oeradio-mcp

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It adds context by stating that the calculation considers efficiency and depth of discharge, which goes beyond the tool name. However, it does not disclose the output unit (e.g., hours) or any underlying assumptions, leaving some behavioral gaps for a calculation 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 two concise sentences, front-loading the primary purpose in the first sentence and adding key considerations in the second. There is no redundant or irrelevant 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?

The tool has a well-documented input schema but no output schema and no annotations. The description adequately communicates the core purpose and factors considered, but it omits the output unit and any calculation assumptions. For a simple calculation tool, this is acceptable but not fully complete without explicit return value information.

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 has 100% parameter description coverage, so the baseline is 3. The description merely paraphrases the main parameters (capacity, consumption, efficiency, depth of discharge) without adding new semantic meaning or relationships beyond what the schema already provides.

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 a specific verb and resource: 'Berechnet die Akkulaufzeit' (calculates battery runtime), and specifies the key inputs (capacity, average consumption). This distinguishes the tool from sibling calculation tools like calculate_cable_loss or calculate_eirp, which target different quantities.

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 battery runtime calculations based on capacity and consumption, but provides no explicit when-to-use guidance, exclusions, or naming of alternatives. The context suggests this tool is for battery runtime estimation, but there is no explicit direction about when to choose it over other tools.

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 burden of disclosure. It indicates a calculation operation with no side effects, but it does not describe the output format (e.g., dB), limitations, or any assumptions about cable data. The constraints in the schema are not referenced in the description.

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, focused sentence in German that immediately states the tool's purpose. There is no verbose repetition or unnecessary detail, making it highly concise and well-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?

The tool has no output schema, so the description should explain the return value (e.g., total attenuation in dB), but it does not. It also lacks guidance on limits or validity, though the schema defines them. For a simple calculation tool, the missing output info is a notable gap.

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 covers 100% of parameters with descriptions, so the baseline is 3. The description only restates the concepts of cable type, frequency, and length without adding practical meaning, such as typical values or the meaning of the result. Thus, it adds no 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 calculates cable attenuation for various coaxial cable types at a given frequency and length, using a specific verb and resource. It distinguishes itself from sibling tools like calculate_wavelength or compare_cables by focusing on attenuation.

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 context is clear: it is for calculating cable loss based on frequency and length. However, it does not explicitly mention alternatives or exclusions, such as when to use compare_cables instead. The scenario is specific enough to guide usage without being fully 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description indicates a pure calculation with no side effects, but does not explicitly state that it is read-only, non-destructive, or that it returns a numeric result in a specific unit (e.g., watts). For a simple calculator, this is acceptable but not fully transparent about output format or limitations.

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, front-loaded with the core purpose immediately. Every word serves a function: the first sentence states the calculation, the second gives a use case. No redundancy or 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?

Given the absence of an output schema and annotations, the description should explain the return value and any relevant details. It mentions the use case (ÖNORM safety distance) but does not specify the output unit or format (e.g., result in watts or dBW). The tool is simple, but the description is somewhat incomplete for an agent that needs to know what to expect from the response.

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 minimal value by naming the parameters in natural language ('Sendeleistung, Kabelverlust und Antennengewinn'), but the schema already provides full descriptions for each parameter. The description does not add additional semantics beyond what the schema offers.

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: 'Berechnet EIRP (Equivalent Isotropically Radiated Power) aus Sendeleistung, Kabelverlust und Antennengewinn.' This specifies the verb (calculate), the resource (EIRP), and the inputs, distinguishing it from sibling calculation tools like calculate_cable_loss or calculate_swr_loss.

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 context for when to use the tool: 'Nützlich für Sicherheitsabstands-Berechnungen nach ÖNORM.' This implies the tool is appropriate for safety distance calculations, but does not explicitly exclude alternatives or name sibling tools. Clear use-case context is given, but no exclusions or alternative recommendations are 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?

