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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but fails to describe key behavioral traits like whether this is a read-only operation, what specific metrics are returned, potential performance impacts, or any rate limits. 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.

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

The description is a single, clear sentence that efficiently conveys the core purpose without any wasted words. It is front-loaded and appropriately sized for a simple tool, making it easy for an agent to parse quickly.

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

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

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is minimally complete. It states what the tool does but lacks details on behavioral aspects and usage context, which are needed for a richer understanding. Without annotations or output schema, the description should do more to compensate, but it remains adequate for basic comprehension.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds no parameter information, which is appropriate here, but it doesn't compensate for any gaps since there are none. A baseline of 4 is given as it adequately handles the zero-parameter case without misleading or redundant details.

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

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('cache statistics and performance metrics'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'toggl_clear_cache' or 'toggl_warm_cache' which also relate to cache operations, missing an opportunity for sibling distinction.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention context such as monitoring cache health, troubleshooting performance issues, or comparing with other cache-related tools in the sibling list, leaving the agent to infer usage scenarios.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions verifying connectivity and authentication but lacks details on what 'valid' means, how errors are handled, or what the output might be (e.g., success/failure status). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, clear sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded and to the point, making it easy to parse quickly. Every part of the sentence earns its place by directly contributing to understanding the tool's function.

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

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

Given the lack of annotations and output schema, the description is incomplete for a tool that verifies critical aspects like API connectivity and authentication. It doesn't explain what happens upon success or failure, potential error messages, or any side effects. For a tool with no structured data to supplement it, this leaves too much ambiguity for effective use.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately avoids mentioning any. This meets the baseline for tools with no parameters, as it doesn't mislead or omit necessary information.

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

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

The description clearly states the tool's purpose: 'Verify Toggl API connectivity and authentication is valid'. It specifies the action (verify) and the target (Toggl API connectivity and authentication), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from siblings like 'toggl_warm_cache', which might also involve connectivity checks, so it falls short of a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as whether authentication must be set up first, or suggest scenarios like troubleshooting connectivity issues. Without this context, users might struggle to determine the appropriate time to invoke it among the 13 sibling tools.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Clear all cached data' implies a destructive operation that removes stored data, but it doesn't specify what types of data are affected, whether this requires authentication, potential performance impacts, or if the action is reversible. This leaves significant gaps for a tool that modifies system state.

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

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

The description is extremely concise at just three words ('Clear all cached data'), front-loading the essential action and target with zero wasted words. Every element earns its place, making it highly efficient.

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

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

For a destructive cache-clearing tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'cached data' encompasses, potential side effects, authentication requirements, or what happens after clearing (e.g., does it trigger re-caching?). Given the complexity of cache management and lack of structured data, more context is needed.

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

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

The tool has zero parameters, and the schema description coverage is 100% (though trivial since there are no parameters). The description doesn't need to explain any parameters, which is appropriate. A baseline of 4 is given for zero-parameter tools when the description doesn't attempt to explain non-existent parameters.

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

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

The description 'Clear all cached data' clearly states the action (clear) and target (all cached data), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'toggl_cache_stats' or 'toggl_warm_cache' that also relate to cache operations, so it doesn't reach the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, timing considerations, or how it relates to siblings like 'toggl_warm_cache' (which likely populates cache) or 'toggl_cache_stats' (which monitors cache).

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates a report but doesn't cover critical aspects like authentication requirements, rate limits, data freshness, or whether it's a read-only operation. For a reporting tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('Generate a daily report with hours by project and workspace') directly contributes to understanding the tool's function, making it highly concise and well-structured.

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

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

Given the tool's moderate complexity (generating a report with two parameters), 100% schema coverage, and no output schema, the description is minimally adequate. It states what the tool does but lacks details on output format beyond the 'format' parameter, behavioral traits, or differentiation from siblings. This leaves gaps in completeness for effective agent use.

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

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

The input schema has 100% description coverage, clearly documenting both parameters ('date' and 'format') with defaults and formats. The description doesn't add any parameter-specific details beyond what the schema provides, such as explaining the 'hours by project and workspace' output structure. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Generate a daily report with hours by project and workspace.' It specifies the verb ('generate'), resource ('daily report'), and key dimensions ('hours by project and workspace'). However, it doesn't explicitly differentiate from sibling tools like 'toggl_weekly_report' or 'toggl_project_summary,' which prevents 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.

