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

No annotations provided, so the description must convey behavioral traits. It states what information is returned (legal framework, markup, etc.), implying a read-only operation. However, it does not explicitly confirm no side effects, authentication needs, or output format. This 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 a single sentence that efficiently conveys the tool's purpose and contents. It is front-loaded with the verb and resource. However, the list of contents could be better structured (e.g., bullet points) for readability. Overall, it is concise without excess.

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 simplicity (one parameter, no output schema), the description covers the return content well. It mentions key aspects of an EOR brief. However, it does not specify the output format (e.g., JSON, text) or any limitations. For a brief tool, this is mostly complete, but minor gaps remain.

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 should compensate. The description mentions 'country-specific' but does not add meaning to the 'country' parameter beyond the schema's enum list. It does not explain how the enum values map to countries or provide examples. The schema itself is clear, but the description offers no additional clarity.

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 a country-specific EOR brief with a specific list of contents. It distinguishes itself from siblings like get_full_eor_pack or get_eor_vs_entity_calc by focusing on a concise brief. The verb 'get' and resource 'country-specific EOR brief' are explicit.

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 siblings. While the description implies it is for a brief overview, it does not provide when-not-to-use or alternatives. Context from sibling names suggests distinctions, but the description does not articulate them.

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 only says 'battle-tested responses' but does not explain what the tool returns (e.g., text, structured advice, actions). There is no indication of side effects, required permissions, or any constraints beyond the single enum parameter.

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 consists of two short sentences that immediately convey the tool's purpose and the available options. There is no redundant information, and the key points are front-loaded.

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 1-parameter tool with no output schema or annotations, the description should clarify what the output looks like (e.g., a text response, a set of steps). It only mentions 'battle-tested responses' without specifying format or how the result aids the user, leaving the agent uncertain about the tool's deliverable.

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% description coverage, so the description must compensate. Although it lists the eight enum values, it does not explain what each objection type means or when to use each, adding minimal semantic value beyond the raw enum.

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 'Handle' and the resource 'EOR sales objections', and lists the eight specific objection types, making the tool's purpose unmistakable. It differentiates well from sibling tools, which focus on other EOR topics like country briefs or calculations.

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 does not provide any guidance on when to use this tool versus its siblings (e.g., when to pick this over get_eor_vs_entity_calc). There is no mention of prerequisites, context, or situations where the tool should not be used, leaving the AI agent without decision support.

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 exist, so the description bears full responsibility for behavioral disclosure. The description mentions 'live calculation' but does not explain what that entails (e.g., API calls, real-time data). It does not disclose mutability, safety, authentication needs, or side effects. This is insufficient for a tool with no annotation support.

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 ~30 words, front-loading the core purpose (live calculation). It uses a list for outputs, which is clear. However, it could be slightly more structured by separating input and output descriptions more explicitly.

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 output schema and annotations, the description partially compensates by listing return components (cost comparison, recommendation, etc.). However, it does not explain the country parameter, data sources, or calculation methodology. The three-input tool is adequately described for basic use but leaves gaps in 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?

Schema description coverage is 0%, so the description must add meaning. It mentions headcount and salary as inputs but does not explicitly list or explain the country parameter (though the tool name suggests it is used). It adds marginal value over the schema by linking parameters to the calculation, but fails to fully describe each parameter's role or constraints.

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: a live calculation comparing EOR and setting up a legal entity, given headcount and salary. It lists specific outputs (cost comparison, recommendation, break-even, pros/cons). This distinguishes it from sibling tools like get_country_eor_brief or get_full_eor_pack, which serve different purposes.

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 does not provide any guidance on when to use this tool versus alternatives. It mentions inputs but not prerequisites or scenarios where this tool is preferred over, for example, get_full_eor_pack. No when-not-to-use or alternative suggestions are given.

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 present. Description implies a read operation fetching a compilation, but does not disclose potential volume, cost, or any side effects beyond being informative.

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?

Two sentences: first states purpose and components, second gives usage context. No wasted words, front-loaded with essential info.

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?

No output schema exists. Description lists key components of the pack, providing enough context for an agent to understand return value. Could mention format or structure.

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?

