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 only states the tool adds an ingredient and returns a confirmation, but fails to disclose crucial behaviors like handling duplicates, case sensitivity, idempotency, or whether changes are persistent or scoped to a user/session.

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

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

The description is concise: a single sentence stating the action, followed by compact Args and Returns sections. It is front-loaded with the purpose. The structured format is slightly verbose but acceptable. No superfluous content.

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

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

For a simple tool with one parameter and no output schema, the description is minimally complete: it defines the action and parameter. However, it lacks details on how this tool fits into the broader workflow (e.g., effect on meal plan generation), duplicate handling, and relationship to the sibling 'get_ignored_ingredients'. More context would be beneficial.

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% coverage (no property descriptions), so the description must compensate. It adds the meaning that 'ingredient' is 'The name of the ingredient to ignore', which clarifies the parameter beyond the schema's bare title 'Ingredient'. However, it does not specify constraints like allowed characters, length, or uniqueness.

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: 'Add an ingredient to the ignored ingredients list.' It uses a specific verb ('Add') and resource ('ignored ingredients list'), distinguishing it from the sibling 'get_ignored_ingredients'.

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, such as 'get_ignored_ingredients' or other sibling tools. There is no mention of prerequisites, exclusions, or context for using this tool.

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

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

With no annotations, the description carries the full burden. It discloses a side effect (saving to a file) and states the return value. However, it omits details like file format, overwrite behavior, required permissions, or error handling. The disclosure is adequate but not thorough.

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

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

The description is concise, with a clear first sentence stating the core action, followed by an Args section and Returns section. The structure is logical and scannable. No redundant or unnecessary sentences.

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 (nested objects, file I/O), the description is missing details such as the file path/location, supported file format, and whether existing files are overwritten or appended. The return value is described, but there is no mention of validation, error states, or prerequisites. The description is functional but leaves gaps for a complete understanding.

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

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

The schema description coverage is 0% (per context), so the description must compensate. It lists the key fields of the meal_plan object (date, meal_type, title, cook, dishes), adding meaning beyond the raw schema. However, it does not explain nested structures (e.g., dishes are objects with their own fields) or data formats (e.g., date format). The schema's $defs partially fill the gap, but the description's contribution is moderate.

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 a meal plan entry') and the outcome ('save it to a file'). It distinguishes from sibling tools like store_dish (which stores a dish) and list_mealplans_by_date_range (which lists), making the tool's role 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?

No guidance on when to use this tool versus alternatives. For example, it does not mention that dishes should be stored first via store_dish before creating a meal plan, or that this tool is for a single entry vs. batch operations. The description lacks context for appropriate 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?

No annotations are provided, so the description must fully convey behavioral traits. It mentions the export action and returns a JSON string, but it does not disclose whether the tool has side effects (e.g., file creation location, overwrite behavior), authorization requirements, or whether it is read-only or destructive. The absence of these details leaves significant behavioral gaps.

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

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

The description is concise, with the main action in the first sentence. The Args and Returns sections are clearly delineated and add necessary detail without unnecessary verbosity. It is well-structured and front-loaded, though the Returns section could be slightly more compact.

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

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

Given the tool has one parameter with a nested object, no output schema, and no annotations, the description covers the parameter format and return structure adequately. However, it lacks details on behavior like file naming, location, error types, and potential side effects, making it minimally complete for an agent to use safely without further 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 input schema provides only a loose object type with no description of its keys. The description compensates fully by specifying the exact structure ('dictionary containing start and end dates'), the date format ('YYYY-MM-DD'), and which keys are required. This adds essential meaning beyond the schema.

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 ('Export'), the resource ('meal plans'), the format ('to a PDF file'), and the scope ('within a specified date range'). This distinguishes it from sibling tools like 'list_mealplans_by_date_range' which lists but does not export.

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 the tool is used when a PDF export of meal plans is needed, but it does not explicitly state when to use it versus alternatives (e.g., listing meal plans) or provide any explicit 'when not to use' or prerequisite conditions. The guidance is implicit rather than prescriptive.

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 must fully disclose behavioral traits. It only states that the tool generates a list and returns a path, but does not mention whether it is destructive (e.g., overwrites existing lists), requires authentication, or how it handles invalid date ranges or empty meal plans. This lack of detail is a significant gap for a non-trivial operation.

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

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

The description is structured as a docstring with clear sections (Args, Returns). It is front-loaded with the purpose, and the parameter explanation is concise. The Returns section is slightly redundant given no output schema, but it adds value. The overall length is appropriate and not verbose.

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 (nested parameter, no output schema, sibling tools implying a meal planning domain), the description is partially complete. It explains the return value as a dictionary with a path, which is adequate, but it does not describe the format of the generated grocery list, error behavior, or side effects. This leaves gaps for an agent to fully understand the tool's output and behavior.

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 coverage is 0% (the schema only defines date_range as an object with additionalProperties: true), so the description carries the burden. It adds meaningful semantics by specifying that date_range must contain 'start' and 'end' keys in YYYY-MM-DD format, and that start is required. This goes beyond the schema and is helpful for correct invocation.

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 grocery list for a specified date range.' It uses a specific verb ('generate') and resource ('grocery list') with a clear scope ('date range'). This effectively distinguishes it from sibling tools like add_ignored_ingredient or store_dish, which perform different actions.

