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

No annotations are provided, so the description must fully disclose behavioral traits. It implies a read-only analysis operation but does not mention permissions, side effects, or what counts as a risk marker, leaving significant ambiguity.

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 one concise, front-loaded sentence that conveys the core purpose and a relevant special case. It contains no filler, though it could be slightly more structured to include usage guidance.

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 an analysis tool with no annotations and one under-documented parameter, the description leaves key gaps: parameter semantics, selection criteria versus siblings, and the meaning of risk markers. An output schema exists but is not shown, so the description still needs to provide more 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 only parameter, country, is not explained in the description, and schema description coverage is 0%. The parameter name and default 'player' provide a small hint, but accepted values and behavior when omitted are left 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 clearly states the tool's function: producing risk markers and actionable suggestions from save data, and even notes a specific case for Qing 1836. This is more specific than a tautology and broadly distinguishes it from data-lookup siblings, though it does not explicitly contrast with overview or country.

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 about when to use this tool instead of the many sibling tools such as overview or country. The description implies a strategic-analysis use case, but it never states explicit conditions 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, the description carries the burden of behavior disclosure. It signals a read-only aggregation and reveals the main result categories, but it does not explain scope (e.g., which country's buildings), ordering, or any side effects. The read-only nature is implied rather than explicit.

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 tool's purpose and contains no filler or redundancy. It is efficient, though slightly terse, matching its role as a short summary.

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 presence of an output schema reduces the need to describe return values, but with no annotations and zero parameter documentation, the description is incomplete. An agent is left without an understanding of how to use the two optional parameters or when this tool should be selected over related tools.

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% and the description never mentions top_n or country. Although the property names give some hint, 'top_n' is ambiguous without knowing what it ranks, and the 'player' default for country is unexplained. The description fails to compensate for the absent schema information.

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 identifies the resource ('buildings') and the operation ('summary'/汇总), and lists the output facets: level, profit, and loss-making buildings by type. It is clear enough about what the tool does, though it does not explicitly differentiate it from sibling tools such as overview or economy.

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 when-to-use guidance, no exclusions, and no mention of alternative sibling tools. An agent must infer the appropriate context entirely from the phrase 'building summary' without routing to or away from any specific sibling.

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 clearly indicates a read-only comparison operation and specifies what is compared, but it does not mention return format, behavior on invalid tags, or whether an active save is required. The output schema partially compensates for return-format details, but deeper behavioral context is absent.

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 states the core action and the parameter format with no filler. Every word contributes to the tool's operational meaning, making it highly 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?

Given the simplicity of the tool—one optional parameter with a schema default and a present output schema—the description covers the essential purpose and parameter format. Minor gaps such as prerequisites or error behavior are not critical for this low-complexity tool, so the definition is nearly 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 description coverage is 0%, so the description must compensate. It adds a clear semantic for the only parameter: tags are comma-separated labels. While it does not explicitly explain that tags are country identifiers, the default value 'CHI,GBR,RUS,FRA,USA,JAP' and the tool name make that inferable. This is sufficient for a single optional 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 states a specific verb ('对比' / compare) and a resource ('多个国家' / multiple countries), and lists the exact metrics compared: GDP, prestige, population, and technology count. This clearly differentiates it from the sibling 'country' tool, which would handle a single country, and from other metric-specific tools like 'economy' or 'technology'.

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 intended context—comparing multiple countries across several metrics—is implied by the description, and the parameter format 'tags 为逗号分隔标签' gives basic input guidance. However, it does not explicitly state when to prefer this tool over alternatives, such as using 'country' for a single-country analysis, nor does it mention any prerequisites like having a save loaded.

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 burden of explaining behavior. It does disclose what data the tool returns (economy, population, government, provinces), which is useful. However, it does not mention read-only status, response structure, or potential limitations, leaving some behavioral ambiguity.

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, compact sentence that immediately states the tool's purpose and key output contents. There is no wasted wording, and the most important information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with only one input parameter, the omission of any explanation of that parameter is a significant gap. The description covers the output scope but not how to specify the target country, which is essential for correct invocation. An output schema exists, but it does not compensate for unclear input semantics.

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 a single 'tag' parameter with 0% description coverage, and the description never explains what 'tag' means or how it selects the country. The default value 'player' is also unexplained, making it impossible for an agent to know what value to provide without external context.