There are no annotations, so the description carries full responsibility for behavioral disclosure. It only states the purpose without mentioning output format, units, or limitations. Even for a simple calculator, the lack of any detail on what the function returns or how it behaves with invalid input is a significant gap.

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, focused sentence that immediately states the tool's purpose. It contains no redundant information and is front-loaded with the core action.

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?

This is a simple one-parameter calculator, but the description is still somewhat incomplete. There is no output schema, and the description does not indicate what the calculated value represents (e.g., loss in dB or percentage). However, the clear schema and simple nature make this an adequate baseline, not a major deficiency.

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% (the 'swr' parameter has a description with example values). The tool description adds no extra parameter semantics. According to the rubric, with high schema coverage, the baseline is 3, and the description does not exceed that.

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 calculates power loss due to SWR/VSWR mismatch. It uses a specific verb ('Berechnet') and resource ('Leistungsverlust durch Fehlanpassung'), which distinguishes it from sibling tools like calculate_cable_loss and calculate_wavelength.

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 guidance is provided. The description does not mention when to use this tool instead of alternatives, nor does it give any contextual scenarios or exclusions. It only states the core function.

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 burden of behavioral disclosure. 'Berechnet' indicates a calculation, implying a read-only, side-effect-free operation. However, it does not disclose the output format, the use of physical constants, or clarify what 'optional Drahtlängen' actually means in terms of computation.

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 immediately conveys the core purpose. It is concise, but the optional 'Drahtlängen' part is ambiguous and could be clearer, slightly reducing the structural quality.

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 no output schema, so the description should at least indicate what the return value is (e.g., wavelength in meters). It does not specify output units or explain how the optional wire lengths are calculated. The ambiguous phrasing also leaves the user guessing about the full scope, making the description incomplete for a calculator 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?

The input schema already provides 100% coverage with descriptions for all three parameters. The tool description does not add meaningful parameter-level information beyond what the schema offers; it only vaguely references wire lengths, which is not clearly tied to the velocity_factor 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 clearly states the tool calculates wavelength for a given frequency, distinguishing it from sibling calculation tools like calculate_cable_loss or calculate_eirp. However, the phrase 'optional Drahtlängen für Antennen' introduces ambiguity about whether it also calculates physical wire lengths, preventing 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?

Usage is implied by the tool name and description: it should be used when converting frequency to wavelength. No explicit guidance is given about when not to use it or which alternative tools might be better for other calculation needs, such as cable loss or power conversion.

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 primary behavior (checking availability and showing per-state status) and implies a read-only operation through the verb 'prüft'. However, it does not explicitly mention side-effect-free behavior, error handling, or data sources.

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, front-loaded sentences that efficiently state the main purpose and the output. Every word earns its place, with no unnecessary jargon or repetition.

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 description adequately covers the function and the output (per-state free/occupied status). For a simple 2-parameter tool with no output schema, this is sufficient, though the exact response structure is not specified.

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% for both parameters (suffix and district), so the description does not need to add parameter details. The tool description mentions federal states, which corresponds to the district parameter, but adds no meaning beyond what the schema already provides.

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 uses the specific verb 'prüft' (checks) with the resource 'suffix in Österreich' and explicitly states the output 'zeigt in welchen Bundesländern das Rufzeichen frei oder belegt ist'. This clearly distinguishes it from sibling tools like callsign_lookup, callsign_validate, and callsign_suggest by focusing on availability across Austrian federal states.

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 use case is implied: when you need to check whether a suffix is available in Austria. However, the description does not reference any alternative tools or state when not to use this tool. No explicit exclusions or alternative suggestions are 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?

No annotations are provided, so the description carries the full burden. It implies a read-only operation via 'Zeigt Informationen' but does not disclose details like data freshness, required permissions, or response format. This is minimal but adequate for a simple info 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 a single, concise sentence in German that front-loads the purpose and specifies key output elements. There is no fluff or redundancy.

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 of the tool (no parameters, no annotations, no output schema), the description sufficiently covers the core function and the type of information returned. It could list exact statistics, but it is reasonably complete for a zero-parameter informational 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?