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, such as needing an existing meal plan, nor does it exclude cases where the date range overlaps with other tools like export_mealplans_to_pdf. The agent is left to infer usage context from the tool name alone.

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

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

No annotations are present, so the description carries full burden. It discloses that the output is a sorted list of ingredient names, which is sufficient for a zero-parameter read operation. However, no details on authorization, side effects, or performance are provided, but these are not critical for this simple 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 extremely concise—two lines of core purpose and output—with no wasted words. Front-loaded with the action and resource, it is efficient 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 simplicity (zero parameters, no output schema), the description provides complete context: it retrieves the list, returns sorted names, and the sibling tool covers the addition side. No additional information is necessary.

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, so no parameter description is needed. The baseline score of 4 applies because the schema coverage is 100% and the description does not need to add meaning beyond the schema.

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 retrieves the list of ignored ingredients and specifies it returns a sorted list of names. The verb-resource combination is explicit, and the sibling tool 'add_ignored_ingredient' provides natural 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?

No explicit guidance on when to use this tool versus alternatives. The name and description imply its role as the read counterpart to 'add_ignored_ingredient', but no direct comparison or usage context is provided.

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

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

With no annotations provided, the description carries the full burden. It only states that the tool returns 'list of dish objects converted to dictionaries', but does not disclose behavioral traits such as whether it is read-only, if it filters results, pagination, error behavior, or authentication needs. This is insufficient for an agent to understand 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 very short at two lines, but it includes an unnecessary return format note that could be omitted if output schema exists. It is concise but under-specifies the tool; brevity here sacrifices clarity. It earns its place but could be improved with one more sentence of context.

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 (no parameters), the description lacks completeness. It does not specify what kind of dishes (e.g., saved, all available), whether there are filters, permissions, or output structure. With no output schema and no annotations, the agent has very little to understand the tool's full behavior.

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% because there are no parameters. The description does not need to explain parameters further, so it meets the baseline. However, it adds no value beyond the schema, which is acceptable given zero 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 states 'List all dishes' which is a clear verb+resource combination, but it does not distinguish this tool from siblings like 'store_dish' or 'list_mealplans_by_date_range'. The purpose is vague because it does not specify what 'dishes' entails (e.g., user-defined, predefined) or how it differs from similar list operations.

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

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

No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives like 'list_mealplans_by_date_range', nor any conditions or prerequisites. There is no guidance on context, alternatives, or exclusions.

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

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

No annotations are provided, so the description carries full behavioral burden. It does not disclose whether the operation is read-only, whether it requires authentication, whether results are paginated, or what happens with overlapping date ranges. The return format is detailed, but safety and side-effect information is missing.

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 well-structured with a clear summary followed by parameter details and return value format. It's a bit verbose in the return section but uses bullet points effectively. Could potentially shorten the return section by referring to a common object type.

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 schema provides only a bare object definition and no annotations, the description adds meaning for the single parameter and return value. However, it lacks behavioral context (authentication, performance, pagination) and is not fully complete for a production tool. The return value description is thorough.

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. It explains the 'date_range' parameter is a dictionary with required 'start' and 'end' keys in YYYY-MM-DD format. This adds critical meaning beyond the schema, which only defines it as an object with additionalProperties true.

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 lists meal plans within a specified date range, using a specific verb ('List') and resource ('meal plans'). The date range constraint is front and center, differentiating it from sibling tools like 'create_mealplan' or 'export_mealplans_to_pdf'.

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

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

The description provides clear context that this tool is for listing over a date range. While it doesn't explicitly mention when not to use it or alternatives, the date-range requirement is stated clearly. There are no sibling tools that also list meal plans, so differentiation is implicit.

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 must disclose behavioral traits. It mentions that the tool stores a dish and returns a confirmation with a path, but does not reveal whether the operation is idempotent, overwrites existing data, requires authentication, or has any side effects beyond storage. For a mutation tool, this is insufficient.

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

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

The description is concise at two sentences plus docstring-style Args/Returns. It front-loads the main purpose. The Args section repeats the parameter name but is acceptable. It could be slightly tighter by removing the docstring formatting, but it remains efficient and scannable.

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 free-form object parameter and no output schema, the description is too minimal. It does not explain what constitutes valid dish data, what the confirmation message contains, or any error conditions. An agent would likely need to guess or assume details, making the tool difficult to use correctly.

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

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

The only parameter 'dish_data' is described as 'Dictionary containing dish data', which adds no information beyond the schema's type and title. The schema has no description for the parameter, and the description does not specify expected keys, structure, or constraints (e.g., required fields). With 0% schema coverage, the description fails 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 verb 'store' and the resource 'dish', and mentions it returns a confirmation. However, it does not differentiate from the sibling tool 'list_dishes' beyond the verb, nor does it specify if this creates a new dish or updates an existing one. It is specific enough to avoid tautology but lacks scope details.

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 explicit guidance on when to use this tool versus alternatives like 'list_dishes' or 'create_mealplan'. The description only explains what it does, not when it is appropriate or when to avoid it. The existence of sibling tools for reading dishes and managing meal plans implies usage context, but no explicit direction is provided.

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