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 compares insurers but doesn't explain what the comparison entails (e.g., returns a list, a table, or a summary), whether it's read-only or has side effects, or any performance considerations like rate limits. For a tool with 5 parameters and no annotations, 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 German that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly. Every word earns its place by conveying essential information.

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 (5 required parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain the output format, error conditions, or how the comparison is performed. For a tool that likely returns detailed comparative data, more context is needed to guide effective use by an AI 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't clarify how parameters interact or affect the comparison). With high schema coverage, the baseline is 3, 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 'Vergleicht mehrere Versicherer für ein bestimmtes Profil' clearly states the action (compare) and resource (insurers) with a specific scope (for a given profile). It distinguishes from sibling tools like 'get_cheapest_insurers' (which likely returns cheapest options rather than comparisons) and 'get_price_history' (which focuses on historical data). However, it doesn't explicitly mention what aspects are compared (e.g., prices, coverage), keeping it from 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 like 'get_cheapest_insurers' or 'get_price_history'. It doesn't specify prerequisites, exclusions, or contextual cues for selection. The only implied usage is comparing insurers for a profile, but this is too vague 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.

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 the tool returns the 'Top 5' results, which adds some context about output behavior. However, it lacks critical details such as whether this is a read-only operation, potential rate limits, authentication requirements, error handling, or data freshness—important for a tool that queries insurance data.

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 and front-loaded with two clear sentences in German. It efficiently states the tool's purpose and output behavior without unnecessary words, though it could be slightly more structured by explicitly mentioning key parameters.

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 (6 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and output format ('Top 5'), but lacks details on behavioral traits, usage context, and error handling. With no annotations or output schema, more completeness would be beneficial for an AI 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, providing clear details for all 6 parameters (e.g., canton codes, age bands, franchise values). The description adds no additional parameter semantics beyond what the schema already documents, so it meets the baseline score of 3 for high schema 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 tool's purpose: 'Findet die günstigsten Krankenkassen für ein bestimmtes Profil. Gibt die Top 5 zurück.' (Finds the cheapest health insurers for a specific profile. Returns the top 5.) It specifies the verb ('findet'), resource ('Krankenkassen'), and scope ('Top 5'), but doesn't explicitly differentiate from sibling tools like 'compare_insurers' or 'get_price_history'.

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 'compare_insurers' or 'get_price_history'. It states what the tool does but offers no context about appropriate scenarios, prerequisites, or exclusions for its use.

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 statistics, implying a read-only operation, but doesn't clarify whether it requires authentication, has rate limits, returns real-time or cached data, or what format the output takes. For a tool with zero annotation coverage, this 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 a single, efficient sentence in German that directly states the tool's purpose and lists the statistics it provides. It's appropriately sized and front-loaded with the core functionality, with no wasted words or 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 tool's complexity (simple read operation with no parameters), no annotations, and no output schema, the description is minimally adequate. It specifies what statistics are returned, which helps compensate for the lack of output schema, but doesn't address behavioral aspects like authentication or data freshness. For a no-parameter tool, it's complete enough to understand the basic purpose.

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% (since there are no parameters to describe). With no parameters, the description doesn't need to add parameter semantics beyond what the schema provides. The baseline for 0 parameters is 4, as there's nothing to compensate for.

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: 'Zeigt Statistiken zur Datenbank' (shows database statistics) and specifies what statistics are included: 'Anzahl Einträge, verfügbare Jahre, Versicherer' (number of entries, available years, insurers). This is a specific verb+resource combination, though it doesn't explicitly differentiate from sibling tools like get_price_history which might also provide statistical data.

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 sibling tools like compare_insurers or get_cheapest_insurers, nor does it specify contexts where database statistics are needed versus other data retrieval operations. 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a read operation ('zeigt' - shows) which implies non-destructive behavior, but doesn't address other important aspects like authentication requirements, rate limits, error conditions, response format, or whether it returns historical data points or aggregated trends. For a tool with 6 parameters and no output schema, 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 a single, efficient sentence in German that directly states the tool's purpose without unnecessary words. It's appropriately sized for a straightforward data retrieval tool and front-loads 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 tool with 6 parameters, no annotations, and no output schema, the description is incomplete. While concise, it doesn't compensate for the lack of structured metadata by explaining what the tool returns (historical price points? percentage changes? annual premiums?), how results are formatted, or important behavioral constraints. The agent would need to guess about the output structure and operational characteristics.

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's already in the schema (which has 100% coverage). It mentions 'Versicherers' (insurer) which aligns with the 'insurer_name' parameter and 'mehrere Jahre' (several years) which relates to the temporal parameters, but provides no additional context about parameter relationships, constraints, or usage patterns. With complete 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 tool's purpose: 'Zeigt die Preisentwicklung eines Versicherers über mehrere Jahre' (Shows the price development of an insurer over several years). It specifies the verb 'zeigt' (shows) and resource 'Preisentwicklung' (price development) with temporal scope 'über mehrere Jahre' (over several years). However, it doesn't explicitly differentiate from sibling tools like 'compare_insurers' or 'get_cheapest_insurers' which might also involve price data.

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 sibling tools like 'compare_insurers' (for comparing multiple insurers) or 'get_cheapest_insurers' (for finding cheapest options), nor does it specify prerequisites or exclusions. Usage context is implied but not explicit.

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