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. It only states 'Fetch accumulation/distribution line', which implies a read-only operation but doesn't cover critical aspects like rate limits, authentication needs, error handling, or what the output looks like (e.g., time series data). This is inadequate for a tool with parameters and no output schema.

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 with zero waste: 'Fetch accumulation/distribution line'. It's front-loaded and appropriately sized for its purpose, though it's under-specified rather than concise, but in terms of structure, it earns full marks for brevity.

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 (a financial indicator tool with 4 parameters, no annotations, no output schema, and 0% schema coverage), the description is severely incomplete. It doesn't explain the tool's behavior, parameters, output, or usage context, leaving the agent with insufficient information to invoke it correctly in a server with many similar 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%, meaning none of the 4 parameters (symbol, interval, month, datatype) are documented in the schema. The description adds no information about these parameters—it doesn't explain what they mean, their formats, or examples (e.g., symbol as ticker, interval as time frame). This fails 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 'Fetch accumulation/distribution line' clearly states the action (fetch) and the resource (accumulation/distribution line), which is a technical indicator in finance. However, it doesn't distinguish this tool from its many siblings (e.g., adosc, adx, adxr) that also relate to accumulation/distribution indicators, leaving the specific purpose vague in 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?

The description provides no guidance on when to use this tool versus alternatives. With numerous sibling tools for financial indicators and data, there's no mention of context, prerequisites, or comparisons (e.g., when to choose 'ad' over 'adosc' or other technical analysis tools), making it misleadingly incomplete.

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 'Fetch', implying a read-only operation, but doesn't specify any behavioral traits such as data sources, rate limits, error conditions, or output format. This leaves significant gaps in understanding how the tool behaves 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 with zero waste. It's front-loaded with the core purpose and appropriately sized for a simple fetch operation, making it easy to parse quickly without unnecessary elaboration.

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

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

Given the complexity of a technical indicator tool with 6 parameters, no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks essential context about parameter usage, behavioral details, and expected outputs, making it inadequate for an agent to invoke the tool correctly without additional 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?

With 6 parameters and 0% schema description coverage, the description adds no meaning beyond what the input schema provides. It doesn't explain what parameters like 'symbol', 'interval', 'month', 'fastperiod', 'slowperiod', or 'datatype' mean in the context of fetching the AD oscillator, 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 'Fetch accumulation/distribution oscillator' clearly states the action (fetch) and the specific technical indicator (accumulation/distribution oscillator), which is more specific than just the tool name 'adosc'. However, it doesn't differentiate from sibling tools like 'ad' (which likely fetches the accumulation/distribution line) or 'adx' (average directional index), leaving the purpose somewhat vague regarding exact scope.

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 many sibling tools for technical indicators (e.g., 'ad', 'adx', 'rsi', 'macd'), there's no indication of the specific use cases, prerequisites, or comparisons that would help an agent choose appropriately in 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 only states what the tool fetches without any information about rate limits, authentication requirements, data sources, response format, or error conditions. For a financial data tool with no annotations, this is completely inadequate.

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 at just 4 words, with no wasted language. It's front-loaded with the core purpose. While this conciseness comes at the expense of completeness, the structure itself is 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 a technical indicator tool with 5 parameters (3 required), 0% schema coverage, no annotations, no output schema, and numerous similar sibling tools, the description is completely inadequate. It doesn't explain what ADX is, how it's calculated, what the parameters mean, what data source is used, or how results are returned.

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 for all 5 parameters, the description provides absolutely no information about what 'symbol', 'interval', 'month', 'time_period', or 'datatype' mean, their expected formats, valid values, or how they affect the ADX calculation. The description doesn't compensate for the complete lack of parameter documentation in the schema.

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

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

The description states the tool fetches the average directional movement index, which is a specific financial indicator. However, it doesn't clarify what resource this operates on (e.g., stock data, forex data) or distinguish it from similar sibling tools like 'ad', 'adosc', or 'adxr' that appear to be related technical indicators.

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 numerous sibling tools including other technical indicators (e.g., 'rsi', 'macd', 'ad', 'adxr'), there's no indication of what makes this specific ADX tool appropriate or how it differs from related 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 only states what the tool does ('fetch'), without any information on permissions, rate limits, data sources, response format, error handling, or whether it's a read-only or mutating operation. This is inadequate for a tool with multiple parameters and no output schema.

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 with no wasted words. It is front-loaded with the core action and resource, making it easy to parse quickly. However, this conciseness comes at the cost of completeness, as noted in other dimensions.

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 (a financial indicator tool with 5 parameters, 3 required), lack of annotations, 0% schema coverage, and no output schema, the description is severely incomplete. It fails to provide necessary context such as parameter meanings, behavioral traits, or usage guidance, making it inadequate for effective tool invocation.

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 none of the 5 parameters (symbol, interval, month, time_period, datatype) are documented in the schema. The description adds no information about these parameters—it doesn't explain what they mean, their expected formats, or examples (e.g., what 'interval' or 'datatype' refer to). This leaves parameters entirely 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 clearly states the verb 'fetch' and the specific resource 'average directional movement index rating', which is a technical financial indicator. It distinguishes this tool from many siblings that fetch different indicators (e.g., 'adx', 'adosc', 'rsi'), though not all siblings are indicators (e.g., 'company_overview', 'news_sentiment'). The purpose is specific but could be more precise about what 'rating' entails versus raw values.

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 explain how 'adxr' differs from similar tools like 'adx' or other technical indicators in the sibling list, nor does it mention prerequisites or typical use cases. The description alone offers no context for selection among the many financial data tools available.

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 'Fetch all commodities' without explaining what 'fetch' means operationally—e.g., whether it's a read-only query, requires authentication, has rate limits, returns paginated results, or involves data processing. This leaves critical behavioral traits undisclosed.

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 just three words, 'Fetch all commodities,' which is front-loaded and wastes no space. However, this conciseness comes at the cost of under-specification, but as per the rubric, it scores high for brevity and structure alone.

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 (fetching data with 2 parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what commodities are fetched, how parameters influence the fetch, what the return format is, or any behavioral aspects, leaving the agent with insufficient information to use the tool effectively.

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 2 parameters (interval, datatype) with 0% description coverage, meaning their purposes are undocumented. The description 'Fetch all commodities' adds no meaning about these parameters—it doesn't hint at what interval or datatype are for, their expected values, or how they affect the fetch operation. This fails to compensate for the schema's lack of 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 'Fetch all commodities' restates the tool name 'all_commodities' in a tautological manner, providing no additional specificity about what 'commodities' refers to or what 'fetch' entails. It fails to distinguish this tool from its many siblings, which include various commodity-specific tools like aluminum, coffee, copper, etc., leaving the purpose vague.

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 the sibling commodity-specific tools (e.g., aluminum, coffee) or other data-fetching tools. The description lacks any context, prerequisites, or exclusions, making it misleading for an agent to determine appropriate usage.

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. 'Fetch aluminum' implies a read-only operation but doesn't specify what is fetched, how data is returned, any rate limits, authentication needs, or error conditions. For a tool with 2 parameters and no output schema, this is inadequate, offering no behavioral insights beyond the basic verb.

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 just two words, 'Fetch aluminum', which is front-loaded and wastes no space. While under-specified, it earns a high score for brevity and lack of redundancy, as every word directly relates to the tool's function without unnecessary elaboration.

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

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

Given the tool's complexity (2 parameters, 0% schema coverage, no annotations, no output schema, and many sibling tools), the description is completely inadequate. It doesn't explain what 'aluminum' refers to, how to use the parameters, what the output looks like, or when to choose this over other tools. This leaves critical gaps for an AI agent to understand and 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?