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 provides a complete summary of a single country, enumerating key content areas (economy, population, government, province list). It implies distinction from sector-specific siblings like economy or politics, though it does not explicitly name them.

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 phrasing 'complete summary' implies the tool is for getting a broad, multi-aspect view of one country rather than sector-specific details. However, it does not explicitly state when to prefer this over alternatives such as overview or analyze_situation, nor does it give 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 reveals the topic scope (relations, pacts/hostility, war) but does not state whether the tool is read-only, how it handles missing or invalid countries, or what the output represents. The ambiguous phrasing leaves room for misinterpretation.

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 short and has no filler, which is superficially concise. However, it is an under-specified fragment that omits essential guidance about behavior and parameters, so the brevity is not achieved through good structure.

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 one optional parameter and an output schema, a minimal call is technically possible using defaults, but the description is not complete enough for reliable tool selection. It lacks usage context, alternative differentiation, and parameter semantics, forcing the agent to guess whether this returns a diplomatic summary or performs an action.

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 is responsible for explaining the country parameter. It never mentions country, its default value, or how the parameter selects the diplomatic view. The description adds no meaning beyond the bare schema fields.

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 identifies the resource (diplomacy) and lists content areas (relations, agreements/hostility, war), which gives some domain scope. However, it lacks a verb and never states what the tool actually does—show, summarize, or modify—so it remains a fragment rather than a clear purpose. It also does not distinguish itself from sibling tools like overview or analyze_situation.

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 such as country, overview, or analyze_situation. The only implied usage is 'diplomatic matters,' but no exclusions, prerequisites, or selection criteria 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 of disclosing behavior. It only lists content areas and does not state whether the tool is read-only, whether it mutates anything, or how the country parameter affects results. There is no contradiction with annotations because no annotations exist.

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 compact line with no filler, and the content areas are front-loaded. It earns its place by identifying the tool's scope, though it is terse enough that it omits important usage context.

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 one parameter and an output schema, the description is too thin to fully guide invocation: it does not explain what action the tool performs, how the country parameter works, or when to pick this tool among many economic/overview siblings. The output schema may clarify return shape, but selection and invocation remain underspecified.

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%, and the description never mentions the 'country' parameter or its default value of 'player'. It adds no meaning beyond the input schema's own field title and default, failing to compensate for the low 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 lists concrete economic areas—treasury, weekly income/expenditure, investment pool, and tax rates—making the tool's subject clear and distinguishing it from siblings like politics or military. However, it lacks an explicit action verb such as 'view' or 'get', so it stops short of 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?

There is no guidance on when to use this tool instead of siblings like overview, country, or rankings. It also does not mention when not to use it or any alternatives, leaving the agent to infer suitability 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. It only states what content is returned and does not explain whether this is a read-only operation, what 'activated' means, how entries are computed, or whether any context limitations apply.

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 short and contains no filler, but it is terse to the point of under-specification. It is concise as a noun phrase but does not provide enough structured information to be genuinely helpful.

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?

Although the tool is simple and an output schema exists, the description omits usage context, parameter semantics, and differentiation from sibling tools. An agent cannot determine when to invoke journal or how the 'country' default works, leaving important context missing.

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 sole parameter 'country' has 0% schema description coverage, and the description does not explain its meaning, accepted values, or default of 'player'. The phrase '该国' only loosely implies a connection to the country without any parameter-level detail.

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 identifies the resource (journal entries) and the scope (activated for the country), which is reasonably distinct from sibling tools like economy, politics, or military. However, it is a noun phrase rather than an explicit verb+resource statement such as 'Get the country's activated journal entries'.

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 journal versus siblings such as overview, analyze_situation, or country. No alternatives, prerequisites, or exclusions are mentioned, so an agent must infer the intended use case.

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 behavioral burden. It discloses that the tool lists countries and supports sorting by gdp, prestige, population, or tag. However, it does not mention read-only intent, limit handling, or any other behavioral nuance beyond listing and sorting.

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 plus a compact list of sort options. Every component carries useful information, and the core purpose is front-loaded. No filler or redundant wording exists.

