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 detects and analyzes, but doesn't explain what this entails—e.g., whether it's read-only, if it modifies files, what output to expect, or any side effects like logging or performance impacts. This is a significant gap for a tool with potential system 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 that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy to understand at a glance while being appropriately sized for its 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. It doesn't cover behavioral aspects like safety, output format, or error handling. For a tool that analyzes implementations, more context on what 'analyze' means and what results to expect would be necessary 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, with 'projectPath' clearly documented as 'Path to the project root.' The description doesn't add any parameter-specific details beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.

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

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

The description clearly states the tool's purpose: 'Detect and analyze existing auth.js/next-auth implementation.' It specifies the action (detect and analyze) and the target resource (auth.js/next-auth implementation). However, it doesn't explicitly differentiate from sibling tools like 'analyze_project' or 'monitor_auth_flows,' which might have overlapping scopes.

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, context for use, or exclusions. For example, it doesn't clarify if this is for initial setup, debugging, or migration scenarios compared to tools like 'setup_better_auth' or 'test_auth_flows.'

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 analyzing logs for issues but doesn't specify what the tool returns (e.g., error summaries, patterns), whether it's read-only or has side effects, or any operational constraints like rate limits or authentication needs. This leaves significant gaps in understanding the tool's behavior.

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

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

The description is a single, efficient sentence that states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for a basic tool, though it could be more informative without sacrificing conciseness.

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

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the analysis entails, what types of issues are detected, or the format of results. For a tool with one parameter but no structured output information, more context is needed to understand its full functionality and use cases.

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

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

The input schema has 100% description coverage, clearly documenting the 'timeRange' parameter. The description adds no additional meaning beyond the schema, such as examples of issues analyzed or how the time range affects results. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.

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

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

The description states the tool 'Analyze Better-Auth logs for issues', which provides a clear verb ('analyze') and resource ('Better-Auth logs'), but lacks specificity about what constitutes 'issues' or how the analysis is performed. It doesn't differentiate from siblings like 'analyze_current_auth' or 'monitor_auth_flows', leaving the scope vague.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'analyze_current_auth' or 'monitor_auth_flows'. The description implies usage for log analysis but offers no context about prerequisites, exclusions, or specific scenarios where this tool is preferred over others.

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 analysis and recommendation, implying a read-only, non-destructive operation, but fails to specify if it requires specific permissions, how recommendations are formatted, or any rate limits. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, with every part contributing 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 complexity of analyzing project dependencies and recommending setups, the description is incomplete. With no annotations, no output schema, and minimal behavioral details, it lacks information on what the analysis entails, the format of recommendations, or how results are returned. This makes it inadequate for guiding an agent in effectively using the tool.

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

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

The input schema has 100% description coverage, with 'projectPath' clearly documented as the path to the project root. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter documentation.

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

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

The description clearly states the tool's purpose: analyzing project structure and dependencies to recommend a Better-Auth setup approach. It specifies the verb 'analyze' and the resource 'project structure and dependencies', making it distinct from siblings like 'analyze_current_auth' or 'analyze_logs'. However, it doesn't explicitly differentiate itself from these siblings in terms of scope or output.

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, context, or exclusions, such as when to choose 'analyze_current_auth' for existing auth systems or 'setup_better_auth' for direct setup. This lack of comparative guidance leaves the agent without clear usage direction.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool creates a plan, implying a read-only or advisory operation, but doesn't clarify if it modifies files, requires specific permissions, has side effects, or details the output format (e.g., markdown, JSON). 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, efficient sentence that front-loads the core purpose without unnecessary details. Every word earns its place, making it highly concise and well-structured for quick understanding.

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

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

Given the tool's complexity (migration planning with 2 parameters) and lack of annotations/output schema, the description is minimally adequate but incomplete. It covers the basic purpose but misses behavioral details, usage context, and output expectations, leaving the agent to infer too much. A score of 3 reflects this as the minimum viable level.

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

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

Schema description coverage is 100%, so the schema already documents both parameters ('projectPath' and 'currentAuthType' with enum values). The description adds no additional meaning beyond what the schema provides, such as explaining how the path is used or what the auth types entail. 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 action ('Create step-by-step migration plan') and target resource ('from existing auth to Better-Auth'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'analyze_current_auth' or 'setup_better_auth', which might have overlapping migration-related functions.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., should 'analyze_current_auth' be run first?), exclusions, or how it relates to siblings like 'setup_better_auth' (which might handle implementation vs. planning). Usage is implied but not explicitly stated.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Real-time monitoring' but does not specify what this entails—e.g., whether it streams data, requires specific permissions, has rate limits, or what the output looks like. The description lacks details on behavioral traits beyond the basic action, leaving significant gaps for a monitoring tool.