Schema description coverage is 0%, meaning parameters 'interval' and 'datatype' are undocumented in the schema. The description 'Fetch aluminum' adds no information about these parameters—it doesn't explain their purpose, expected values, or how they affect the fetch operation. With low coverage and no compensation in the description, this fails to provide any 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 'Fetch aluminum' restates the tool name 'aluminum' with a generic verb 'fetch', making it tautological. It lacks specificity about what resource is being fetched (e.g., price data, market info, production stats) and doesn't distinguish it from sibling tools like 'copper' or 'wheat', which likely have similar vague descriptions. This provides minimal clarity beyond the name.

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 context, prerequisites, or comparisons to sibling tools (e.g., other commodity tools like 'copper' or 'corn'), leaving the agent with no usage instructions. This is a complete lack of 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 fails to disclose any behavioral traits. It does not mention whether this is a read-only operation, its potential side effects, rate limits, authentication needs, or what the output might look like, leaving the agent with insufficient information.

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?

While concise with only three words, the description is under-specified rather than efficiently informative. It lacks front-loaded critical details and wastes its brevity on redundancy without adding value.

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 (5 parameters, 4 required), no annotations, no output schema, and 0% schema coverage, the description is completely inadequate. It does not provide enough context for an agent to understand or invoke the tool effectively.

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 adds no meaning beyond the schema. It does not explain what parameters like 'symbols', 'interval', or 'calculations' represent, their expected formats, or how they interact, 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 'Fetch analytics fixed window' restates the tool name with minimal elaboration, making it tautological. It lacks specificity about what analytics are fetched, what resources are involved, or how it differs from sibling tools like 'analytics_sliding_window'.

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 'analytics_sliding_window' or other analytics-related siblings. The description offers no context, prerequisites, or exclusions for usage.

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 fully disclose behavioral traits. However, it only states the action ('fetch') without any details on permissions, rate limits, side effects, or response format. For a tool with 6 parameters and no output schema, this lack of behavioral context is a significant gap, leaving the agent uninformed about how the tool operates.

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—a single three-word phrase—with no wasted words. It is front-loaded and efficiently states the core action, though this brevity comes at the cost of clarity and completeness. In terms of structure, it is minimal but not misleadingly verbose.

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

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

Given the tool's complexity (6 parameters, 5 required), lack of annotations, and absence of an output schema, the description is grossly inadequate. It fails to explain what the tool does, how to use it, what parameters mean, or what to expect in return. This leaves the agent with insufficient information to operate the tool effectively in 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 description coverage is 0%, meaning none of the 6 parameters are documented in the schema. The description does not compensate by explaining any parameters—it mentions no parameter names, purposes, or formats. This leaves all parameters undocumented, severely hindering the agent's ability to invoke the tool correctly.

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 'Fetch analytics sliding window' is tautological—it essentially restates the tool name with minimal elaboration. It specifies the verb 'fetch' and resource 'analytics sliding window', but provides no details about what analytics are fetched, what a sliding window entails, or how this differs from sibling tools like 'analytics_fixed_window'. This leaves the purpose vague and indistinguishable from alternatives.

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. It does not mention any context, prerequisites, or exclusions, nor does it reference sibling tools like 'analytics_fixed_window' for comparison. This absence of usage guidelines makes it difficult for an agent to decide when this tool 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 of behavioral disclosure. It only states 'Fetch absolute price oscillator', which implies a read operation but doesn't cover critical aspects like data sources, rate limits, error handling, or output format. This leaves significant gaps in understanding 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 a single, efficient sentence with no wasted words. It's front-loaded with the core purpose, making it easy to scan and understand quickly.

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 8 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain parameter meanings, behavioral traits, or return values, which are essential for a technical indicator 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?

The description provides no parameter information, and schema description coverage is 0%, leaving all 8 parameters undocumented. While the schema defines types and requirements, the description fails to explain what parameters like 'matype', 'datatype', or 'series_type' mean, making it hard to use correctly.

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 'Fetch absolute price oscillator' clearly states the action (fetch) and the resource (absolute price oscillator), which is a specific technical indicator. However, it doesn't differentiate from sibling tools like 'macd', 'rsi', or 'stoch' that also fetch technical indicators, leaving the distinction unclear.

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. With many sibling tools fetching technical indicators (e.g., 'macd', 'rsi', 'stoch'), the description lacks context about when the absolute price oscillator is appropriate, such as for trend analysis or momentum signals.

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 fully disclose behavioral traits. 'Fetch aroon' only implies a read operation without details on rate limits, authentication needs, data sources, or output format. This is inadequate for a tool with 5 parameters and no output schema.

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 two words, 'Fetch aroon', which is front-loaded and wastes no space. However, this brevity comes at the cost of clarity and completeness, but strictly for conciseness, it scores high.

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, 0% schema coverage, no annotations, no output schema, and many sibling tools), the description is completely inadequate. It doesn't explain the tool's purpose, usage, behavior, or parameters, failing to provide essential context for effective agent use.

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 by explaining parameters. It adds no meaning beyond the schema, failing to clarify what 'symbol', 'interval', 'month', 'time_period', or 'datatype' represent, their formats, or typical values, leaving all 5 parameters 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 'Fetch aroon' restates the tool name with a generic verb, making it tautological. It doesn't specify what 'aroon' refers to (likely a technical indicator in financial data) or what resource is being fetched, leaving the purpose vague compared to more descriptive sibling tools like 'time_series_daily' or 'rsi'.

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. With many sibling tools for financial indicators (e.g., 'rsi', 'macd', 'stoch'), the description lacks any context, prerequisites, or comparisons, 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?

No annotations are provided, so the description must fully disclose behavioral traits. 'Fetch' implies a read operation, but it doesn't specify data sources, rate limits, authentication needs, error handling, or what 'oscillator' entails in terms of output format or calculations. This leaves critical behavioral aspects 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 extremely concise with a single phrase, 'Fetch aroon oscillator', which is front-loaded and wastes no words. However, this conciseness comes at the cost of clarity and completeness.

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 technical indicator tool with 5 parameters (3 required), 0% schema coverage, no annotations, and no output schema, the description is severely incomplete. It doesn't explain the tool's purpose, usage, parameters, or expected outputs, making it inadequate for effective agent use.

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 parameters like 'symbol', 'interval', 'month', 'time_period', and 'datatype' are entirely undocumented in the schema. The description adds no meaning beyond the parameter names, failing to explain what these inputs represent or how they affect the fetch operation.

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 'Fetch aroon oscillator' restates the tool name 'aroonosc' (which appears to be a contraction of 'aroon oscillator'), making it tautological. It doesn't specify what resource is being fetched (e.g., financial data for a security) or provide any distinguishing context from sibling tools like 'aroon'.

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. With many sibling tools for technical indicators (e.g., 'aroon', 'adx', 'rsi'), the description offers no context about specific use cases, prerequisites, or comparisons.

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 fully disclose behavioral traits. 'Fetch average true range' only states the action without any details on data sources, rate limits, authentication needs, error handling, or output format. This is inadequate for a tool with multiple parameters and no output schema.

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 phrase with no wasted words. It's front-loaded and directly states the tool's purpose, making it easy to parse quickly despite its brevity.

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, 3 required, no annotations, no output schema), the description is severely incomplete. It doesn't explain what the tool returns, how parameters interact, or any behavioral context, leaving critical gaps for an agent to use the tool effectively.

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 none of the 5 parameters (symbol, interval, month, time_period, datatype) are documented in the schema. The description adds no information about what these parameters mean, their expected formats, or examples, 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 'Fetch average true range' clearly states the action (fetch) and the financial indicator (average true range), which is specific enough to understand the basic purpose. However, it doesn't distinguish this tool from sibling tools like 'natr' (normalized average true range) or 'trange' (true range), leaving ambiguity about when to choose one over another.

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 many sibling tools for technical indicators (e.g., 'natr', 'trange', 'rsi'), there's no mention of specific use cases, prerequisites, or comparisons, leaving the agent to guess based on tool names 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 full burden for behavioral disclosure. 'Fetch' implies a read operation, but the description doesn't specify whether this requires authentication, has rate limits, returns real-time or historical data, or what format the balance sheet data comes in. This leaves critical behavioral traits 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 extremely concise at just three words, front-loading the core purpose without any wasted language. Every word earns its place, though this conciseness comes at the cost of completeness.