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, optional-parameter list tool with an output schema and no required parameters, the description is largely sufficient. It documents the key sort options and the resource scope. Minor gaps include no explicit limit semantics and no usage alternatives, but these are partially covered by the schema defaults and the tool's simplicity.

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 adds meaning to the 'sort' parameter by enumerating valid values (gdp, prestige, population, tag), which the schema itself does not provide via enums. However, the 'limit' parameter is not described at all, leaving a 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 uses a specific verb and resource: '列出存档里的国家' ('list countries in the save'), and explicitly names the available sort keys. It clearly distinguishes itself from sibling tools like 'country' or 'compare_countries' by identifying its action as listing countries across the save.

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 such as 'country', 'compare_countries', or 'rankings'. It does not state exclusions, prerequisites, or when another sibling would be more 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 behavioral burden. It states that the tool lists local saves and identifies the source directory, which implies a read-only directory scan. However, it does not disclose details such as whether subdirectories are included, what file types are matched, or how results are ordered.

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 action and resource, with the path given in parentheses. Every part is useful and there is no 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?

For a simple zero-parameter list operation with an output schema available, this description is fully adequate. It tells the agent what is listed and where, and nothing else is needed to invoke the tool 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?

The tool has zero parameters, so there is minimal semantic burden. The description adds useful context beyond the empty input schema by specifying the exact path being scanned, which helps the agent understand the tool's scope.

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 (列出/list) and a clear resource (local Victoria 3 saves) and even provides the exact directory path. This clearly distinguishes it from sibling tools like load_save, which load rather than list.

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 intended use is clear: call this tool to enumerate local Victoria 3 saves from the standard save-games directory. It does not explicitly state when not to use it or mention alternatives such as load_save, but the context is unambiguous enough for a 0-parameter listing tool.

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 disclosing behavior. It says the tool 'melts and loads' a save but does not state whether loading replaces the current session state, requires a prior save listing, has side effects, or how invalid paths are handled.

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 compact sentence that places the core action first. It contains no filler, but the word '融化' is ambiguous and could confuse agents despite being short.

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?

Although an output schema exists, the description is too thin for a state-changing load operation in a tool suite with clear workflow siblings. It does not explain where loading fits in the workflow, what happens to the currently loaded save, or how this interacts with list_saves.

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 adds useful meaning for 'name' (save name or full path, with example), but 'lang' is left completely undocumented and its role is not mentioned anywhere.

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 names a specific verb ('load') and a specific resource ('.v3 save'), and explains what 'name' refers to with an example. However, '融化' is an unexplained metaphor, and the description does not explicitly distinguish this tool from siblings like list_saves or search_save.

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 given about when to use this tool versus alternatives, such as list_saves to find available saves or search_save to locate content. The only usage hint is how to specify 'name', which is parameter-level guidance rather than contextual usage 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?

With no annotations provided, the description carries the behavioral disclosure burden. It conveys that this is a query operation and explains the key format, but it does not mention behavior such as handling of unknown keys, locale nuances, or side effects. The presence of an output schema mitigates the need to explain return values.

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 states the action, the parameter meaning, and an example with no filler. Every word contributes to the agent's understanding and call construction.

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 lookup tool with an output schema, the description is largely complete: it gives the required input format and an example. Minor gaps remain, such as what the returned localized strings represent or how missing keys are handled, but the output schema likely covers return structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It fully defines the meaning of the only parameter 'keys' by specifying comma-separated loc keys and providing a concrete example ('CHI,law_serfdom,ig_landowners'), which goes well beyond the raw schema type of string.

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 a specific action and resource: '查询游戏本地化' (query game localization), and clarifies the input format with an example. It is clearly distinct from the sibling tools, which all concern save/state inspection rather than localization 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 intended use is implied: call it when you need game localization strings for given loc keys. However, the description does not explicitly state when to prefer it over alternatives or what conditions make it appropriate, though no sibling tool competes with this functionality.

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 carry the behavioral burden. It discloses no behavior, side effects, return characteristics, or whether this is a read-only informational lookup. '编制' is a static label and gives the agent no basis to predict how the tool behaves.

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 short, but this is under-specification rather than effective conciseness. It saves tokens at the cost of all actionable content, and no sentence earns its place because no real information is provided.

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?