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

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

The description is a single, efficient sentence: 'Real-time monitoring of authentication processes'. It is front-loaded and wastes no words, making it appropriately concise. However, it could be more structured by including key details, but it earns high marks for brevity without redundancy.

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

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

Given the complexity of monitoring authentication processes, the description is incomplete. With no annotations, no output schema, and only a basic purpose statement, it lacks essential details such as what the tool returns, how monitoring works, or any behavioral context. The schema covers the single parameter well, but overall, the description does not provide enough information 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 input schema has 100% description coverage, with the single parameter 'duration' documented as 'Monitoring duration (e.g. '1h', '30m')'. The description does not add any meaning beyond this schema, as it does not mention parameters or provide additional context. With high schema coverage, the baseline score is 3, reflecting adequate but no extra value from the description.

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

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

The description states the tool's purpose as 'Real-time monitoring of authentication processes', which is clear but vague. It specifies the verb ('monitoring') and resource ('authentication processes') but lacks specificity about what monitoring entails or what distinguishes it from siblings like 'analyze_current_auth' or 'test_auth_flows'. It does not restate the name/title tautologically, but it fails to differentiate from alternatives.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, exclusions, or prerequisites, nor does it refer to sibling tools like 'analyze_current_auth' or 'test_auth_flows'. Usage is implied only by the general purpose, with no explicit instructions or comparisons.

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 installation and configuration but fails to specify critical details like whether this modifies project files, requires specific permissions, or has side effects (e.g., overwriting existing auth setups). This leaves significant gaps for a tool that likely performs mutations.

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

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

The description is a single, efficient sentence that front-loads the core action and resource without any wasted words. It is appropriately sized for a straightforward tool, 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 complexity of installing and configuring an auth system, the description is incomplete. With no annotations and no output schema, it lacks details on behavioral traits (e.g., file modifications, error handling) and expected results. For a tool with nested parameters and likely significant side effects, this minimal description is insufficient.

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

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

Schema description coverage is 100%, so the schema already documents both parameters ('projectPath' and 'config') thoroughly. The description adds no additional meaning beyond implying that 'config' relates to Better-Auth setup, which the schema's property names and descriptions already convey adequately.

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

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

The description clearly states the action ('Install and configure') and the target resource ('Better-Auth in the project'), making the purpose immediately understandable. However, it does not differentiate from sibling tools like 'analyze_current_auth' or 'test_auth_flows', which focus on analysis/testing rather than installation/configuration.

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 'analyze_current_auth' for assessment or 'generate_migration_plan' for planning changes. It lacks context about prerequisites, such as whether the project must be initialized or if Better-Auth dependencies are needed.

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. 'Test authentication workflows' implies a read-only or diagnostic operation, but it doesn't specify whether it's safe, if it modifies data, requires permissions, has side effects, or details response behavior. For a 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 extremely concise with a single phrase, 'Test authentication workflows', which is front-loaded and wastes no words. It efficiently conveys the core idea without unnecessary elaboration, 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.

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

Given the complexity of authentication testing, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'test' entails, expected outcomes, or how results are returned. For a tool with one parameter but critical behavioral context needed, it falls short of providing sufficient information for effective use.

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

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

Schema description coverage is 100%, with the 'flows' parameter well-documented in the schema (including enum values). The description adds no additional meaning beyond the schema, such as explaining what 'test' does with these flows or their interactions. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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

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

The description 'Test authentication workflows' states a general purpose but lacks specificity. It identifies the action ('Test') and domain ('authentication workflows'), but doesn't clarify what 'test' entails (e.g., validation, simulation, verification) or distinguish it from sibling tools like 'monitor_auth_flows' or 'test_security'. It's vague about the scope and outcome.

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

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

No guidance is provided on when to use this tool versus alternatives. With siblings like 'monitor_auth_flows' (likely for ongoing observation) and 'test_security' (possibly broader security testing), the description offers no context, prerequisites, or exclusions. It leaves the agent to infer usage without explicit direction.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Run security tests' but does not explain what this entails—e.g., whether it's a read-only analysis, if it modifies settings, requires specific permissions, or has side effects like generating reports. This leaves critical behavioral traits unclear.

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

Is 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 and directly states the tool's action, making it easy to parse quickly 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 complexity of security testing, lack of annotations, no output schema, and low schema coverage, the description is incomplete. It does not cover what the tool returns, error conditions, or how results should be interpreted, leaving significant gaps for an AI agent to use it effectively.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'security tests' but does not detail the 'tests' parameter beyond what the schema's enum provides (e.g., what each test does or how to interpret results). This adds minimal semantic value, meeting the baseline for low coverage.

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

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

The description clearly states the verb 'Run' and the resource 'security tests on Better-Auth setup', making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'test_auth_flows' or 'analyze_current_auth', which might cover overlapping security aspects, so it misses full 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 does not mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the name alone, which is insufficient for effective tool selection.

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