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 financial data tool with no annotations, no output schema, and 0% schema parameter coverage, the description is completely inadequate. It doesn't explain what data is returned, how to interpret results, or any operational constraints, leaving the agent with insufficient context to use the tool effectively.

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 for the single parameter 'symbol', the description provides no additional meaning about what 'symbol' represents (e.g., stock ticker, company identifier), expected format, or examples. The description doesn't compensate for the schema's lack of 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 clearly states the verb 'fetch' and the resource 'company balance sheet', making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'income_statement' or 'cash_flow', which would require more specific language about what distinguishes a balance sheet from other financial statements.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'income_statement' or 'cash_flow', nor does it mention any prerequisites or context for usage. It simply states what the tool does without indicating appropriate 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Fetch' suggests a read-only operation, but it doesn't specify data sources, rate limits, authentication needs, error conditions, or what the output looks like. For a tool with 8 parameters and no output schema, 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 extremely concise with just two words, 'Fetch bollinger bands', which is front-loaded and wastes no space. While it may be under-specified, it earns full marks for brevity and clarity within its limited scope.

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

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

Given the complexity (8 parameters, 6 required, no schema descriptions, no annotations, no output schema), the description is completely inadequate. It doesn't explain the tool's behavior, parameter meanings, output format, or usage context. For a data-fetching tool with multiple inputs, this leaves the agent with insufficient information to use it correctly.

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

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

The schema description coverage is 0%, meaning none of the 8 parameters are documented in the schema. The description 'Fetch bollinger bands' adds no information about what parameters like 'symbol', 'interval', 'time_period', 'series_type', 'nbdevup', 'nbdevdn', 'month', or 'datatype' mean or how to use them. It fails 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 'Fetch bollinger bands' clearly states the action (fetch) and resource (bollinger bands), providing a basic purpose. However, it lacks specificity about what bollinger bands are or what data source is used, and doesn't differentiate from sibling tools like 'sma' or 'ema' which are also technical indicators. It's not tautological but remains somewhat vague.

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 many sibling tools for technical indicators (e.g., 'sma', 'rsi', 'macd'), there's no indication of when bollinger bands are appropriate, what prerequisites exist, or any exclusions. Usage is implied only by the tool name, not explained.

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 fully disclose behavioral traits. 'Fetch balance of power' only indicates a read operation without details on rate limits, authentication needs, data sources, or output format. It fails to describe what 'fetch' entails (e.g., real-time vs. historical data, potential costs, or error conditions), leaving significant gaps in understanding the tool's 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 with a single phrase 'Fetch balance of power', which is front-loaded and wastes no words. However, this conciseness comes at the cost of under-specification, but per the rules, conciseness is scored based on efficiency, not completeness.

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 implied by 4 parameters (including required ones) and no annotations or output schema, the description is incomplete. It does not cover parameter meanings, usage scenarios, behavioral aspects, or what the tool returns, making it inadequate for an agent to effectively select and invoke this tool among many 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?

The input schema has 4 parameters with 0% description coverage, and the tool description provides no information about any parameters. It does not explain what 'symbol', 'interval', 'month', or 'datatype' mean, their expected formats, or how they affect the 'balance of power' fetch. With no parameter details in the description, it fails 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 'Fetch balance of power' restates the tool name 'bop' (which likely stands for 'balance of power'), making it tautological. It specifies the verb 'fetch' and resource 'balance of power', but lacks detail on what 'balance of power' means in this context (e.g., a financial indicator, market metric) or how it differs from sibling tools like 'bbands' or 'rsi', which also appear to be technical indicators.

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 does not mention any context, prerequisites, or exclusions, and with many sibling tools (e.g., 'rsi', 'macd', 'cci') that might serve similar analytical purposes, the agent has no basis for choosing 'bop' over others.

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 but only states 'Fetch Brent crude oil', which implies a read operation without details on rate limits, authentication needs, data freshness, or return format. It lacks behavioral traits like whether it's real-time or historical, making it inadequate for a tool with parameters.

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 with zero waste, making it appropriately sized and front-loaded. However, this conciseness comes at the cost of under-specification, not verbosity.

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 (a data-fetching tool with 2 parameters), no annotations, no output schema, and 0% schema coverage, the description is completely inadequate. It doesn't explain what data is returned, how parameters affect the fetch, or behavioral context, failing to provide necessary completeness.

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 doesn't mention parameters at all. With 2 parameters ('interval', 'datatype') undocumented in both schema and description, it fails to add any meaning or compensate for the coverage gap, leaving their purpose and usage 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 'Fetch Brent crude oil' restates the tool name 'brent_crude_oil' with a generic verb, making it tautological. It doesn't specify what exactly is fetched (e.g., price data, historical trends, current quotes) or distinguish it from sibling tools like 'wti_crude_oil', leaving the purpose vague beyond the obvious resource.

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. With many sibling tools for commodities (e.g., 'wti_crude_oil', 'natural_gas', 'all_commodities'), the description offers no context, exclusions, or prerequisites, making it misleadingly simple 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. 'Fetch' implies a read operation, but it doesn't disclose behavioral traits like authentication requirements, rate limits, data freshness, error conditions, or what format the cash flow data returns. For a financial data tool with zero annotation coverage, this leaves significant gaps in understanding 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 concise at three words with zero waste. It's front-loaded with the core purpose, though this brevity comes at the cost of completeness. Every word earns its place by conveying the essential action and resource.

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 financial data tools, no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain what the tool returns, how to interpret results, or any constraints. For a tool that likely provides structured financial statements, more context is needed for effective use.

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 mentions no parameters. The single parameter 'symbol' is undocumented in both schema and description, leaving its meaning (e.g., stock ticker format, required exchanges) unclear. The description doesn't compensate for the schema's lack of 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 'Fetch company cash flow' clearly states the action (fetch) and resource (company cash flow), but it's somewhat vague about what 'cash flow' specifically entails (e.g., statement type, period). It distinguishes from many siblings by focusing on cash flow, but doesn't explicitly differentiate from similar financial tools like 'balance_sheet' or 'income_statement' beyond the resource name.

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 'balance_sheet', 'income_statement', and 'company_overview' that might overlap in financial data contexts, there's no indication of when cash flow data is specifically needed or what prerequisites might exist (e.g., symbol format).

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 'Fetch commodity channel index' without explaining what this operation entails—such as data sources, rate limits, authentication needs, error handling, or what 'fetch' implies (e.g., real-time vs. historical data). This leaves critical behavioral traits unspecified.

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, 'Fetch commodity channel index,' which is front-loaded and wastes no words. While it may be under-specified, it scores high on conciseness as every word directly contributes to stating the purpose without 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 complexity (a financial technical indicator tool with 5 parameters), lack of annotations, no output schema, and 0% schema description coverage, the description is severely incomplete. It fails to provide necessary context on behavior, parameters, or outputs, making it inadequate for effective tool invocation.

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

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

The description adds no meaning beyond the input schema, which has 0% description coverage. With 5 parameters (symbol, interval, month, time_period, datatype) and no explanation in the description of what they represent or how they affect the fetch operation, the agent lacks essential semantic context for proper usage.

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 'Fetch commodity channel index' clearly states the action (fetch) and the resource (commodity channel index), which is a specific technical indicator. However, it doesn't differentiate this tool from its many siblings (like rsi, macd, etc.) that also fetch different technical indicators, leaving the purpose somewhat vague in 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?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for technical indicators (e.g., rsi, macd, bbands), there's no mention of specific use cases, prerequisites, or comparisons, leaving the agent without contextual 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?

The description provides zero behavioral information beyond the basic purpose. With no annotations provided, the agent doesn't know if this is a read-only operation, whether it has rate limits, what data source it uses, what format the output takes, or any error conditions. For a financial data tool with 5 parameters, this is critically 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 extremely concise at just 4 words, front-loading the essential purpose with zero wasted words. While it's under-specified, what's there is perfectly structured 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?

