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 implies a calculation or read-only operation but doesn't specify if it's a simulation, requires external data, or has side effects like caching. For a tool with 5 parameters and no annotation coverage, 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 that front-loads the core purpose. It avoids unnecessary words, but could be slightly improved by structuring key details more clearly (e.g., separating parameters). Overall, it's appropriately concise for its content.

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 parameters with nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain the calculation logic, return format, or error handling, leaving gaps that could hinder an AI agent's ability to use the tool effectively in this Pokémon-related 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?

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It lists the parameters (level, IVs, EVs, nature) but doesn't explain their meanings, formats, or interactions (e.g., what IVs and EVs represent, valid nature values). This adds minimal semantic value beyond the schema's structure.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool calculates 'final stats' with specific components (level, IVs, EVs, nature), which clarifies the purpose beyond the name. However, it doesn't explicitly distinguish this from sibling tools like 'team_analysis' or 'suggest_moveset', which might also involve stat calculations, leaving some ambiguity about its unique role.

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. For example, it doesn't specify if this is for individual Pokémon stat calculation as opposed to broader team analysis or move suggestions, nor does it mention prerequisites like needing a Pokémon name. This leaves the agent without clear usage context.

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 full burden for behavioral disclosure. The description fails to indicate whether this is a read-only operation, what format the evolution chain data returns, whether there are rate limits, authentication needs, or error conditions. It provides no behavioral context beyond the vague purpose statement.

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 extremely concise (one phrase), but this brevity comes at the cost of clarity. While it's not verbose, it's under-specified rather than efficiently informative. The mixed language and lack of complete sentences make it feel incomplete rather than purposefully 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?

For a tool with no annotations, 0% schema coverage, no output schema, and 1 required parameter, the description is completely inadequate. It doesn't explain what the tool does clearly, how to use it, what the parameter means, or what to expect in return. The agent would struggle to use this tool correctly based on the provided 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 input schema has 1 parameter with 0% description coverage, and the tool description provides no information about the 'name' parameter. It doesn't explain what 'name' refers to (species name, Pokémon name, identifier format), what values are valid, or provide examples. The description fails to compensate for the complete lack of schema documentation.

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 'Cadena/grafo de evoluciones desde species->evolution_chain' is vague and mixes Spanish/English terms. It suggests retrieving evolution chains but doesn't clearly state the action verb or what resource it operates on. While it distinguishes from some siblings like 'get_pokemon' or 'type_matchup', it's not specific enough about what 'evolutions' means in this context.

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. The description doesn't mention prerequisites, when-not-to-use scenarios, or how it differs from sibling tools like 'get_pokemon' or 'search_names'. The agent must infer usage from the name alone.

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. However, it fails to describe any behavioral traits such as whether this is a read-only operation, what data is returned, potential rate limits, or error conditions. It provides no insight beyond the minimal name restatement.

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 extremely concise with a single phrase, but this brevity comes at the cost of under-specification rather than efficient communication. It's front-loaded but lacks substance, making it more of a placeholder than a helpful description.

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 of a 3-parameter tool with no annotations, no output schema, and 0% schema coverage, the description is completely inadequate. It doesn't explain what a 'learnset' is, how the parameters interact, what the output looks like, or any operational context, leaving critical gaps for the 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?

With 0% schema description coverage and 3 parameters (name, version_group, method), the description adds no meaning beyond what the input schema provides. It mentions 'version_group' and 'método' (method) but doesn't explain their purposes, valid values, or how they affect the learnset retrieval, failing to compensate for the lack of schema documentation.

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 'Learnset por version_group y método' is a tautology that essentially restates the tool name 'get_learnset' in Spanish, providing no additional clarity about what the tool actually does. It doesn't specify what resource is being retrieved (Pokémon learnset data) or what the verb 'get' entails, making it vague and minimally informative.

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?

There is no guidance on when to use this tool versus alternatives like 'get_pokemon', 'suggest_moveset', or 'validate_moveset' from the sibling list. The description offers no context about appropriate use cases, prerequisites, or exclusions, leaving the agent with no usage direction.