Input schema has no parameters (0), so schema provides no meaning. Description adds value by specifying contents: 'all country briefs, misclassification risks, objection handlers.'

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?

Description clearly states it provides 'complete EOR intelligence pack' with enumerated components, distinguishing from sibling tools that offer individual pieces.

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?

Explicitly says 'For agent fine-tuning or full system context,' indicating when to use; lacks mention of when not to use but implies exhaustive retrieval.

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 lists return fields but does not explicitly state whether the tool is read-only or disclose any side effects, permissions, or costs.

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, front-loaded sentence that efficiently conveys the tool's function and key outputs with no wasted words.

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?

The tool has a simple input and no output schema; the description thoroughly enumerates all return fields (risk level, legal test, enforcement authority, etc.), providing complete context for what the tool returns.

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?

With 0% schema description coverage, the description partially compensates by explaining the tool's purpose and outputs, but does not describe the country parameter or its enum values 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 provides country-specific misclassification risk analysis and lists specific outputs (risk level, legal test, etc.), distinguishing it from sibling tools like get_country_eor_brief or get_eor_vs_entity_calc.

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 implicitly indicates the tool is for misclassification risk analysis, providing clear context. However, it does not explicitly state when to use it versus alternatives or exclude certain use cases.

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 provided; description states what the tool returns but does not disclose read-only nature, potential rate limits, or output format. For a simple lookup, it is minimally adequate but not rich in behavioral context.

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?

Single sentence with no wasted words. Lists relevant benefit examples succinctly. Front-loaded with purpose and scope.

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 no output schema and one simple parameter, the description is nearly complete. Could explicitly state return format (e.g., list of benefit names), but the examples hint at the output. High completeness for a low-complexity 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?

Schema coverage is 0%; however, the single parameter 'country' is an enum with clear values. The description mentions 'per country' but does not explain the parameter beyond that. Baseline 3 is appropriate given the enum clarity.

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?

Description clearly states the tool returns required statutory benefits per country, with specific examples (pension, health, etc.). It distinguishes well from siblings like get_termination_rules or get_visa_paths by focusing on benefits.

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?

Usage is implied (use when you need statutory benefits for a country), but there is no explicit guidance on when not to use, prerequisites, or alternatives. The tool is straightforward, but the description lacks contextual 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?

No annotations exist; the description indicates it returns country-specific rules but does not explicitly state read-only behavior, error handling, or if any side effects occur. It adds moderate behavioral context beyond the schema.

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?

Single sentence that is well-structured, front-loads key information, and contains no fluff. 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?

With a single parameter and no output schema, the description covers the main aspects of the tool. However, it could mention the return format or what the response includes, which would enhance completeness.

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% (no parameter descriptions), but the description compensates by explaining the purpose related to 'country-specific' rules. It does not add new meaning about the country parameter itself, just its role.

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 it provides 'country-specific termination rules' and enumerates key components (notice period, severance calculation, just-cause requirements, procedural pitfalls), making the tool's purpose explicit and distinct from sibling 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 the tool is used when termination rules are needed but does not explicitly state when to use it versus alternatives (e.g., for EOR or misclassification). No exclusion or comparison 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, the description carries full behavioral disclosure. It identifies the tool as a read operation that returns visa types, cost, timeline, and sponsorship requirements. However, it omits details like data source, recency, response format, or any limitations, leaving some 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 a single 12-word sentence that conveys the essential purpose and outputs without any extraneous text. It is well front-loaded and 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?

No output schema is provided, but the description lists key return elements (visa types, cost, timeline, sponsorship). For a tool with one parameter and a straightforward purpose, this is sufficiently complete, though it could specify the response structure more explicitly.

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% description coverage, and the description only says 'per country' without adding meaning to the country parameter. It does not explain the enum values, country-specific nuances, or how the parameter affects the output.

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 provides work visa/right-to-work paths per country, listing specific outputs like visa types, cost, timeline, sponsorship requirements. This verb+resource combination effectively distinguishes it from sibling tools (e.g., EOR, termination rules).

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 for hiring foreigners and obtaining visa info, but it does not explicitly state when to use this tool over alternatives like get_country_eor_brief. No when-not-to-use guidance or comparison is provided.

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