The description is completely inadequate given the context. This is a financial data tool with 5 parameters (3 required), no annotations, no output schema, and 100+ sibling tools. The agent needs much more information about what this oscillator measures, how parameters affect it, what data it returns, and when to choose it over alternatives.

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

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

The description mentions no parameters at all, while the schema has 5 parameters with 0% description coverage. The agent must guess what 'symbol', 'interval', 'month', 'time_period', and 'datatype' mean and how they affect the oscillator calculation. This is a major gap for a tool with multiple required parameters.

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 with a specific verb ('fetch') and resource ('chande momentum oscillator'), making it immediately understandable. However, it doesn't differentiate this tool from its many sibling technical indicator tools (like 'rsi', 'macd', 'stoch'), which all fetch different financial indicators.

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 100+ sibling tools on the server (mostly other technical indicators and financial data tools), the agent receives no help in selecting this specific oscillator over similar tools like 'rsi' or 'mom'.

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 offers none. 'Fetch coffee' doesn't reveal whether this is a read/write operation, what permissions are needed, rate limits, error conditions, or what the return format might be. This is critically inadequate for a tool with parameters.

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?

While technically concise with just two words, this is under-specification rather than effective brevity. The description is front-loaded but provides no useful information, making every word wasted rather than earning its place through clarity or 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?

Given the tool's complexity (2 parameters, no annotations, no output schema) and rich sibling context (100+ financial tools), the description is completely inadequate. It doesn't explain what 'coffee' means in this financial context, what data it returns, or how to use the parameters, making the tool essentially unusable.

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

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

The description mentions no parameters, while the schema has 2 parameters (interval, datatype) with 0% description coverage. The description fails to compensate for this complete lack of parameter documentation, leaving both parameters entirely unexplained and unusable.

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 'Fetch coffee' is a tautology that merely restates the tool name 'coffee' without specifying what resource it actually fetches. It doesn't distinguish this tool from its many financial data siblings, leaving the purpose ambiguous and unhelpful for an AI agent.

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 the 100+ sibling tools, which include various financial indicators, commodities, and data types. There's no indication of context, prerequisites, or alternatives, making it impossible for an agent to make an informed 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 for behavioral disclosure. 'Fetch' implies a read operation, but the description provides no information about authentication requirements, rate limits, error conditions, response format, or whether this is a real-time or historical data source. This is inadequate for a tool with no annotation coverage.

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 at just two words. While this represents under-specification rather than ideal conciseness, it's not verbose or poorly structured. Every word serves a purpose, even if that purpose is insufficient.

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 financial data tool with no annotations, no output schema, and 0% parameter documentation, the description is completely inadequate. It doesn't explain what data is returned, in what format, with what limitations, or how it differs from related tools. The name/description mismatch further undermines completeness.

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 0% description coverage, with one required parameter 'symbol' completely undocumented. The description adds no information about what the symbol parameter represents (ticker format, exchange codes, validation rules) or how it should be used. This fails to compensate for the schema 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 'Fetch company splits' restates the tool name 'company_dividends' without clarifying the actual purpose. The name suggests dividends while the description mentions splits, creating confusion rather than providing a clear verb+resource statement. This is a tautology with misleading elements.

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 many sibling tools available (like company_earnings, company_overview, balance_sheet), there's no indication of what distinguishes this tool or when it's appropriate to use it.

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. 'Fetch' implies a read-only operation, but it doesn't specify authentication needs, rate limits, data freshness, error conditions, or what format the earnings data returns. This leaves significant gaps for an agent to understand how to use it effectively.

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 just two words, making it front-loaded and free of unnecessary details. Every word directly contributes to stating the tool's purpose without any fluff or redundant information.

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

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

Given the complexity of financial data tools, no annotations, no output schema, and low parameter coverage, the description is inadequate. It doesn't explain what 'earnings' includes (e.g., quarterly reports, metrics), how results are structured, or any prerequisites, leaving the agent with insufficient information to use this tool correctly in 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 input schema has 1 parameter with 0% description coverage, and the tool description doesn't mention any parameters. The description doesn't explain what 'symbol' represents (e.g., stock ticker, company identifier) or provide any context beyond what's in the bare schema, 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 'Fetch company earnings' clearly states the action (fetch) and resource (company earnings), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'earnings_calendar' or 'earnings_call_transcript', leaving ambiguity about what specific earnings data this provides compared to alternatives.

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 many sibling tools related to earnings (e.g., 'earnings_calendar', 'earnings_call_transcript'), there's no indication of what makes this tool distinct or when it should be preferred over others.

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. 'Fetch' implies a read-only operation, but the description doesn't specify any behavioral traits such as data sources, rate limits, authentication needs, or error handling. This leaves the agent with minimal operational context.

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 just two words, making it front-loaded and efficient. There's no wasted verbiage, though this brevity contributes to gaps in other dimensions.

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 financial data tools, no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover what the overview includes, how it differs from other tools, or any behavioral aspects, leaving significant gaps for an AI agent.

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

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

The input schema has 1 parameter with 0% description coverage, and the tool description doesn't mention the parameter at all. It fails to explain what 'symbol' represents (e.g., stock ticker, company identifier) or provide any semantic context beyond the bare 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 'Fetch company overview' states a clear verb ('fetch') and resource ('company overview'), but it's vague about what specific information constitutes the overview. It doesn't differentiate from sibling tools like 'balance_sheet', 'income_statement', or 'stock_quote', which might provide overlapping financial data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to company data (e.g., 'balance_sheet', 'earnings_calendar', 'news_sentiment'), there's no indication of what makes this tool unique or when it's preferred over others.

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. 'Fetch' implies a read operation, but the description reveals nothing about authentication needs, rate limits, data freshness, error conditions, or what format/scope of data is returned. For a financial/commodity data tool with zero annotation coverage, this is completely inadequate.

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 ('Fetch copper' - just two words), but this represents under-specification rather than effective brevity. While front-loaded with the verb 'fetch', it lacks any meaningful content that would help an AI agent understand or use the tool correctly.

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 implied by sibling tools (financial/commodity data with various parameters), zero annotations, 2 undocumented parameters, and no output schema, the description is completely inadequate. It provides no information about what data is fetched, how parameters affect results, what format data returns in, or how this differs from similar commodity 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% (both parameters have no descriptions), and the tool description provides zero information about the 'interval' and 'datatype' parameters. The description doesn't mention parameters at all, leaving both completely undocumented. With 2 parameters and no schema descriptions, the description fails to compensate for 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 'Fetch copper' is a tautology that merely restates the tool name with a generic verb. It doesn't specify what 'copper' refers to (commodity price, mining data, market information) or what resource is being fetched. Compared to siblings like 'coffee', 'corn', and 'wheat' which have similar vague descriptions, it fails to distinguish itself or provide meaningful purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides absolutely no guidance about when to use this tool versus alternatives. With 100+ sibling tools including many commodity-related ones (coffee, corn, wheat, aluminum), there's no indication whether this fetches price data, market analytics, or other copper-related information, or how it differs from tools like 'all_commodities' or 'time_series_daily'.

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 but only states 'Fetch corn' without disclosing behavioral traits like data sources, rate limits, authentication needs, or output format. This is inadequate for a tool with parameters and no output schema.

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 two words, front-loaded and zero waste. However, this conciseness comes at the cost of under-specification, but based on the dimension's focus on brevity and structure, it scores high.

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 implied by parameters and sibling tools, no annotations, no output schema, and 0% schema coverage, the description is completely inadequate. It doesn't provide enough context for an AI agent to understand or use the tool effectively.

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 adds no meaning for the two parameters ('interval' and 'datatype'). It doesn't explain what these parameters control or their expected values, 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 'Fetch corn' restates the tool name 'corn' with a generic verb, making it tautological. It doesn't specify what 'corn' refers to (e.g., corn prices, corn market data, corn commodities) or distinguish it from sibling tools like 'wheat' or 'sugar', leaving the purpose vague beyond the name.

