a complete Tableau dashboard') and resources ('from a CSV file'), including the end-to-end pipeline details. It distinguishes itself from sibling tools like 'csv_to_hyper' or 'create_workbook' by emphasizing the comprehensive dashboard creation process.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the pipeline explanation and parameter defaults, suggesting it's for automated dashboard generation from CSV data. However, it doesn't explicitly state when to use this tool versus alternatives like 'hyper_to_dashboard' or 'suggest_charts_for_csv', nor does it mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it describes an end-to-end pipeline, mentions external dependencies, notes that password is used only for schema inference, and specifies default values and output format. However, it lacks details on error handling or performance limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear overview followed by detailed sections for Args and Returns. It is appropriately sized for a complex tool, but the pipeline list could be more concise, and some parameter explanations are slightly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 13 parameters, no annotations, and an output schema, the description is largely complete: it explains the tool's purpose, pipeline, prerequisites, parameters, and return value. The output schema handles return details, but the description could better address error cases or limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage and 13 parameters, the description compensates by explaining most parameters in the 'Args' section, adding meaning like default behaviors and usage notes (e.g., username ignored if trusted_connection=True). It covers all required parameters and many optional ones, though some like theme and rules_yaml remain brief.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Build a Tableau dashboard') and resources ('from a Microsoft SQL Server table'), and it distinguishes itself from siblings like csv_to_dashboard and mysql_to_dashboard by specifying the MSSQL source. The pipeline overview adds detail without redundancy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (for building dashboards from MSSQL tables) and mentions prerequisites (pyodbc, ODBC Driver 17), but it does not explicitly state when not to use it or name specific alternatives among siblings, such as csv_to_dashboard for non-SQL sources.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the profile includes (dimension/measure classification, semantic types, etc.) and that it returns a 'Human-readable DataProfile with signals for template/chart decisions', which adds useful context. However, it lacks details on permissions, rate limits, or potential side effects, leaving some behavioral aspects unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose, followed by scope details, profile contents, and parameter/return explanations. Every sentence adds value without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (1 parameter, no annotations, but with an output schema), the description is complete enough. It explains the purpose, usage context, parameter semantics, and return value, and since an output schema exists, it doesn't need to detail return values further. This covers all necessary aspects for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful semantics for the single parameter 'source_type', explaining it's an override for source detection, with 'auto' as the default and other options like 'csv' or 'hyper' requiring separate tools. Since schema description coverage is 0% (the schema only provides a title and type), the description compensates well, though it could elaborate more on the implications of each option for a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('profile') and resources ('currently connected data source'), and distinguishes it from siblings by specifying it works for 'ANY connection type' and includes dimension/measure classification, semantic types, etc. This is distinct from tools like 'profile_csv' or 'profile_twb_for_migration' which are more specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool: 'Profile the currently connected data source' and 'Works for ANY connection type', implying it's a general profiling tool. However, it does not explicitly state when not to use it or name alternatives (e.g., 'profile_csv' for CSV-specific profiling), which prevents a score of 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and adds valuable behavioral context: it discloses the type inference mechanism, the dependency requirement (tableauhyperapi), and the output format (.hyper file for Tableau). However, it does not mention potential side effects like file overwriting or performance considerations for large files.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by implementation details, dependencies, parameter explanations, and return value—all in concise sentences that earn their place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (file conversion with type inference), no annotations, and an output schema that handles return values, the description is complete: it covers purpose, dependencies, all parameters, and the confirmation output, leaving no gaps for the agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It clearly explains the purpose of all four parameters (csv_path as source, hyper_path as output, table_name for internal naming, sample_rows for type inference), compensating fully for the schema's lack of documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Convert a CSV file to a Tableau Hyper extract'), the resource involved (CSV file to .hyper file), and distinguishes it from sibling tools like 'csv_to_dashboard' or 'hyper_to_dashboard' by focusing on file format conversion rather than dashboard creation or inspection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the mention of Tableau workbooks and type inference, but does not explicitly state when to use this tool versus alternatives like 'csv_to_dashboard' or 'inspect_csv'. It provides a prerequisite ('Requires tableauhyperapi') but lacks explicit guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the tool's purpose and basic operation but lacks details about permissions needed, file size limitations, performance characteristics, or error conditions. The description doesn't contradict any annotations (none exist), but could provide more 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured: purpose statement first, sibling differentiation second, parameter explanations third, return value fourth. Every sentence earns its place with zero wasted words, and information is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (returns 'Human-readable DataProfile'), the description doesn't need to explain return values. It covers purpose, differentiation, parameters, and output type adequately. For a 2-parameter tool with output schema, this is quite complete, though could mention any prerequisites or limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides clear semantic meaning for both parameters: 'csv_path: Path to the CSV file' and 'sample_rows: Number of rows to sample for type inference.' This adds significant value beyond the bare schema, though it doesn't specify format requirements or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Profile a CSV file') and resource ('CSV file'), distinguishing it from sibling tool 'profile_data_source' by explaining it works on raw CSV files without needing an active workbook. This provides excellent 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.