The tool has zero parameters, and the schema is empty with full coverage. With no parameters to describe, the baseline is 4 as per the rubric. The description does not need to compensate for parameter semantics.

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 shows database information (version, entry count, statistics), using a specific verb ('Zeigt') and resource. It distinguishes from sibling tools like callsign_lookup, which focus on individual callsigns.

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 sibling tools or exclusion conditions, leaving the agent to infer usage solely from the tool name.

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 multi-source lookup behavior (primary official list, fallback to QRZ.com/HamQTH), which is valuable. However, it doesn't describe what happens when a callsign is not found, response format, or any access limitations. The fallback disclosure adds some context, but the description is still minimal.

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 long, front-loaded with the action and resource, with no redundant wording. The second sentence adds relevant information about data sources. 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-only lookup tool with well-documented parameters, the description is complete enough. It states the purpose, output, and data sources. However, the lack of an output schema and no mention of not-found behavior means the agent doesn't know the exact response structure. Given the tool's simplicity, this is a minor gap, so a 4 is reasonable.

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 covers both parameters (callsign, include_address) with clear descriptions. The tool description itself does not add parameter-level details beyond what the schema already provides. With 100% schema description coverage, the baseline 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 uses a specific verb ('Sucht') and resource ('österreichisches Amateurfunkrufzeichen') and clearly states the outcome ('gibt Inhaberinformationen zurück'). It distinguishes itself from sibling tools like callsign_validate (format validation) or callsign_available (availability) by focusing on owner lookup.

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 clearly implies the tool is for looking up Austrian amateur radio callsigns and retrieving owner information. It provides context about data sources (official list with fallback to QRZ.com and HamQTH) but does not explicitly name alternatives or state when not to use it. Since the context is clear, a 4 is appropriate.

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 that the tool considers availability, phonetics, and CW-friendliness, which adds meaningful behavioral context. However, it does not mention whether results are based on live data, any limitations, or the nature of the return value. Since this is a non-destructive generation tool, the lack of detail is acceptable but not fully 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?

The description is two concise sentences. The first sentence front-loads the verb and resource, and the second sentence adds relevant criteria. No filler or redundancy.

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 5 parameters and no output schema. The description explains the core purpose and criteria, which is sufficient for a user to understand what the tool does. It could specify the return format (e.g., list of suggestions with scores), but overall it is adequately complete for a suggestion-generation 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?

The input schema has 100% description coverage for all 5 parameters, so the schema already provides detailed meaning for each field. The description adds general context about which factors are considered (availability, phonetics, CW-friendliness) but does not add specific parameter-level semantics 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 uses a specific verb 'Generiert' (generates) with a clear resource 'Wunschrufzeichen-Vorschläge' (desired call sign suggestions) based on name and preferences. It clearly distinguishes from sibling tools like callsign_available (availability check) and callsign_validate (validation) by focusing on suggestion 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 usage for generating call sign suggestions and mentions criteria (availability, phonetics, CW-friendliness), but it does not explicitly state when to use this tool versus alternatives or provide exclusions. The context is clear from the purpose, but explicit guidance is missing.

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 burden of transparency. It discloses the specific checks performed (format, district, suffix length), which is useful. However, it does not state what happens on validation success/failure, whether it is read-only, or what the return format is, 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 two short sentences, front-loaded with the main purpose, and contains no filler or redundant phrasing.

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 one-parameter tool without an output schema, the description explains the core function but omits details about the return value or validation outcome. This is a notable gap for a validation tool, so it is adequate but 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?

The schema covers the single 'callsign' parameter 100%, and the description does not add any new parameter semantics. Baseline 3 is appropriate since the schema already documents the 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 uses a specific verb 'Validiert' and resource 'Rufzeichen gegen österreichische Regeln', and lists the exact checks (Format, Bezirk, Suffix-Länge). This clearly distinguishes it from sibling tools like callsign_lookup or callsign_suggest.