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. With many sibling tools for commodities and financial data, the description offers no context, prerequisites, or comparisons, making it misleadingly simplistic 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 the full burden of behavioral disclosure. 'Fetch cotton' gives no indication of whether this is a read-only operation, whether it requires authentication, what rate limits might apply, what format the output takes, or any error conditions. This leaves critical behavioral traits completely unspecified.

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 ('Fetch cotton'), which could be appropriate if it were informative, but here it's under-specified rather than efficiently structured. While it's front-loaded with the only information available, that information is insufficient, making this a case of brevity at the expense of 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 the complexity implied by two parameters, no annotations, no output schema, and numerous sibling tools in what appears to be a financial/commodity data domain, the description is completely inadequate. It doesn't explain what the tool returns, how parameters affect results, or how it differs from similar tools, leaving the agent with insufficient context for effective use.

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, with two parameters ('interval' and 'datatype') completely undocumented in the schema. The description 'Fetch cotton' provides no information about these parameters—what values they accept, what they control, or whether they're optional/required. This fails to compensate for the schema's deficiencies.

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 'Fetch cotton' is a tautology that restates the tool name without adding meaningful context. It provides a basic verb ('fetch') but doesn't specify what 'cotton' refers to (commodity data, price information, market metrics, etc.) or distinguish it from sibling tools like 'coffee', 'corn', or 'wheat' that appear to be in the same domain. The purpose remains vague beyond the most generic interpretation.

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 any context, prerequisites, or exclusions, and doesn't reference sibling tools that might serve similar purposes (e.g., 'coffee', 'corn'). Without this information, an agent cannot make informed decisions about tool selection.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Fetch' implies a read operation, but there's no information about authentication requirements, rate limits, data freshness, error conditions, or what the return format looks like. This is inadequate for a tool with parameters.

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 maximally concise at just three words. It's front-loaded with the core purpose and wastes no space on unnecessary elaboration. For such a simple statement, this is perfectly 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 a 2-parameter tool with no annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what the tool returns, how to use the parameters, or any behavioral characteristics. This leaves the agent with insufficient information to use the tool effectively.

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 both parameters (interval and datatype), and the tool description provides absolutely no information about what these parameters mean, what values they accept, or how they affect the CPI data fetched. This leaves both parameters completely 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 'Fetch consumer price index' clearly states the verb ('fetch') and resource ('consumer price index'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its many siblings (like 'inflation' or other economic indicators), which would require a 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. With 100+ sibling tools including 'inflation' and other economic indicators, there's no indication of what makes 'cpi' distinct or when it should be preferred over similar 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 must fully disclose behavioral traits. 'Fetch crypto intraday' only implies a read operation without details on rate limits, authentication needs, data sources, error handling, or output format. This is inadequate for a tool with 5 parameters and no output schema, leaving agents guessing about 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 with 'Fetch crypto intraday', a single phrase that is front-loaded and wastes no words. While under-specified, it is structurally efficient, earning a high score for brevity and clarity within its limited scope.

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

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

Given the tool's complexity (5 parameters, no annotations, no output schema, and many sibling tools), the description is severely incomplete. It lacks purpose differentiation, usage guidelines, behavioral details, parameter explanations, and output information, making it inadequate for effective agent use.

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 none of the 5 parameters (symbol, market, interval, outputsize, datatype) are documented in the schema. The description adds no semantic information about these parameters (e.g., what symbols or markets are valid, interval formats, outputsize options, datatype meanings), failing to compensate for 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 'Fetch crypto intraday' restates the tool name 'crypto_intraday' with minimal elaboration, making it tautological. It specifies the resource (crypto intraday data) and verb (fetch) but lacks detail on what 'intraday' entails (e.g., time-series data, price metrics) or how it differs from sibling tools like 'digital_currency_daily' or 'fx_intraday', leaving purpose vague.

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. With sibling tools like 'digital_currency_daily', 'fx_intraday', and 'time_series_intraday', the description fails to indicate context (e.g., for cryptocurrency vs. forex, specific data types), prerequisites, or exclusions, offering 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Fetch' implies a read operation, but the description doesn't address critical behavioral aspects like data sources, rate limits, authentication requirements, error conditions, or what format/scope the 'fetch' returns. For a financial data tool with 6 parameters, this leaves significant gaps in understanding 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 maximally concise with a single clear phrase. There's no wasted language or unnecessary elaboration - every word contributes directly to stating the tool's purpose. The structure is front-loaded with the essential information.

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

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

For a technical indicator calculation tool with 6 parameters, no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It provides only the basic purpose without explaining parameter meanings, behavioral characteristics, or output format. Given the complexity implied by multiple parameters and the financial data context, more complete guidance is needed.

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 for all 6 parameters, the description provides no information about what any parameter means or how they interact. 'Fetch double exponential moving average' gives no insight into required parameters like symbol, interval, time_period, series_type, or optional ones like month and datatype. 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 'Fetch double exponential moving average' clearly states the action (fetch) and resource (double exponential moving average), which is specific enough to understand the basic purpose. However, it doesn't differentiate from similar technical indicator tools like 'ema' (exponential moving average) or 't3' (triple exponential moving average) in the sibling list, leaving ambiguity about when to choose this specific variant.

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. With many similar technical analysis tools in the sibling list (e.g., ema, sma, wma, t3), the description lacks any context about appropriate use cases, prerequisites, or comparisons to help an agent select this specific moving average calculation method.

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 only states the action ('fetch') without disclosing behavioral traits such as rate limits, authentication needs, data freshness, error handling, or what the output contains (e.g., historical prices). This leaves critical operational details unknown.

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 with no wasted words. It's front-loaded and appropriately sized for the tool's apparent simplicity, though this conciseness comes at the cost of detail.

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, 0% schema coverage, and no output schema, the description is incomplete. It lacks essential context for a data-fetching tool, such as output format, data scope, or behavioral constraints, making it inadequate for reliable agent use.

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 schema provides no parameter details. The description adds no meaning beyond the schema—it doesn't explain what 'symbol' and 'market' represent (e.g., currency ticker, exchange code), their formats, or examples. This fails 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 'Fetch digital currency daily' states the action (fetch) and resource (digital currency daily), but it's vague about what 'digital currency daily' specifically refers to (e.g., price data, volume, market data). It doesn't distinguish from siblings like 'digital_currency_monthly' or 'digital_currency_weekly', leaving ambiguity about scope.

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. With siblings like 'digital_currency_monthly', 'digital_currency_weekly', and 'crypto_intraday', there's no indication of differences in timeframes or data granularity, nor any prerequisites or exclusions 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'fetch', implying a read operation, but doesn't cover critical aspects like rate limits, authentication needs, error handling, or what the output looks like (e.g., data format, pagination). This is inadequate for a tool with no annotation support.

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 'Fetch digital currency monthly', which is front-loaded and wastes no words. However, this conciseness comes at the cost of completeness, as noted in other dimensions.

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 (a data-fetching tool with 2 required parameters), no annotations, 0% schema coverage, and no output schema, the description is highly incomplete. It lacks essential details on behavior, parameters, output, and usage context, making it insufficient for effective tool selection and invocation.

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 'symbol' and 'market' have no documentation in the schema. The description adds no information about these parameters, such as what they represent (e.g., currency symbol like BTC, market like USD), expected formats, or examples. This fails to compensate for the lack of schema details.

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 'Fetch digital currency monthly' states a verb ('fetch') and resource ('digital currency monthly'), providing a basic purpose. However, it's vague about what 'monthly' means (e.g., monthly data, monthly updates) and doesn't distinguish it from siblings like 'digital_currency_daily' or 'digital_currency_weekly' beyond the time period in the name.

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 sibling tools like 'digital_currency_daily' or 'digital_currency_weekly' for different timeframes, or other tools like 'crypto_intraday' for intraday data, leaving usage context unclear.