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('profile a CSV file before connecting it') and provides a direct comparison to 'profile_data_source' with clear guidance on when to choose this alternative ('Unlike profile_data_source (which needs an active workbook), this tool profiles a raw CSV file directly').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it discards runtime changes and reloads defaults from a YAML file, indicating a destructive reset operation. However, it lacks details on permissions needed, potential side effects on other configurations, or error handling, which are important for a mutation tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core action in the first sentence, followed by clarifying details and return information. Every sentence earns its place: the first states the purpose, the second explains the process, and the third specifies the output. It is appropriately sized with zero waste, making it easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a mutation with no annotations) and the presence of an output schema (which covers return values), the description is mostly complete. It explains what the tool does, when to use it, and the source of defaults. However, it could improve by mentioning any prerequisites or side effects, but the output schema mitigates some gaps by handling return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately omits parameter details, focusing on the tool's action and outcome. A baseline of 4 is applied since no parameters exist, and the description adds value by explaining the reset process without redundant schema repetition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Reset') and resource ('all rules'), and distinguishes it from sibling tools by specifying it targets rules rather than other resources like dashboards, worksheets, or connections. It explicitly mentions discarding runtime changes from 'set_rule()', which is a sibling tool, reinforcing its distinct role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: to revert to built-in defaults and discard changes made via 'set_rule()'. It provides clear context by naming the alternative ('set_rule()') and specifying the action (discarding runtime changes), making it evident when this tool is appropriate versus other rule-related operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior, including the pipeline steps (schema inference, chart suggestion, etc.), data handling (password used only for schema inference, not stored), and output (.twb file). However, it lacks details on error handling, performance, or rate limits, which are important for a complex tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by details. Most sentences earn their place, but it could be slightly more concise by integrating the pipeline list into the initial sentence. Overall, it's efficient for a complex tool with many parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, 12 parameters, no annotations, and an output schema present, the description is complete enough. It covers the purpose, pipeline, prerequisites, parameter semantics, and return summary, leveraging the output schema for return values. No critical gaps remain for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema description coverage and 12 parameters, the description compensates fully by explaining each parameter's purpose and defaults (e.g., 'password used for schema inference only; not stored in the workbook', 'port default 3306', 'max_charts: 0 = use rules default'). This adds significant meaning beyond the bare schema, making parameter usage clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Build a Tableau dashboard from a MySQL table') and resources ('MySQL', 'Tableau dashboard'), distinguishing it from sibling tools like csv_to_dashboard or hyper_to_dashboard by specifying the MySQL source. It outlines an end-to-end pipeline, making the purpose explicit and distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool (e.g., for building dashboards from MySQL tables) and mentions prerequisites ('Requires mysql-connector-python for schema inference'), but it does not explicitly state when not to use it or name alternatives like mssql_to_dashboard for other data sources, leaving some guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it's a mutation tool (implied by 'Set'), requires admin privileges, has session-level persistence, can be exported via export_rules(), and returns confirmation or error messages. It doesn't mention rate limits or destructive consequences beyond the rule change.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured with clear sections (purpose, context, parameters, returns). Every sentence adds value, though the parameter documentation is quite detailed which is necessary given the schema coverage gap.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, mutation operation, no annotations) and 0% schema coverage, the description provides excellent completeness. It covers purpose, usage context, detailed parameter semantics, and behavioral traits. The presence of an output schema means the description doesn't need to explain return values in detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by providing comprehensive parameter documentation. It clearly explains all three parameters (section, key, value) with detailed options, examples, and formatting guidance that goes far beyond what the bare schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Set a specific rule value'), target resource ('active dashboard rules'), and user role ('admins'). It distinguishes from siblings by focusing on runtime rule modification rather than other dashboard operations like export_rules or reset_rules.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use this tool ('modify rules at runtime without editing YAML files') and mentions persistence behavior ('Changes persist for the current session'). It explicitly references the complementary export_rules() function but doesn't specify when NOT to use this tool or compare it to all alternatives like reset_rules.