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 makes it clear this tool is for validating callsigns under Austrian rules, which is the intended use case. However, it does not explicitly exclude alternatives like lookup or suggestion, nor does it state when not to use it, so it misses the top score.

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 states the core behavior (checking legality and returning the band) but does not disclose what happens when the frequency is not allowed (e.g., error vs. empty response), or whether any side effects occur. This is a notable gap for a validation 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?

A single, well-structured German sentence that immediately conveys the tool's function. It is front-loaded with the action and resource, with no superfluous words or repetition.

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 is relatively simple with only two parameters and no output schema. The description provides enough for a basic understanding, but leaves unspecified the behavior for invalid frequencies and the exact return format, which are important for an agent to use it correctly without seeing output examples.

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% with clear descriptions for both parameters ('Frequenz als Zahl' and 'Einheit der Frequenz'). The tool description adds no additional meaning beyond the schema, so it meets the baseline but does not elevate it.

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 uses a specific verb 'Prüft' (checks) with a clear resource: whether a frequency is allowed in amateur radio and returns the associated band. This clearly distinguishes it from sibling tools like get_band_plan or list_all_bands, which focus on band plans rather than single-frequency validation.

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: you would call this when you have a specific frequency and want to know if it's permitted and which band it falls into. However, it does not explicitly mention when to prefer this over alternatives such as get_band_plan or list_all_bands, nor does it provide exclusions or alternative tool 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 must disclose behavioral traits. It only states the action 'Vergleicht' without explaining what the output looks like, whether it returns a table, list, or comparison metrics, or if it has side effects. This leaves a significant transparency gap for a read-only comparison 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 a single, clear sentence that front-loads the main verb and resource. It is concise with no redundancy, efficiently conveying the essential purpose and conditions.

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 only 2 parameters and no output schema, so the description is moderately sufficient. However, it lacks details about the return format or how comparisons are presented, leaving room for ambiguity. For a simple tool, it is adequate but 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?

The schema covers 100% of parameters with descriptions (frequency_mhz and length_meters). The description merely restates these parameters in German ('Frequenz und Länge') without adding additional semantic details. The baseline of 3 is appropriate since schema does the heavy lifting.

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 uses a specific verb 'Vergleicht' (compares) and identifies the resource 'Kabeltypen' (cable types) with clear conditions (frequency and length). It distinguishes itself from sibling tools like calculate_cable_loss, which focuses on a single cable's loss, by explicitly stating it compares all available cable 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 clearly conveys the tool's purpose and implies when to use it (when comparing multiple cable types), but it does not explicitly mention alternatives or exclusions. Since it says 'alle verfügbaren Kabeltypen' (all available cable types), it's clear this is for comparative scenarios, yet no direct 'use this instead of X' guidance is 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the conversion action, implying a read-only calculation, but it does not disclose return format, handling of edge cases, or limitations. This adds some context but leaves significant behavioral details undocumented.

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 with no unnecessary words. It efficiently states the core purpose without any waste, making it highly concise.

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 description covers the basic function but lacks detail about the return value structure, which is not provided by an output schema. Since the tool has no annotations and no output schema, the missing information about what the conversion result looks like (e.g., all units or a single target) is a clear gap, though the tool's simplicity mitigates the impact.

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 already describes both parameters (value and from_unit) with descriptions and an enum for from_unit. The description does not add any additional meaning beyond the schema, so the baseline of 3 is appropriate given 100% 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 uses a specific verb ('rechnet um' / converts) and clearly specifies the resource (power values) and the units (Watt, dBm, dBW). This distinguishes it from sibling tools that handle other RF-related calculations like cable loss or EIRP.

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 for converting power units, but it does not explicitly state when to use it versus alternatives or when not to use it. No exclusions or alternative tools are mentioned, so usage is inferred rather than clearly guided.

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 the basic read-only lookup behavior ('returns typical gain values'), but does not mention output format, units, or error handling for invalid antenna types, leaving notable 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, front-loaded sentence with no redundancy or irrelevant details.