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 but fails to disclose behavioral traits. It doesn't mention whether this is a read-only operation, potential rate limits, authentication needs, error handling, or what 'fetch' entails (e.g., returns historical data, current status). This leaves critical behavioral aspects unspecified.

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, 'Fetch digital currency weekly', which is front-loaded and wastes no words. While it may be under-specified, it earns full marks for brevity and 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?

Given the complexity of a financial data tool with 2 parameters, no annotations, and no output schema, the description is incomplete. It doesn't cover parameter meanings, behavioral aspects, or expected outputs, making it insufficient for an agent to use the tool effectively.

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 0% description coverage, with two required parameters ('symbol' and 'market') undocumented. The description adds no meaning beyond the schema, failing to explain what these parameters represent (e.g., currency symbol like BTC, market like USD) or their expected formats, which is inadequate given the low 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 'Fetch digital currency weekly' states a verb ('fetch') and resource ('digital currency weekly'), making the purpose understandable. However, it's vague about what 'weekly' means (e.g., weekly data, weekly frequency) and doesn't differentiate from siblings like 'digital_currency_daily' or 'digital_currency_monthly', which is a missed opportunity for clarity.

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 lacks context such as use cases, prerequisites, or comparisons to sibling tools like 'digital_currency_daily' or 'crypto_intraday', leaving the agent without direction on 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 must fully disclose behavior. 'Fetch durables' implies a read-only operation but lacks details on permissions, rate limits, data freshness, or response format. It fails to compensate for the absence of structured annotations.

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

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

The description is extremely concise with two words, front-loaded and zero waste. However, this conciseness comes at the cost of clarity and completeness, but strictly on structure, it's 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 complexity (1 parameter with no schema coverage, no annotations, no output schema), the description is inadequate. It doesn't explain what 'durables' are, how to use the parameter, or what to expect in return, leaving the tool's functionality ambiguous.

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 one parameter 'datatype' with 0% description coverage and no enums. The description adds no meaning about this parameter—it doesn't explain what 'datatype' is, valid values, or how it affects fetching. With low schema coverage, the description doesn't compensate.

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 'Fetch durables' restates the tool name 'durables' with a generic verb 'fetch', making it tautological. It doesn't specify what 'durables' refers to (e.g., economic data, financial instruments, or commodities) or distinguish it from sibling tools like 'aluminum', 'copper', or 'wheat' which appear to be commodity-related.

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. With many sibling tools (e.g., commodity-specific ones like 'aluminum', 'copper'), the description offers no context for selection, 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 full burden for behavioral disclosure. The description only states what the tool does at a high level ('Fetch directional movement index') without explaining what 'fetch' entails - whether it's a read operation, if it requires authentication, rate limits, data freshness, error behavior, or what format the results come in. For a financial data tool with 5 parameters, this is critically 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 maximally concise - a single 4-word phrase that gets straight to the point. There's zero wasted language or unnecessary elaboration. While this conciseness comes at the cost of completeness, as a standalone assessment of conciseness and structure, it's perfect.

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 (financial indicator calculation with 5 parameters), zero annotation coverage, zero schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what a directional movement index is, how parameters affect it, what data is returned, or any behavioral characteristics. The description fails to provide the minimal context needed for effective tool use.

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 none of the 5 parameters (symbol, interval, month, time_period, datatype) have descriptions in the schema. The tool description provides absolutely no information about any parameters - not what they mean, what values they accept, or how they affect the directional movement index calculation. This leaves all parameters completely 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 'Fetch directional movement index' states a verb ('Fetch') and resource ('directional movement index'), but it's vague about what this actually does - it doesn't explain what a directional movement index is or what specific data is retrieved. It doesn't distinguish from siblings like 'adx' or 'adxr' which appear related. The description is better than a tautology but lacks specificity.

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 numerous sibling tools including 'adx' and 'adxr' that appear to be related technical indicators, there's no indication of when this specific directional movement index tool should be selected over those alternatives. No context, prerequisites, or exclusions 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. While 'fetch' implies a read operation, it doesn't specify whether this requires authentication, has rate limits, what format the earnings calendar data returns, or whether it's real-time or historical data. The description is too minimal for a tool with parameters.

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 at just three words, with zero wasted language. It's front-loaded with the core purpose and doesn't contain any unnecessary elaboration. This is appropriate conciseness for a simple-sounding tool.

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 has 2 parameters with 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, how to use the parameters, or any behavioral characteristics. For a financial data tool with parameters, this leaves too many unanswered questions.

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 both parameters (symbol and horizon), and the tool description provides no information about what these parameters mean, their expected formats, or valid values. The description doesn't compensate for the complete lack of parameter documentation in the schema.

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

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

The description clearly states the verb 'fetch' and the resource 'company earnings calendar', making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'company_earnings' or 'ipo_calendar', which might have overlapping functionality in the financial data 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?

The description provides no guidance on when to use this tool versus alternatives like 'company_earnings' or 'ipo_calendar'. There's no mention of what makes this earnings calendar tool unique, what timeframes it covers, or any prerequisites for its use.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool fetches data, implying a read-only operation, but doesn't specify any constraints like rate limits, authentication needs, error handling, or the format of the returned transcript. This leaves significant gaps in understanding 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 a single, well-structured sentence that efficiently conveys the core functionality without unnecessary words. It's front-loaded with the main action and resource, making it easy to parse quickly.

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 (fetching specific financial data), lack of annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like data sources, potential errors, or return format, leaving the agent with insufficient context to use the tool effectively.

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 0% description coverage, so the description must compensate. It mentions 'symbol' and 'quarter' but doesn't explain what they represent (e.g., stock ticker, fiscal quarter format) or provide examples. This adds minimal semantic value beyond the schema's property names, failing to adequately clarify parameter usage.

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 action ('Fetch') and resource ('earnings call transcript') with specific targeting ('for a given company in a specific quarter'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'company_earnings' or 'earnings_calendar', which might offer related financial data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description lacks context about prerequisites, such as needing a valid company symbol or quarter format, and doesn't mention any sibling tools that might serve similar or overlapping purposes, leaving usage unclear.

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. 'Fetch exponential moving average' only states the action without any behavioral details: it doesn't mention data sources, rate limits, authentication needs, error handling, response format, or whether this is a read-only operation. For a tool with 6 parameters and no annotations, this is a significant gap in transparency.

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

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

The description is a single, efficient phrase: 'Fetch exponential moving average'. It's front-loaded with the core action and resource, with zero wasted words. This is appropriately concise for a simple-sounding tool, though the simplicity might mask complexity in parameters.

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

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

Given the complexity (6 parameters with 0% schema coverage, no annotations, no output schema, and many sibling tools), the description is incomplete. It doesn't explain what the tool returns, how parameters interact, or any behavioral context. For a technical indicator tool with multiple inputs, this is insufficient to guide an AI agent effectively.

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 description coverage is 0%, meaning none of the 6 parameters have descriptions in the schema. The tool description 'Fetch exponential moving average' adds no information about what the parameters (symbol, interval, month, time_period, series_type, datatype) mean, their expected values, or how they affect the calculation. With low coverage and no compensation in the description, this is inadequate.

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 'Fetch exponential moving average' clearly states the action (fetch) and the resource (exponential moving average), which is a specific technical indicator. However, it doesn't differentiate this tool from other technical analysis tools in the sibling list (like sma, dema, wma, trima, t3, etc.), which all fetch different types of moving averages or similar indicators. The purpose is understandable but lacks sibling differentiation.

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 many sibling tools for technical indicators (e.g., sma, dema, wma, trima, t3, mama, kama, etc.), there's no indication of when an exponential moving average is preferred over other moving average types or other indicators. No context, exclusions, or prerequisites 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Fetch' implies a read operation, but it doesn't specify if it's idempotent, has rate limits, requires authentication, or what the output format might be. For a data-fetching tool with zero 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 extremely concise with just two words, 'Fetch ETF profile', which is front-loaded and wastes no space. While it may be under-specified, it earns a high score for brevity and clarity within its limited scope.