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 of behavioral disclosure. It mentions data retrieval from PokeAPI but doesn't specify traits like rate limits, error handling, authentication needs, or response format. This leaves gaps in understanding how the tool behaves operationally, though it correctly implies a read-only action.

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 very brief and front-loaded, stating the core purpose in a single sentence. It wastes no words, but the use of Spanish ('Ficha') and lack of structure might slightly hinder clarity for non-Spanish speakers. Overall, it's efficient but could be more polished.

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 (a data retrieval operation with one parameter), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover parameter details, behavioral traits, or output expectations, making it inadequate for an AI agent to use the tool effectively without additional 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 has 0% description coverage for the single parameter 'name', and the description adds no information about it. It doesn't explain what 'name' represents (e.g., Pokémon name, ID), valid formats, or examples. With low schema coverage, the description fails to compensate, leaving the parameter's meaning unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool retrieves a 'ficha' (sheet/card) with types, base stats, and abilities from PokeAPI, which indicates a read operation for Pokémon data. However, it's vague about the exact verb (e.g., 'fetch' or 'retrieve') and doesn't clearly differentiate from siblings like 'search_names' or 'get_evolutions', which might overlap in purpose. The Spanish term 'Ficha' adds some ambiguity.

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. It doesn't mention prerequisites, exclusions, or compare to siblings such as 'search_names' for broader queries or 'get_evolutions' for related data. The description implies usage for detailed Pokémon info but lacks explicit context for 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?

No annotations are provided, so the description carries full burden. It mentions 'substring' search behavior, which adds some context, but lacks details on rate limits, authentication needs, error handling, or what happens with no results. For a search tool with zero annotation coverage, 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 Spanish, front-loaded with the core purpose. It avoids unnecessary words, though it could be more structured for clarity.

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 annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on return values, error cases, and how it integrates with sibling tools, making it inadequate for a search tool in this 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?

Schema description coverage is 0%, so the description must compensate. It implies the 'query' parameter is used for substring searches, but doesn't explain format, constraints, or examples. With one undocumented parameter, the description adds minimal 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 states the tool performs a 'search' (verb) in PokeAPI for Pokémon and moves (resources), which is clear but vague. It mentions 'substring' as a search method, but doesn't specify what distinguishes this from sibling tools like 'get_pokemon' or 'suggest_moveset'.

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 alternatives is provided. The description implies substring matching, but doesn't clarify scenarios where this is preferred over exact-match tools or other search methods available in sibling 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'sugiere moveset' but does not explain how the suggestion is generated, whether it's based on algorithms or data, what the output format might be, or any constraints like rate limits or permissions. This is inadequate for a tool with no annotation coverage, leaving significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence in Spanish, making it concise and front-loaded. However, it could be more structured by clarifying key terms like 'STAB' and 'cobertura' for non-experts. Overall, it avoids unnecessary verbosity but lacks depth.

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 of moveset suggestion with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It does not explain the tool's logic, output expectations, or how parameters affect results. This is insufficient for effective tool invocation 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 0%, meaning parameters are undocumented in the schema. The description does not add any meaning to the parameters (name, version_group, role). It does not explain what 'name' refers to (e.g., Pokémon name), what 'version_group' options entail beyond the default, or how 'role' influences the moveset suggestion. This fails to compensate for the low coverage, providing minimal 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 states the tool 'sugiere moveset (STAB + cobertura) usando tipos de cada movimiento,' which translates to 'suggests moveset (STAB + coverage) using types of each move.' This provides a vague purpose: it suggests a moveset based on types, but it's unclear what 'STAB + cobertura' specifically entails or how it differs from sibling tools like 'validate_moveset' or 'get_learnset.' It does not clearly distinguish from siblings, making it somewhat ambiguous.

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 offers no guidance on when to use this tool versus alternatives. With sibling tools such as 'validate_moveset' and 'get_learnset,' there is no indication of context, prerequisites, or exclusions. This lack of guidance leaves the agent unsure about appropriate usage scenarios.

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 but provides almost none. It doesn't indicate whether this is a read-only operation, what data sources it uses (beyond mentioning PokeAPI), what format the output takes, or any error conditions. The Spanish description may confuse English-speaking agents about the tool's actual behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (one sentence in Spanish), but this brevity comes at the cost of clarity. While not verbose, the single sentence doesn't effectively communicate the tool's purpose to an English-speaking agent. The structure is simple but the language mismatch creates additional cognitive load.