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'toggl_weekly_report' for weekly data or 'toggl_project_summary' for project-specific summaries, nor does it specify prerequisites or exclusions. This lack of contextual direction leaves the agent without clear usage cues.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool retrieves a current entry 'if any', hinting at a possible null response, but doesn't cover other aspects like authentication needs, rate limits, error conditions, or what data is returned. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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

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

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core purpose ('Get the currently running time entry') and adds a clarifying condition ('if any'). Every part of the sentence contributes value, making it highly concise and well-structured.

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

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on return format, error handling, or integration with siblings like 'toggl_stop_timer'. For a tool that interacts with time-tracking data, more context on what 'currently running' entails would be helpful, though the low complexity keeps it from being severely incomplete.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is given since the schema fully covers the absence of parameters, and the description doesn't need to compensate.

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

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

The description clearly states the action ('Get') and resource ('currently running time entry'), making the purpose understandable. It distinguishes from siblings like 'toggl_get_time_entries' by specifying 'current' vs. general entries, though it doesn't explicitly name alternatives. The description avoids tautology by not just repeating the tool name.

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

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

The description implies usage when checking for an active timer, but provides no explicit guidance on when to use this tool versus alternatives like 'toggl_get_time_entries' or 'toggl_stop_timer'. It mentions 'if any' to indicate it may return nothing, which gives some context, but lacks clear when/when-not instructions or named alternatives.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that entries are 'hydrated' with project/workspace names, which adds some context about the return format. However, it lacks critical details such as whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or error handling. For a tool with 5 parameters and no annotations, this is a significant gap in transparency.

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

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

The description is highly concise and front-loaded, consisting of two clear sentences. The first sentence states the core functionality and filters, while the second explains the return format. There is no wasted language, and every sentence adds value, making it easy for an agent to parse quickly.

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

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

Given the complexity (5 parameters, no annotations, no output schema), the description is somewhat incomplete. It covers the basic purpose and return format but misses behavioral details like read-only nature, error cases, or pagination. Without an output schema, the description should ideally elaborate more on the return structure, but it does mention hydration, which helps. It's adequate for a simple retrieval tool but leaves gaps for robust agent usage.

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

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

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying date range filtering and hydration of results, but it doesn't explain parameter interactions (e.g., that 'period' might override 'start_date'/'end_date') or provide usage examples. Baseline 3 is appropriate since the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Get time entries with optional date range filters.' It specifies the verb ('Get') and resource ('time entries'), and mentions the return format ('hydrated entries with project/workspace names'). However, it doesn't explicitly differentiate from siblings like 'toggl_daily_report' or 'toggl_weekly_report', which might also retrieve time-related data, leaving some ambiguity about when to use this versus those alternatives.

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

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

The description provides no guidance on when to use this tool versus sibling tools. It mentions optional filters but doesn't specify contexts, prerequisites, or alternatives. For example, it doesn't compare to 'toggl_daily_report' or 'toggl_weekly_report', which might offer aggregated views, leaving the agent to infer usage based on parameter names alone.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't cover critical aspects like authentication requirements, rate limits, pagination, or error handling. This leaves significant gaps for an agent to understand how to use it safely and effectively.

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

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

The description is extremely concise at just four words, front-loaded with the core action and resource. Every word earns its place with no wasted text, making it easy to parse quickly.

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

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., list format, fields returned), authentication needs, or error conditions. For a tool that likely interacts with an external API, this leaves too many unknowns for reliable agent use.

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

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

The description doesn't add any parameter-specific information beyond what's in the schema, which has 100% coverage for the single parameter 'workspace_id'. The schema already describes it as optional with a default, so the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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

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

The description clearly states the action ('List') and resource ('clients for a workspace'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'toggl_list_workspaces' or 'toggl_list_projects' beyond specifying 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.

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., authentication), when not to use it, or how it compares to other listing tools like 'toggl_list_projects' or 'toggl_list_workspaces' in the sibling set.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states a read operation ('List'), implying it's likely safe and non-destructive, but doesn't specify permissions, rate limits, pagination, or return format. This leaves significant gaps for a tool that interacts with external data.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It is 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.