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It effectively discloses behavioral traits: it's a read-only operation (implied by 'Return'), describes its role in session initialization, and explains how rules affect other tools (validation with errors/warnings). It doesn't detail rate limits or auth needs, but covers core behavior well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by usage guidance and return details. Every sentence earns its place: the first states what it does, the second explains when to use it, the third provides context, and the fourth specifies the return format. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple read operation with 0 params), no annotations, but an output schema exists, the description is complete. It covers purpose, usage, behavioral context, and return format, making the output schema sufficient for details without redundancy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds value by explaining why no parameters are needed (it returns all active rules at session start), justifying a score above the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Return') and resource ('active dashboard creation rules'), distinguishing it from siblings like 'set_rule' or 'reset_rules'. It explicitly mentions what it returns and its role in understanding constraints.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does 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: 'Call this at the start of a session to understand what constraints are enforced.' It also mentions the context of rules engine validation for other tools like 'configure_chart' and 'add_dashboard', offering clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool evaluates templates against data profile and chart mix, returns a ranked list with reasoning, and uses a decider. However, it doesn't mention performance aspects (e.g., rate limits), error handling, or authentication needs, 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the core purpose, followed by usage guidelines and parameter details. It's appropriately sized, but the 'Args' and 'Returns' sections could be integrated more smoothly into the narrative flow, slightly affecting readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (evaluation and ranking tool), no annotations, and an output schema present, the description is complete enough. It covers purpose, usage timing, parameters, and return format, providing sufficient context for an agent to invoke it correctly without needing to explain return values redundantly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema, which has 0% description coverage. It explains both parameters: 'chart_types' as a comma-separated list with an example, and 'kpi_count' as an override derived from chart_types. This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Score all gallery templates and recommend the best fit.' It specifies the verb ('Score... and recommend'), resource ('gallery templates'), and outcome ('best fit'), distinguishing it from siblings like 'list_gallery_templates' (which just lists) or 'diff_template_gap' (which compares).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does 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: 'Call this AFTER profiling the data source and deciding on chart types, but BEFORE creating the dashboard layout.' It also distinguishes it from alternatives by specifying the decider's role, though it doesn't name specific sibling tools as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does so effectively. It discloses key behavioral traits: non-blocking/advisory nature, that deviations are normal due to Tableau Desktop practices, and that workbooks will likely open regardless of findings. It doesn't mention rate limits or authentication needs, but covers the essential operational context well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise. It begins with the core purpose, then provides crucial context about the check's advisory nature, followed by clear parameter and return value documentation. Every sentence earns its place with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (schema validation), lack of annotations, and presence of an output schema, the description is complete. It explains the tool's purpose, limitations, parameter usage, and return value nature. The output schema handles return format details, so the description appropriately focuses on operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides clear semantics for the single parameter: 'file_path: Path to a .twb or .twbx file to check. If omitted, checks the currently open workbook (in memory).' This explains the parameter's purpose, file types, and default behavior, adding significant value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run an informational XSD schema check on a workbook (2026.1 schema).' It specifies the exact action (schema check), resource (workbook), and schema version, distinguishing it from siblings like analyze_twb or profile_twb_for_migration which have different analytical purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does 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: 'This is a non-blocking, advisory check only.' It clarifies that Tableau Desktop is the true validator and deviations don't indicate broken workbooks, establishing clear boundaries for appropriate usage versus alternatives like actual validation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
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How to claim the server?
If you are the author of the server, you simply need to authenticate using GitHub.
However, if the MCP server belongs to an organization, you need to first add glama.json to the root of your repository.
{
"$schema": "https://glama.ai/mcp/schemas/server.json",
"maintainers": [
"your-github-username"
]
}Then, authenticate using GitHub.
Browse examples.
How to make a release?
A "release" on Glama is not the same as a GitHub release. To create a Glama release:
- Claim the server if you haven't already.
- Go to the Dockerfile admin page, configure the build spec, and click Deploy.
- Once the build test succeeds, click Make Release, enter a version, and publish.
This process allows Glama to run security checks on your server and enables users to deploy it.
How to add a LICENSE?
Please follow the instructions in the GitHub documentation.
Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear on the server after some time, you can manually trigger a new scan using the MCP server admin interface.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
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