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 description covers the core purpose but lacks details about return structure, units, and behavior when antenna_type is omitted, despite these being partially present in the schema. No output schema adds extra burden to explain return values.

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 single parameter is fully described in the schema (antenna type, empty for all), and the description adds no additional parameter semantics. With schema coverage at 100%, 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 returns typical gain values for various antenna types, using a specific verb ('Gibt ... zurück') and a defined resource. It distinguishes itself from sibling tools focused on calculations, callsigns, and band plans.

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 when antenna gain values are needed, but provides no explicit guidance on when to choose this over alternatives, no exclusions, and no mention of related tools like calculate_eirp that might also involve gain.

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 discloses the return fields and the regional scope ('IARU Region 1 / Österreich'), which is useful behavioral context. The verb 'Gibt zurück' (returns) implies a read-only lookup, though it does not explicitly mention error handling or data source.

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 immediately communicates the tool's purpose and scope without any fluff. It is well-structured and front-loaded, with every word earning 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 one-parameter tool with no output schema, the description is sufficiently complete: it names the three key return elements (frequency limits, modes, max power) and specifies the regional standard. It could be more explicit about the data structure, but it is adequate for an agent to correctly invoke the 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 100%: the only parameter 'band' is fully described with examples ('20m', '2m', '70cm', '160m') in the schema. The description does not add additional parameter semantics beyond what the schema already provides, so the baseline 3 applies.

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 returns frequency limits, allowed modes, and maximum transmit power for an amateur radio band, with explicit scope to IARU Region 1 / Austria. This distinguishes it from sibling tools like list_all_bands (which lists bands) and check_frequency (which checks frequencies).

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 retrieving band plan details but does not explicitly state when to prefer it over alternatives or provide exclusions. The context of amateur radio bands is clear, but no direct comparison to sibling tools is 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 are provided, so the description carries the full burden. It implies a read-only list operation but does not clarify what 'basic information' includes, return format, or potential limitations. The behavior is mostly implicit.

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 concise single sentence in German with no redundant words. It is front-loaded with the main action 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?

For a simple zero-parameter list tool, the description provides a basic idea but leaves ambiguity about what 'basic information' entails and what the return structure looks like. Without an output schema, this vagueness makes the description only minimally 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?

The tool has zero parameters, and the schema trivially covers this. No parameter details are needed, and the description adds none, but the baseline for a no-parameter tool 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 lists all available amateur radio bands with basic information, using a specific verb ('listet') and resource ('Amateurfunkbänder'). It does not explicitly distinguish from sibling tools like get_band_plan, but the purpose is 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 is provided on when to use this tool versus alternatives such as get_band_plan or check_frequency. The description only states what the tool does, without specifying use cases, prerequisites, 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?

With no annotations provided, the description carries the burden. It discloses that the output includes URLs and descriptions, which is useful, but it does not mention the return format, whether results are sorted, or any side effects. For a read-only listing tool, the behavior is fairly predictable, but some behavioral details are 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 a single concise sentence that front-loads the primary action and result. No unnecessary words or filler; every word contributes to the purpose.

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 low complexity (one optional parameter, no output schema, no annotations), the description is mostly complete. It states what the tool returns (URLs and descriptions) and implies the filtering capability via schema. It could mention that the list is a discovery mechanism, but overall it adequately covers the essential 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 schema descriptions cover the only parameter (category) with a clear explanation of the enum values, so the schema provides full meaning. The tool description adds no additional semantic detail about the parameter, but none is needed given the 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 function: listing all available OERadio.at amateur radio tools with URLs and descriptions. It uses a specific verb ('listet') and resource ('verfügbaren OERadio.at Amateurfunk-Werkzeuge'), which distinguishes it from sibling tools that perform calculations or lookups.

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 discovering available tools, but it does not explicitly state when to use it versus alternatives, nor does it mention exclusions or context like 'use this to see what other tools exist.' The usage is inferable but not directly stated.

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