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. While 'Adiciona' implies a write/mutation operation, the description doesn't disclose any behavioral traits like whether this requires specific permissions, what happens on duplicate tasks, whether the operation is idempotent, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap.

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

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

The description is a single, efficient sentence in Portuguese that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded with the core functionality.

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

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

For a mutation tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what happens after adding a task, what the return value might be, or any error conditions. The description alone doesn't provide enough context for an agent to understand the full implications of using this 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 schema description coverage is 100%, with all 5 parameters well-documented in the schema itself. The description adds no parameter information beyond what's already in the schema, so it doesn't enhance parameter understanding. 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 action ('Adiciona' - adds) and resource ('uma nova tarefa à lista' - a new task to the list), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'todo_create', which appears to serve a similar purpose based on naming, leaving some ambiguity about differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'todo_create' or 'todo_list'. There's no mention of prerequisites, constraints, or appropriate contexts for this specific add operation versus other todo-related 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 the full burden of behavioral disclosure. It states the tool marks a task as completed, implying a mutation, but doesn't address permissions, side effects (e.g., if completion is reversible), error handling, or response format. 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.

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

The description is a single, efficient sentence in Portuguese ('Marca uma tarefa como concluída') that directly states the tool's purpose with zero waste. 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 this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits (e.g., what happens on success/failure), return values, or error conditions, which are critical 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 schema description coverage is 100%, with both parameters (listTitle and taskTitle) documented in the schema. The description doesn't add any meaning beyond what the schema provides (e.g., it doesn't explain how to identify the task or list). 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 'Marca uma tarefa como concluída' clearly states the action (marks as completed) and the resource (a task). It's specific about what the tool does, though it doesn't explicitly differentiate from sibling tools like todo_add or todo_create, which would require a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., the task must exist), exclusions, or comparisons to siblings like todo_list or todo_show, leaving the agent without contextual usage information.

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 new task list, implying a write operation, but lacks details on permissions required, whether creation is idempotent, error handling (e.g., if a list with the same title exists), or response format (since no output schema exists). For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence: 'Cria uma nova lista de tarefas.' It's front-loaded with the core action and resource, with no wasted words or redundant information. This makes it easy to parse quickly, though its 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.

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

Given the tool's complexity (a write operation with no annotations and no output schema), the description is incomplete. It doesn't address behavioral aspects like authentication needs, error conditions, or what happens on success (e.g., returns a list ID). With siblings like 'todo_list' and 'todo_show', more context on how this tool fits into the workflow is missing, leaving users under-informed.

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

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

The description doesn't add any parameter-specific information beyond what the input schema provides. The schema has 100% description coverage, with clear docs for 'title' and 'description', so the baseline is 3. The description doesn't explain parameter interactions (e.g., how title uniqueness is handled) or provide examples, but it doesn't need to compensate for schema gaps either.

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: 'Cria uma nova lista de tarefas' (Creates a new task list). It specifies the verb 'cria' (creates) and the resource 'lista de tarefas' (task list), making the action and target explicit. However, it doesn't differentiate from sibling tools like 'todo_add' (which likely adds items to an existing list) or 'todo_list' (which likely lists existing lists), leaving some ambiguity about when to choose this tool over others.

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., whether authentication is needed), exclusions (e.g., cannot create duplicate lists), or comparisons to siblings like 'todo_add' (for adding tasks) or 'todo_list' (for viewing lists). Without such context, users must infer usage from the tool name alone, which is insufficient for optimal selection.

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

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

No annotations are provided, so the description carries the full burden. It mentions listing but doesn't disclose behavioral traits such as pagination, sorting, authentication needs, rate limits, or what happens if no lists exist. 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 in Portuguese ('Lista todas as listas de tarefas'), which is appropriately sized and front-loaded. There's no wasted text, though it could be slightly more informative without losing conciseness.

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

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is incomplete. It lacks context on return values, error handling, or how it interacts with sibling tools, making it inadequate for full agent understanding despite the low complexity.

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 information is needed. The description doesn't add param semantics, but with no parameters, a baseline of 4 is appropriate as it doesn't need to compensate for gaps.

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 'Lista todas as listas de tarefas' (Lists all task lists) states a clear verb ('Lista') and resource ('listas de tarefas'), but it's vague about scope and doesn't differentiate from sibling tools like 'todo_show'. It provides a basic purpose but lacks specificity about what 'all' entails (e.g., user-specific vs. global).

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

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

No guidance is provided on when to use this tool versus alternatives like 'todo_show' or 'todo_create'. The description implies a listing function but doesn't specify contexts, prerequisites, 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.

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 shows details, implying a read-only operation, but doesn't confirm if it's safe (non-destructive), specify authentication needs, rate limits, or error handling (e.g., what happens if the list doesn't exist). 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 purpose without unnecessary words. It's appropriately sized for a simple tool, though it could be slightly more front-loaded by including key details upfront. There's no wasted text, earning a high score for conciseness.

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

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

Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It doesn't explain what 'detalhes' includes in the output, potential errors, or behavioral traits. While the schema covers the parameter, the lack of output schema means the description should ideally hint at return values, but it doesn't, leaving gaps for the agent.

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

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

The input schema has 100% description coverage, with the parameter 'listTitle' documented as 'Título da lista'. The description doesn't add any meaning beyond this, such as format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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

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

The description 'Mostra os detalhes de uma lista específica' clearly states the verb ('Mostra' - shows) and resource ('detalhes de uma lista específica' - details of a specific list), making the purpose understandable. It distinguishes from siblings like todo_add (adds items), todo_complete (marks items as done), todo_create (creates lists), and todo_list (lists all lists) by focusing on showing details of a single list. However, it doesn't specify what 'detalhes' includes (e.g., items, metadata), 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., that the list must exist), exclusions (e.g., not for editing), or comparisons to siblings like todo_list (which lists all lists) or todo_create (which creates new lists). This lack of contextual guidance leaves the agent to infer usage from the purpose alone.

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