Even though the tool has only one optional parameter and an output schema exists, the definition is too sparse to be complete. It does not explain what the military establishment output contains, how the country parameter affects it, or how this tool relates to the sibling detail tools.

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%, and the description does not mention the 'country' parameter or its 'player' default. The agent is left to infer parameter meaning entirely from the schema's property name and title, which is inadequate compensation for the missing description.

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 is a bare noun phrase, '陆军/海军编制' ('army/navy establishment'), which names a topic rather than an operation. It does not state what action the tool performs, such as retrieving, listing, or analyzing military organization, so an agent cannot tell what invoking it will do.

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 siblings like overview, analyze_situation, country, or other sector-specific tools. The description gives no context and names no alternatives or exclusion conditions.

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, yet it only lists returned fields and never states that the operation is read-only or what side effects, if any, it has. It adds useful content about the field set, but not enough about behavior, defaults, or guarantees.

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 with a clean colon and a comma-separated field list. It is front-loaded, concise, 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 one-parameter tool with an output schema, the field list is a decent starting point. However, usage guidelines and behavioral transparency are missing, so an agent cannot tell whether the call is safe, what country is targeted by default, or when to prefer a sibling 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 description coverage is 0% and the description never mentions the 'country' parameter or its 'player' default. Only the word '国家' hints at the parameter's subject, so the description does little to compensate for the schema 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 names the resource (country) and enumerates the exact fields returned: date, rank, GDP, prestige, living standard, population, treasury, and great powers. It lacks an explicit verb, but 'overview' plus the field list clearly conveys a read-only summary, and the aggregated scope distinguishes it from specialized siblings like economy or politics.

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 given on when to use this tool versus alternatives such as country, economy, rankings, or analyze_situation. The intended niche as a high-level summary is implied by the name and field list, but no exclusions, prerequisites, or alternative routing 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?

With no annotations, the description carries the full burden of disclosing behavior, but it is only a noun phrase listing topics. It does not state that the tool returns data, whether it is read-only, or how the country parameter affects results, so behavioral transparency is limited to topic scope.

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 short and contains no fluff, with the topical terms front-loaded. However, it is a sentence fragment with no verb or structural context, so it is more under-specified than properly 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 tool is simple, but the description only identifies the general subject matter. It does not explain the action, the role of the optional country parameter, or how the result relates to the player context, so an agent cannot fully determine correct invocation from the description alone.

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%, and the description does not mention the country parameter at all. The parameter name and default 'player' offer some self-evident meaning, but the description adds no clarification about accepted values, formats, or what 'player' refers to.

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 lists concrete content areas (interest groups, bills, institutions, rulers/heirs), so an agent can infer this is a politics information look-up tool and distinguish it from economy, military, or other sibling domains. However, it lacks an explicit verb like 'get' or 'list,' leaving the action implied rather than stated.

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 domain label and content list imply that this tool should be used when political information is needed, but the description gives no explicit guidance about when to prefer it over siblings like country, analyze_situation, or journal. There are no alternative recommendations or exclusion conditions.

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 does not explicitly state whether this is a read-only query, what side effects exist, what the default 'player' context means, or how data is returned. The described content hints at a read operation but does not disclose 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 compact phrase that lists the exact data categories covered, with no filler or redundancy. It is well-suited for quick scanning, though being only a fragment it leaves other dimensions underspecified.

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 simple with one optional parameter and an output schema, so the description need not detail return values. However, it lacks usage guidance, parameter explanation, and explicit behavioral caveats, making it only a minimally complete description for an agent to select and call the tool 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?

Schema description coverage is 0%, and the description does not mention the 'country' parameter at all. The parameter name and default value are self-explanatory to some degree, but the description adds no meaning and fails to explain the special default 'player', leaving a significant compensation 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 identifies the resource as population structure and lists specific dimensions (class, occupation, culture, unemployment, living standards), which distinguishes it from adjacent tools like economy or politics. Although it lacks an explicit verb, the noun phrase is informative and not tautological.

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 statement about when to use this tool versus any sibling tool, nor any exclusion or alternative mention. The content description implies a demographic lookup, but the agent receives no explicit routing guidance or prerequisites.

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 and only discloses the subject matter (prestige order and country tiers), not how the ranking is computed, whether it reflects the current save, or what granularity the tiers have. The output schema presumably covers the return structure, which softens the 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?

