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

With no annotations, the description carries the full behavioral burden and meets it well. It discloses weekend/holiday skipping, the non-business-day start rule for both positive and negative N, and the fact that only the holiday list varies by country while the weekend definition is fixed.

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 compact and front-loaded, with the core operation in the first sentence and necessary edge cases following. Every sentence adds relevant information about the calculation, with no filler.

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 date-addition utility, the description covers the calculation logic fully and states that it returns the resulting date. The only minor gap is that it does not explicitly say the output is a YYYY-MM-DD string, which is otherwise implied by the input schema.

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 100%, giving a baseline of 3, but the description adds real parameter meaning beyond the schema: the subtle rule for start_date when it is not a business day and the clarification that country affects only the holiday list, not the weekend. This goes beyond the generic schema descriptions.

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 a specific action and resource: 'Add N business days to a start date and return the resulting date,' with negative N explicitly allowed. This clearly distinguishes the tool from siblings like is_business_day or count_business_days, which perform different date 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 usage is implied by the verb 'Add N business days' and the description of edge-case behavior, but it never explicitly names sibling tools or states when to use this tool instead of count_business_days or is_business_day. It provides clear context about how the tool behaves, but no explicit when/when-not guidance.

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 behavioral burden. It does well by disclosing that both dates are inclusive, that the weekend is always Saturday+Sunday regardless of country, and that country only changes the holiday list. It could add edge-case behavior such as reversed date order, but the core semantics are transparent.

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?

Three tight sentences: core behavior first, then a practical use case, then a clarification of the most likely misinterpretation. Every sentence carries meaning and no information is wasted.

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 small deterministic counting tool, the definition is complete. The input schema covers formats and required fields, while the description explains the two potentially surprising aspects: inclusive bounds and weekend handling independent of country. The return value is implied by the verb 'count', and no output schema exists to reconcile.

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 100%, so the baseline is 3. The description adds value by reinforcing that both dates are inclusive and by clarifying that the country parameter affects only holidays, not the weekend definition. This supplements the schema and reduces the chance of misusing the country parameter.

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 a precise verb-resource pair: count business days between two inclusive dates, skipping weekends and Polish public holidays. It clearly differentiates from siblings like list_holidays, is_business_day, and add_business_days because it is the only counting tool in the group.

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?

It provides a concrete application context (enforcing '14-dni-roboczych' payment terms) that signals when counting business days is the right operation. However, it does not explicitly name sibling alternatives or state when not to use it, so it stops short of full routing guidance.

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 discloses the key behavioral trait that the weekend is fixed to Sat/Sun irrespective of the country parameter, and it warns about incorrect results for non-standard weekend countries. It also states the return structure (answer plus reason). This is transparent for a read-only check, though it does not mention any potential side effects or limitations beyond the weekend caveat.

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 two sentences with zero fluff. The first sentence states the purpose and return value, and the second delivers the critical caveat. It is front-loaded and easy to scan.

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 (2 params, no output schema), the description covers the essential context: it explains the return includes an answer and a reason (weekend/holiday/business_day), and it highlights the country-related pitfall. It could specify the exact format of the 'answer' (e.g., boolean) but that is minor. Overall, it is complete enough for an agent 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 schema already documents both parameters with 100% coverage, including the date format and the country's effect on holidays but not the weekend. The description repeats the weekend caveat that is already in the schema's country description, adding no new semantic meaning beyond what the schema provides. Thus 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 function: 'Check whether a date is a Polish business day — Monday–Friday and not a public holiday.' It specifies the verb (check), resource (date), and scope (Polish business day). It also differentiates from siblings like is_holiday by focusing on business-day status and mentions the return value (answer plus reason).

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 important usage context by warning that the weekend is always Saturday/Sunday regardless of country and that results are wrong for countries with different weekends. However, it does not explicitly state when to use this tool versus siblings like is_holiday or count_business_days, nor does it mention any exclusions or 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?

With no annotations, the description must disclose behavior. It states the return value (holiday details or null) and implies read-only operation. However, it does not clarify scope (e.g., only national holidays, or does the country parameter override the 'Poland' mention), nor does it mention potential edge cases like timezone or date format handling. Adequate for a simple check but with 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?

One sentence, front-loaded with the core purpose, zero waste. Efficient and to the point.

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 boolean-like check with two parameters, the description provides the essential return behavior. However, it lacks detail on the exact structure of 'holiday details' and does not clarify that the country parameter can be used to check other countries, which is important given the default. The absence of an output schema increases the need for this information, so it is not fully complete.

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 covers 100% of parameters with descriptions (date format and country code default). The tool description adds no additional meaning beyond the schema, so it meets the baseline of 3 without enhancement.

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?

States the specific action: checking whether a date is a public holiday in Poland, and specifies the return behavior (holiday details or null). Clearly distinguishes from siblings like list_holidays (which lists) and is_business_day (which checks business days) by naming the resource and condition.

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?

Provides no guidance on when to use this tool versus alternatives. Does not mention that is_business_day is for a different check, nor any exclusions. The only context is the tool name and the sibling list, but the description itself is silent on selection criteria.

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 the disclosure burden. It usefully reveals the returned item fields and the country default/ISO support, but it does not disclose edge cases such as invalid country handling, sorting, or possible variation in holiday types by country.

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?

Three concise sentences with the core action front-loaded, followed by useful output-shape and country-scope details. There is minor redundancy with the schema default, but no wasted words of consequence.

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 two-parameter list tool with no output schema, the description conveys enough to make a correct call: year is required, country is optional with a default, and returned items contain date and name fields. It could add return-format details like date type or sorting, but those are not essential for basic invocation.

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 baseline is 3. The description adds output-context but does not add new parameter semantics beyond what the schema already states; year is only documented as '4-digit year' in 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 states a specific verb ('List'), a clear resource ('public holidays'), and a scope ('in a given year'), and it previews the output fields. It does not explicitly contrast with siblings, but 'all ... in a given year' distinguishes it from single-date or next-holiday tools.

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 this tool is for full-year enumeration rather than single-date checks like is_holiday or next_holidays, but it never says when to prefer it or when to use an alternative. The guidance is inferred rather than explicit.

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 does not state whether the operation is read-only, what the output format looks like, how edge cases (e.g., no more holidays in the year) are handled, or whether the start date is inclusive. The description is minimal and lacks the behavioral detail needed for an agent to predict 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 two sentences with no fluff. The core function is front-loaded in the first sentence, and the use-case note in the second is optional but relevant. Every word earns its place.

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 read tool with 3 fully documented parameters and no output schema, the description covers the main intent but leaves important gaps: no mention of the returned structure, the inclusivity of from_date, or how count interacts with holidays remaining. It is adequate for a basic understanding but not fully complete for calling without further inference.

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 the parameters and their formats. The description echoes the count default ('default: next 5') and the source date ('from a given date'), adding no significant meaning beyond the schema. Baseline 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 verb ('Get'), the resource ('upcoming public holidays'), and the default count, which is specific. It does not explicitly distinguish itself from siblings like list_holidays, but the 'upcoming' qualifier and 'from a given date' imply its 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 phrase 'Handy for planning around long weekends' gives a use case but does not explicitly address when to use this tool versus alternatives like list_holidays or is_holiday. The intended usage is implied from 'upcoming' and 'from a given date', but no exclusions or sibling comparisons are given.

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