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like authentication needs, response structure, or error handling. For a data retrieval tool in a multi-tool server, more context is needed to ensure reliable use.

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

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

The schema description coverage is 100%, with the single parameter 'workspace_id' fully documented in the schema. The description adds no additional parameter details beyond implying workspace context, so it meets the baseline of 3 where the schema handles the heavy lifting.

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

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

The description clearly states the action ('List') and resource ('projects for a workspace'), making the purpose immediately understandable. It distinguishes from siblings like 'toggl_list_clients' or 'toggl_list_workspaces' by specifying 'projects'. However, it doesn't specify the scope (e.g., all projects vs. filtered), which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'toggl_project_summary' or 'toggl_workspace_summary'. It mentions a workspace context but doesn't clarify prerequisites, exclusions, or comparative use cases with sibling tools.

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

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

No annotations are provided, so the description carries full burden. 'List all available workspaces' implies a read-only operation but doesn't disclose behavioral traits like authentication requirements, rate limits, pagination, or whether it returns active/inactive workspaces. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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

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

The description is a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information without unnecessary elaboration.

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

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

Given the tool's simplicity (0 parameters, no output schema), the description is adequate but minimal. It states what the tool does but lacks context about authentication, workspace states, or relationship to sibling tools. For a read operation with no annotations, it should ideally mention authentication needs or data freshness, but it meets minimum viability.

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

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

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter semantics, and it correctly doesn't mention any parameters. Baseline 4 is appropriate for zero-parameter tools where the schema already covers everything.

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

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

The description clearly states the action ('List') and resource ('all available workspaces'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'toggl_workspace_summary' which might provide aggregated data versus a raw list, but the verb+resource combination is unambiguous.

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

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

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'toggl_workspace_summary' that might offer summarized workspace data, there's no indication of whether this tool is for raw listings, administrative purposes, or initial setup. No prerequisites or exclusions are mentioned.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get total hours'), implying a read-only operation, but doesn't clarify aspects like authentication requirements, rate limits, error handling, or the format of the returned data (e.g., whether it's a list, summary object, or includes pagination). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence: 'Get total hours per project for a date range.' It is front-loaded with the core purpose, has no redundant words, and every part earns its place by specifying the action, resource, and scope concisely.

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

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

Given the tool's complexity (4 parameters, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits (e.g., authentication needs, data format), usage guidelines compared to siblings, and output specifics. While the schema covers parameters well, the overall context for an AI agent to correctly invoke this tool is insufficient, especially without annotations or an output schema to clarify results.

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

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

The input schema has 100% description coverage, so the schema already documents all parameters ('period', 'start_date', 'end_date', 'workspace_id') with details like formats and enums. The description adds minimal value beyond the schema by implying date-range filtering but doesn't explain parameter interactions (e.g., that 'period' might override 'start_date'/'end_date') or provide usage examples. With high schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Get total hours per project for a date range.' It specifies the verb ('Get'), resource ('total hours per project'), and scope ('date range'). However, it doesn't explicitly distinguish this from sibling tools like 'toggl_daily_report' or 'toggl_weekly_report,' which also involve time reporting but with different aggregations or formats.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'toggl_daily_report' or 'toggl_workspace_summary,' which might offer similar time-tracking summaries but with different scopes or outputs. There's no indication of prerequisites, such as authentication or workspace selection, beyond what the parameters imply.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool starts a timer but doesn't mention what happens if a timer is already running, whether this requires authentication, or any side effects like cache updates. This leaves significant behavioral gaps for a mutation tool.

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

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

The description is a single, clear sentence with no wasted words. It's front-loaded with the essential 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.

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

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or behavioral constraints. Given the complexity of starting a timer (which may interact with other tools like 'toggl_get_current_entry'), more context is needed.

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

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

The schema has 100% description coverage, so all parameters are documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema, meeting the baseline expectation but not providing extra value.

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

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

The description clearly states the action ('Start') and resource ('a new time entry timer'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'toggl_stop_timer' or other time-related tools, which would be needed for a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'toggl_stop_timer' or 'toggl_get_current_entry'. There's no mention of prerequisites (e.g., authentication status) or typical use cases, leaving the agent to infer usage from context alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Stop') but doesn't describe what happens after stopping (e.g., does it save the entry, require confirmation, or have side effects like notifications). This is a significant gap 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.

