normhyra

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

Annotations already indicate readOnlyHint and idempotentHint are true. The description adds that the tool returns values for three norm systems and includes an attribution field, providing some behavioral context beyond annotations, but lacks detail on side effects or permissions.

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 with clear structure. Could be slightly more concise, but no unnecessary 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?

Given no output schema, the description mentions return includes norm values and attribution, but does not specify the exact structure (e.g., object fields). For a calculation tool, this is adequate but not 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 coverage is 100%, so descriptions exist for all parameters. The description adds that correctionPoints defaults to 0 and apartmentTypeId comes from list_apartment_types, adding marginal value 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 converts normhyra to actual annual rent for a given apartment type, area, and correction points, specifying output includes values for three norm systems and an attribution field. This distinctively separates it from siblings like calculate_normhyra or list_apartment_types.

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 explicit guidance on when to use this tool versus alternatives, such as when to use calculate_normhyra instead. No exclusions or context for prioritization 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?

Annotations already indicate read-only and idempotent behavior. The description adds valuable context: the calculation is based on a reference apartment (3 rooms, 77 m²), and the response must include an attribution field. This goes beyond what annotations provide, disclosing important constraints for presentation.

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 concise sentences: the first covers purpose and output, the second covers attribution requirement. No extraneous information. Every sentence 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 no output schema, the description compensates by listing the return values (norm -78, -91, -12, RH numbers, attribution field). It is mostly complete, though the exact structure of the output (e.g., field names) is not detailed, which might require the agent to infer.

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 only minimal context about the reference apartment, which does not significantly enhance parameter understanding. The schema already describes the parameters adequately.

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: converting actual annual rent to norm rent (kr/m²/år) for a reference apartment (3 rooms, 77 m²). It specifies the output includes norm values for three years and RH numbers, and mentions an attribution requirement. This is a specific verb-resource pair that clearly distinguishes it from siblings like calculate_actual_rent.

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 explicitly state when to use this tool versus its alternatives (e.g., calculate_actual_rent). It implies usage for norm rent conversion, but fails to provide guidance on exclusions or when not to use it. The context is implicit but not actionable.

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?

Beyond annotations (readOnlyHint, idempotentHint), the description adds behavioral details: each apartment is recalculated to normhyra for three norms, a summary is returned, and the attribution field is always present. No contradictions with annotations.

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 paragraph that efficiently covers purpose, usage, output, attribution, and alternatives. It is front-loaded with the main action but could be slightly more structured.

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 rich schema (100% coverage) and annotations providing readOnly and idempotent hints, the description adequately explains the tool's functionality, output structure, usage constraints, and alternative tools for different needs.

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 100% schema description coverage, the baseline is 3. The description adds value by noting that correctionPoints defaults to 0 (not in schema) and emphasizing the max of 300 apartments per call (though schema includes maxItems). It also reiterates the yearlyRent/monthlyRent choice.

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 'Konvertera' (convert) and resource 'hyreslista' (rent roll), distinguishing it from siblings like 'calculate_normhyra' (single apartment) and 'export_rent_roll_pdf' (PDF output). The explicit mention of the sibling tool further clarifies its purpose.

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 advises when to use the tool (for multiple apartments in one call) and provides guidance on splitting large sets or using 'export_rent_roll_pdf'. However, it does not explicitly state when not to use it or compare to other sibling tools like 'calculate_normhyra'.

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?

The description adds value beyond annotations by specifying the output format (PDF layout, download link valid 7 days, attribution). It also mentions the behavior of including attribution in every response. Annotations provide readOnlyHint=false and destructiveHint=false, and the description does not contradict them.

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 the main purpose. It includes necessary details about layout, download link validity, and attribution without unnecessary fluff.

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 absence of an output schema, the description adequately explains the return value (download link, attribution) and some behavioral details. It covers most aspects an agent would need to know, though error handling is not mentioned.

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 schema already documents all parameters. The description does not add significant additional parameter semantics beyond what is 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 clearly states that the tool converts a rent roll to normalized rent and generates a PDF summary with a specific layout. It distinguishes itself from siblings like calculate_normhyra and calculate_rent_roll by explicitly mentioning PDF generation.

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 for obtaining a PDF export, but it doesn't explicitly state when to use this versus siblings or provide exclusions. Usage context is implied but not clearly differentiated.

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?

Annotations already declare readOnlyHint and idempotentHint, covering safety and idempotency. The description adds what fields are returned, but does not disclose other behavioral traits (e.g., whether the list is static or dynamic). Since annotations provide the core, the description adds moderate value.

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 in Swedish that efficiently conveys the tool's output with no wasted words. It is well-structured and front-loaded with the key action 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, the description fully explains what the tool returns (id, label, number of rooms, base points for three norms). The tool is simple with no parameters, and the description covers everything an agent needs to invoke it 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?

No parameters exist, so schema description coverage is effectively 100%. The description focuses on the return content, which is appropriate. Baseline for zero parameters is 4.

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 returns all apartment types supported by normhyra.ai, including specific fields (id, label, number of rooms, base points). This verb and resource combination is distinct from sibling tools that perform calculations or exports.

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 as a reference list, but no explicit when-to-use or when-not-to-use guidance is given. The sibling tools are all calculation-oriented, making the purpose clear, but the description lacks explicit context for alternatives.

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