One short sentence, no filler, and the key term '威望排行' is front-loaded. Every word contributes to the meaning.

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 zero-parameter read-only listing tool with an output schema, the description is nearly complete: it names the content and the category of result. It could be more complete by noting which save/context it applies to, but the simplicity keeps the gap small.

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, so the schema already fully covers inputs and the baseline is 4. The description adds no parameter details, which is acceptable because there is nothing to configure.

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 identifies the resource: prestige rankings and country tiers (列强/大国等), which is enough to distinguish it from generic list/overview siblings. It lacks an explicit verb, relying on the noun 'rankings,' but the intent 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?

The use case is implied: an agent looking for a prestige leaderboard or country-classification view would select this tool. However, there is no explicit when-to-use guidance, no mention of alternatives such as overview, list_countries, or compare_countries, and no 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 burden of behavioral disclosure. It communicates that the search operates on melted save text and targets raw fields, which is core behavior. However, it does not clarify match semantics, whether it searches field names or values, or any limits beyond the schema default.

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 front-loads the key scoping ('melted save text', 'raw fields') and the intended use cases. Every part adds value and there is no 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?

For a simple 2-parameter tool with an output schema, the description covers the core purpose and typical usage context. However, with no annotations and no parameter-level description, the agent still lacks some detail about query behavior and hit limits.

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 needed to compensate. It implicitly suggests that query is a search term for raw fields, but it never mentions max_hits or clarifies query syntax/format. This leaves parameter semantics mostly undocumented.

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 a specific verb and resource: searching raw/original fields within the melted save text, with explicit use cases (debugging/looking up obscure data). It does not explicitly contrast with sibling tools, but 'raw fields' clearly distinguishes it from higher-level analysis tools like overview or analyze_situation.

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 parenthetical '(调试/查冷门数据)' provides clear context for when this tool is appropriate: low-level debugging or uncommon data lookups. It does not explicitly name alternatives or state when not to use it, so it falls short of a 5.

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?

Since annotations are absent, the description carries the behavioral disclosure burden. It usefully states the output categories, but it does not disclose default-country behavior, whether the operation is read-only, or any other behavioral traits beyond the listed fields.

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 compact sentence with no filler, and the main purpose is front-loaded. It is terse but every word contributes to indicating what the tool returns.

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 lookup with an output schema present, the description is minimally viable: it names the resource and key output fields. However, without annotations or parameter semantics, it leaves notable gaps around default behavior, accepted country identifiers, and how this tool relates to siblings.

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%, and the only parameter is 'country' with a default of 'player'. The description refers obliquely to '该国' but never explains acceptable country values or that omitting the parameter selects the player country, leaving the parameter semantics mostly to inference.

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 identifies the resource (the country's provinces) and enumerates the returned fields: name, integration, infrastructure, and population. This makes the tool's purpose understandable and distinguishes it from siblings like list_countries or country, although no explicit verb is used.

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 gives no guidance on when to use this tool versus alternatives such as country, overview, or list_countries, and it does not mention exclusions or prerequisites. The intended usage is only implied by '该国省份'.

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 carry the full burden of behavioral disclosure. '已研究科技。' only expresses a vague state of having researched technology; it does not state whether the tool mutates state, reads data, requires permissions, or what side effects may occur.

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 short, but this is under-specification rather than conciseness. A single opaque sentence does not front-load any useful information and spends its only words on a vague restatement of the tool name.

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?

Although an output schema exists, the overall definition remains incomplete: the purpose is unclear, the single parameter is undocumented, and there is no differentiation from at least eighteen sibling tools. An agent cannot reliably infer what data will be returned or how to invoke this tool 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?

Schema description coverage is 0%, and the description does not mention the 'country' parameter or its default value of 'player'. The agent receives no explanation of how the parameter affects the result, which is especially important since the parameter is optional and unnamed in the description.

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 '已研究科技。' is essentially a tautological restatement of the tool name 'technology' and offers no clear verb or resource. It does not distinguish this tool from its many siblings, and it is unclear whether it returns researched technologies, triggers research, or displays a tech tree.

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 about when to use this tool versus alternatives such as 'country', 'analyze_situation', or 'overview'. The description provides no context, prerequisites, or exclusions, leaving the agent without any basis for selecting it.

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