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

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

Given the complexity of financial data tools, no annotations, no output schema, and low parameter coverage, the description is incomplete. It doesn't cover behavioral aspects, output details, or usage context, making it inadequate for an agent to effectively use this tool without additional assumptions or errors.

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 description provides no additional parameter information. It doesn't explain what 'symbol' represents (e.g., ticker format, examples, constraints), leaving the agent to guess. With low schema coverage, the description fails to compensate, 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 'Fetch ETF profile' states a clear verb ('fetch') and resource ('ETF profile'), which is better than a tautology. However, it lacks specificity about what an 'ETF profile' contains and doesn't differentiate from siblings like 'company_overview' or 'stock_quote', which might provide similar financial data. The purpose is understandable but vague in scope.

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, context, or exclusions, such as whether it's for real-time data, historical info, or how it differs from other financial data tools in the sibling list. This leaves the agent without direction on tool selection.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Fetch exchange rate' provides minimal behavioral information - it doesn't indicate whether this is real-time or historical data, what data source is used, rate limits, authentication requirements, or what format the response takes. For a financial data tool with zero annotation coverage, this is inadequate.

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 maximally concise with just two words. While it's under-specified, it's not verbose or poorly structured. Every word earns its place, though more words would be needed for a complete 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 financial data tools, zero annotation coverage, 0% schema description coverage, no output schema, and 100+ sibling tools, this description is completely inadequate. It doesn't provide enough information for an AI agent to understand when or how to use this tool effectively compared to alternatives.

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 neither parameter (from_currency, to_currency) has any documentation in the schema. The description provides no information about these parameters - no examples, no format requirements (currency codes like USD/EUR), no constraints. 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 'Fetch exchange rate' is a tautology that essentially restates the tool name 'exchange_rate'. While it includes a verb ('fetch'), it doesn't specify what resource or data is being fetched beyond what's implied by the name. It doesn't distinguish this tool from its many financial/economic sibling tools.

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 100+ sibling tools including various financial data tools (fx_daily, fx_intraday, etc.), there's no indication of what makes this tool distinct or when it should be preferred over similar 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. 'Fetch' implies a read operation, but the description doesn't specify data sources, update frequency, error handling, or output format. This is inadequate for a tool with parameters and no output schema.

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 just three words, front-loading the essential action and resource. There's no wasted language, making it efficient for quick comprehension, though this brevity contributes to gaps in other dimensions.

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 what the tool returns, how parameters affect results, or behavioral traits, leaving the agent with insufficient information for reliable use.

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 the two parameters ('interval' and 'datatype') are undocumented in the schema. The description adds no information about these parameters—not their purposes, allowed values, or defaults—failing 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 clearly states the verb 'fetch' and the resource 'federal funds rate', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools that might also fetch economic indicators (like 'inflation' or 'unemployment'), so it doesn't reach the highest score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for economic data (e.g., 'inflation', 'unemployment', 'cpi'), there's no indication of context, prerequisites, or comparisons, leaving the agent to guess based on tool names 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. 'Fetch' implies a read-only operation, but the description doesn't clarify authentication needs, rate limits, data freshness, error handling, or output format. It fails to disclose any behavioral traits beyond the basic action, leaving critical operational details unspecified.

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 at just two words ('Fetch FX daily'), which is appropriate for a simple data retrieval tool. It's front-loaded with the core action and resource, with no wasted words or redundant information. This minimalism is efficient, though it comes at the cost of completeness.

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 moderate complexity (4 parameters, no annotations, no output schema), the description is incomplete. It doesn't compensate for the lack of structured data: parameters are undocumented, behavioral traits are unspecified, and there's no output information. While concise, it fails to provide enough context for reliable agent use, especially compared to more detailed sibling 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?

The input schema has 4 parameters with 0% description coverage, and the tool description adds no semantic information about any parameters. It doesn't explain what 'from_symbol' and 'to_symbol' represent (e.g., currency codes), the purpose of 'datatype' and 'outputsize', or provide examples. With no parameter guidance in either schema or description, the agent lacks essential context for correct invocation.

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 'Fetch FX daily' clearly indicates a retrieval action ('fetch') and specifies the resource type (FX/financial data) with a temporal scope ('daily'). However, it lacks specificity about what exactly is fetched (e.g., exchange rates, historical prices) and doesn't differentiate from sibling tools like 'fx_intraday', 'fx_monthly', or 'fx_weekly', which all handle FX data at different 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'fx_intraday' for intraday data or 'exchange_rate' for real-time rates, nor does it specify prerequisites, constraints, or typical use cases. The agent must infer usage from the tool 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 must fully disclose behavioral traits. It only states 'Fetch FX intraday', which implies a read operation but doesn't cover critical aspects like rate limits, authentication needs, data freshness, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.

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 ('Fetch FX intraday'), which is front-loaded but under-specified. While it avoids unnecessary words, it lacks essential details that would make it useful. Conciseness alone doesn't justify a higher score when the content is insufficient.

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 (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'FX intraday' data includes, how parameters affect the fetch, or what the return values look like. This makes it inadequate for an agent to use the tool effectively.

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 5 parameters with 0% description coverage, and the description adds no semantic information about them. Parameters like 'interval', 'outputsize', and 'datatype' are undefined, making it unclear what values are expected or their effects. The description fails to compensate for the low 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 'Fetch FX intraday' states a verb ('Fetch') and resource ('FX intraday'), but it's vague about what 'FX intraday' entails—it could mean exchange rates, prices, or other data. It doesn't differentiate from sibling tools like 'fx_daily' or 'crypto_intraday', leaving ambiguity. This is a tautology that mostly restates the tool name without clarifying the specific purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools for financial data (e.g., 'fx_daily', 'crypto_intraday'), the description lacks any context, exclusions, or prerequisites. This absence makes it difficult for an agent to choose appropriately among similar 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 full burden but discloses no behavioral traits. It does not indicate if this is a read-only operation, requires authentication, has rate limits, or describes output format (e.g., time series data). The term 'fetch' implies retrieval but lacks specifics on data freshness or constraints.

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 two words, but this brevity leads to under-specification rather than efficient communication. It is front-loaded but lacks necessary detail, making it concise at the expense of 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 3 parameters with 0% schema coverage, no annotations, no output schema, and a complex context with many sibling tools, the description is incomplete. It fails to provide essential details for proper tool invocation, such as parameter meanings, behavioral context, or differentiation from alternatives.

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 adds no meaning beyond the schema. It does not explain parameters like 'from_symbol', 'to_symbol', or 'datatype' (e.g., currency codes, data format), leaving all three parameters undocumented in both schema and 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 'Fetch FX monthly' restates the tool name 'fx_monthly' with minimal elaboration, making it tautological. It specifies the verb 'fetch' and resource 'FX monthly' but lacks detail on what 'FX monthly' entails (e.g., foreign exchange rates, time series data) and how it differs from siblings like 'fx_daily' or 'fx_weekly', leaving purpose vague beyond the name.

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 does not mention sibling tools (e.g., 'fx_daily', 'fx_weekly', 'exchange_rate') or context for preferring monthly data, offering no usage instructions 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. 'Fetch' implies a read operation, but it doesn't specify any behavioral traits such as rate limits, authentication needs, data freshness, or error handling. This is inadequate for a tool with parameters and no structured safety hints.

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 just two words, 'Fetch FX weekly', which is front-loaded and wastes no space. While it may be under-specified, it earns full marks for brevity and lack of 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 complexity (3 parameters with 0% schema coverage, no annotations, no output schema, and many sibling tools), the description is severely incomplete. It doesn't explain what the tool returns, how to interpret parameters, or differentiate it from similar tools, making it inadequate for effective agent use.