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 no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It doesn't explain what defensive synergies means, how they're calculated, what the output format is, or provide any meaningful context for the single parameter. The language mismatch further reduces completeness for English-speaking agents.

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 and 1 parameter ('team' array of objects with 'name' property), the description provides no information about parameter semantics. It doesn't explain what constitutes a valid 'team', what the 'name' property should contain (Pokémon names? IDs?), or any constraints beyond the schema's min/max items. The description fails to compensate for the complete lack of schema documentation.

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 'Sinergias defensivas del equipo (usa tipos de PokeAPI y tabla de tipos)' states the tool analyzes defensive synergies using PokeAPI types and type tables, which gives a vague purpose. However, it's in Spanish while the tool name and context are in English, creating potential confusion. It doesn't clearly distinguish from siblings like 'type_matchup' or 'calc_stats' that might also involve type analysis.

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. With siblings like 'type_matchup' and 'calc_stats' that might handle similar type-related analyses, there's no indication of what makes this tool unique or when it should be selected over those options. No prerequisites or context for usage are mentioned.

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 tool calculates an offensive damage multiplier, implying a read-only operation, but doesn't specify if it's deterministic, requires authentication, has rate limits, or what the output format is. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose. It's appropriately sized and front-loaded with the key information. There's no wasted text, though it could benefit from more detail given the lack of annotations and schema coverage.

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 (2 parameters with 0% schema coverage, no annotations, no output schema), the description is incomplete. It doesn't explain parameter meanings, return values, or behavioral traits. For a tool that likely outputs numerical multipliers or type effectiveness, more context is needed to be fully usable by an 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 0%, so the description must compensate for undocumented parameters. It doesn't mention the 'attacking' and 'defending' parameters or explain their semantics (e.g., that 'attacking' is a single type string and 'defending' is an array of 1-2 type strings). No additional meaning beyond the schema is provided, failing to address the coverage gap.

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: 'Multiplicador de daño ofensivo' (offensive damage multiplier) using PokeAPI/type. It specifies a verb ('multiplicador') and resource ('daño ofensivo'), though it doesn't explicitly distinguish from siblings like 'calc_stats' or 'team_analysis' which might involve damage calculations. The Spanish phrasing is specific but not perfectly differentiated.

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. The description mentions using PokeAPI/type, but it doesn't indicate scenarios for choosing this over other type-related tools (if any) or siblings like 'calc_stats' for broader calculations. There's no mention of 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action (validate) but doesn't describe what validation entails (e.g., checks for move legality, compatibility, or errors), the response format, error handling, or any rate limits or authentication needs. This leaves significant gaps in understanding the tool's behavior beyond its basic purpose.

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 Spanish: 'Valida un moveset contra PokeAPI por version_group.' It's front-loaded with the core action and resource, with zero wasted words. Every part of the sentence contributes directly to the tool's purpose, 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?

Given the complexity (3 parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It doesn't explain the validation process, return values, or parameter details, leaving the agent with insufficient information to use the tool effectively. The conciseness comes at the cost of missing critical contextual details for a tool with multiple inputs.

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 compensate for undocumented parameters. It only mentions 'version_group' implicitly, without explaining 'name' or 'moves' parameters. The description adds minimal meaning beyond the schema, failing to clarify what 'name' refers to (e.g., Pokémon name) or the purpose of the 'moves' array, resulting in inadequate 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's purpose: 'Valida un moveset contra PokeAPI por version_group.' This translates to 'Validates a moveset against PokeAPI by version_group,' which is a specific verb (validate) applied to a resource (moveset) with a target (PokeAPI) and a scoping parameter (version_group). However, it doesn't explicitly differentiate from siblings like 'suggest_moveset' or 'team_analysis,' which might involve movesets in different ways, so it's not a perfect 5.

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 'suggest_moveset' or 'team_analysis,' nor does it specify prerequisites or exclusions. Usage is implied by the purpose but lacks explicit context, making it unclear how this validation differs from other moveset-related operations.

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