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

The description is a single, direct sentence with zero waste—it states exactly what the tool does without unnecessary words. It's appropriately sized and front-loaded, making it highly efficient for quick understanding.

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

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

Given the tool's complexity (a mutation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral outcomes, error conditions, or what the tool returns, which are crucial for an agent to use it correctly in context with siblings.

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

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't mention parameters, aligning with the schema. A baseline of 4 is applied since the schema fully covers the absence of parameters.

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

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

The description clearly states the action ('Stop') and the target resource ('the currently running timer'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'toggl_get_current_entry' which might provide status information without stopping, though the verb 'stop' implies a distinct action.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., that a timer must be running), exclusions, or relationships with siblings like 'toggl_start_timer' or 'toggl_get_current_entry', leaving usage context unclear.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions caching for performance but lacks details on side effects (e.g., network usage, data freshness), permissions required, or error handling. This is inadequate for a tool that likely involves data fetching and storage operations.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand quickly.

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

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

Given the complexity of a caching tool with no annotations and no output schema, the description is insufficient. It doesn't explain what data is cached, how long it persists, performance implications, or return values, leaving significant gaps for agent understanding.

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

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

The input schema has 100% description coverage, with the parameter 'workspace_id' documented as 'Specific workspace to warm cache for.' The description adds no additional parameter semantics beyond this, so it meets the baseline for high schema coverage without compensating further.

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

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

The description clearly states the tool's purpose: 'Pre-fetch and cache workspace, project, and client data for better performance.' It specifies the action (pre-fetch and cache) and resources (workspace, project, client data), but doesn't explicitly differentiate from sibling tools like 'toggl_cache_stats' or 'toggl_clear_cache' that also involve cache operations.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, optimal timing, or compare it to sibling tools such as 'toggl_list_workspaces' or 'toggl_cache_stats', leaving the agent without context for selection.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates a report but doesn't cover critical aspects like whether it requires authentication, has rate limits, modifies data, or what the output looks like (e.g., format details beyond the schema). This leaves significant gaps for an AI agent to understand how to use it effectively.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly communicates what the tool does, making it easy to parse and understand quickly.

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

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

Given the complexity of a report-generation tool with no annotations and no output schema, the description is incomplete. It lacks details on authentication needs, output structure, error handling, or how it differs from siblings. This makes it inadequate for an AI agent to fully grasp the tool's behavior and usage context.

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

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

The schema description coverage is 100%, with clear descriptions for both parameters ('week_offset' and 'format'). The description adds no additional parameter semantics beyond what the schema provides, such as default behaviors or usage examples. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Generate a weekly report with daily breakdown and project summaries.' It specifies the verb ('generate') and resource ('weekly report') with details about content ('daily breakdown and project summaries'). However, it doesn't explicitly differentiate from sibling tools like 'toggl_daily_report' or 'toggl_project_summary' beyond the weekly scope.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'toggl_daily_report' for daily reports or 'toggl_project_summary' for project-focused summaries, nor does it specify prerequisites or contexts for usage.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it's a read operation ('Get'), but doesn't mention authentication needs, rate limits, error handling, or what the output format looks like (e.g., structured data vs. raw hours). This is a significant gap for a tool with potential API interactions.

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

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

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

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

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

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate but incomplete. It covers the basic purpose but lacks behavioral context and usage guidelines, which are important for an agent to operate effectively in a server with multiple time-tracking tools.

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

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

The schema description coverage is 100%, with clear descriptions for all parameters, so the baseline is 3. The description adds no additional parameter semantics beyond implying date-range usage, which is already covered in the schema. It doesn't clarify parameter interactions (e.g., using 'period' vs. 'start_date/end_date').

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

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

The description clearly states the verb 'Get' and resource 'total hours per workspace' with scope 'for a date range', making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'toggl_daily_report' or 'toggl_weekly_report' which might provide similar time-based summaries, so it doesn't reach the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'toggl_daily_report' or 'toggl_weekly_report' from the sibling list. It mentions a date range but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage context.

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