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 'from_symbol', 'to_symbol', and 'datatype' are undocumented in the schema. The description adds no information about these parameters—no explanations of what they represent, valid formats, or examples. This fails 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 'Fetch FX weekly' states a verb ('Fetch') and resource ('FX weekly'), making the basic purpose clear. However, it's vague about what 'FX weekly' specifically entails (e.g., foreign exchange rates, data, or reports) and doesn't distinguish it from sibling tools like 'fx_daily', 'fx_monthly', or 'exchange_rate', leaving ambiguity in scope.

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. With siblings such as 'fx_daily', 'fx_monthly', and 'exchange_rate', the description lacks any indication of context, prerequisites, or exclusions, leaving the agent to infer usage based on naming 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 must fully disclose behavioral traits. It only states the action ('fetch') without details on permissions, rate limits, data format, or side effects. For a tool with no annotations and three parameters, this is inadequate and fails to inform the agent about 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 concise with just two words, 'Fetch historical options', which is front-loaded and wastes no space. However, this brevity comes at the cost of clarity and completeness, but as a standalone text, it's efficiently 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 tool's complexity (3 parameters, no annotations, no output schema), the description is incomplete. It lacks purpose differentiation, usage guidelines, behavioral details, and parameter explanations. For a data-fetching tool in a financial context, this minimal description fails to provide necessary context for effective use.

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 'symbol', 'datatype', and 'contract' are undocumented in the schema. The description adds no meaning about these parameters—it doesn't explain what they represent, their formats, or examples. With low coverage and no compensation, this leaves parameters ambiguous.

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 'Fetch historical options' states a verb ('fetch') and resource ('historical options'), but it's vague about what 'historical options' means—likely financial options data, but this isn't specified. It doesn't distinguish from siblings like 'realtime_options' or 'company_overview', leaving ambiguity. This is a tautology that mostly restates the tool name without added clarity.

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. With siblings like 'realtime_options' and 'time_series_daily', the description offers no context on use cases, prerequisites, or exclusions. This leaves the agent without direction 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 the full burden of behavioral disclosure. The description only states what is fetched, with no information about how the tool behaves: whether it's a read-only operation, potential rate limits, authentication requirements, error conditions, or what the output format looks like. This is inadequate for a tool with 5 parameters.

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 at just 6 words, with no wasted language. It's front-loaded with the core purpose. However, this conciseness comes at the cost of completeness, as it omits necessary contextual information.

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

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

Given the complexity (technical indicator calculation with 5 parameters), no annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what the tool returns, how parameters affect the calculation, when to use it, or any behavioral characteristics. The agent would struggle to use 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%, meaning none of the 5 parameters have descriptions in the schema. The tool description provides no information about what the parameters mean, their expected formats, or how they affect the calculation. Parameters like 'month', 'series_type', and 'datatype' are completely unexplained, leaving the agent guessing about their purpose.

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 as 'Fetch hilbert transform - dominant cycle period', which specifies the action (fetch) and the technical indicator being retrieved. It distinguishes from many siblings that fetch different indicators or data types, though it doesn't explicitly differentiate from similar Hilbert transform tools like ht_dcphase, ht_phasor, ht_sine, ht_trendline, and ht_trendmode.

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 what the dominant cycle period represents, when this indicator is useful in analysis, or how it differs from other Hilbert transform tools in the sibling list, leaving the agent to 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, and the description offers no behavioral information. It doesn't disclose whether this is a read-only operation, what data sources it uses, potential rate limits, error conditions, or any other behavioral traits needed for reliable invocation.

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 just 5 words, front-loading the core purpose without any unnecessary elaboration. Every word serves a functional purpose in identifying what the tool does.

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 4 parameters (2 required), no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It provides only basic purpose identification without any of the contextual information needed for proper tool selection and invocation.

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 for all 4 parameters, the description provides no information about what 'symbol', 'interval', 'month', or 'datatype' mean, their expected formats, or valid values. The description doesn't compensate for this complete lack of parameter 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 states the tool fetches the Hilbert transform dominant cycle phase, which is a specific technical indicator. However, it doesn't explain what this indicator measures or how it differs from similar sibling tools like ht_dcperiod, ht_phasor, or ht_sine, leaving the purpose somewhat vague for non-experts.

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 any context, prerequisites, or comparisons to sibling tools, making it impossible for an agent to determine 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?

No annotations are provided, so the description must fully disclose behavioral traits. It only mentions 'Fetch', implying a read operation, but lacks details on permissions, rate limits, data sources, or output format. This is inadequate for a tool with parameters and no output schema.

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 with no wasted words. It's front-loaded but under-specified, which is a completeness issue rather than conciseness. For its brevity, it earns a high score in this dimension.

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 (technical financial/technical analysis tool), 4 parameters with 0% schema coverage, no annotations, and no output schema, the description is severely incomplete. It doesn't explain the tool's function, usage, behavior, or parameters, making it inadequate for an AI agent.

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

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

Schema description coverage is 0%, so the description must compensate by explaining parameters. It adds no meaning beyond the schema, failing to clarify what 'symbol', 'interval', 'month', or 'datatype' represent or how they affect the fetch. This leaves all 4 parameters 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 'Fetch hilbert transform - phasor components' states a verb ('Fetch') and resource ('hilbert transform - phasor components'), but it's vague and technical without explaining what the tool actually does or what 'phasor components' are. It doesn't distinguish from siblings like 'ht_dcperiod' or 'ht_sine', which appear related. The purpose is unclear to non-experts.

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. With many sibling tools (e.g., 'ht_dcperiod', 'ht_sine'), the description offers no context, exclusions, or comparisons. This leaves the agent guessing about appropriate use cases.

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. It only states 'fetch', implying a read operation, but gives no information about rate limits, authentication needs, data sources, error conditions, or what the output looks like. For a tool with 5 parameters and no output schema, this is critically inadequate.

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—just 5 words. While this leads to severe under-specification, it's not verbose or poorly structured. Every word earns its place by hinting at the tool's function, though it fails to provide necessary 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?

Given the complexity (5 parameters, no annotations, no output schema, and many sibling tools), the description is completely inadequate. It doesn't explain what the tool does beyond a vague hint, provides no parameter guidance, no behavioral context, and no differentiation from alternatives. This leaves the agent unable to use the tool effectively.

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 none of the 5 parameters (symbol, interval, month, series_type, datatype) are documented in the schema. The description adds no parameter information whatsoever—it doesn't explain what these parameters mean, their formats, or valid values. This leaves all parameters completely 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 'Fetch hilbert transform - sine wave' is tautological, essentially restating the tool name 'ht_sine' (likely meaning Hilbert Transform sine). It doesn't specify what resource is being fetched (e.g., financial data, signal processing results) or provide a clear verb beyond 'fetch'. While it hints at a mathematical transformation, it lacks specificity about the domain or output.

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 numerous sibling tools (e.g., ht_dcperiod, ht_phasor, ht_trendline) that appear related to Hilbert Transform functions, there's no indication of how this specific sine wave variant differs or when it's appropriate. No context, exclusions, or prerequisites 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. The description only mentions 'fetch' without specifying whether this is a read-only operation, what data sources are used, potential rate limits, error conditions, or what format the output takes. For a tool with 5 parameters and no output schema, this is a significant gap in behavioral 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 extremely concise at just 4 words. While this brevity comes at the cost of completeness, every word earns its place by specifying the action ('fetch'), the mathematical concept ('hilbert transform'), and the specific component ('trendline'). There's no wasted language.

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 (technical indicator with 5 parameters), no annotations, 0% schema description coverage, and no output schema, the description is completely inadequate. It doesn't explain what the tool returns, how parameters interact, what the Hilbert transform trendline represents mathematically, or any prerequisites for use. This leaves too many unanswered questions for effective tool selection and invocation.

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 none of the 5 parameters have descriptions in the schema. The tool description provides no information about what 'symbol', 'interval', 'month', 'series_type', or 'datatype' mean, their expected formats, or valid values. With 3 required parameters and no parameter guidance, this is inadequate.

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 'Fetch hilbert transform - trendline' states the action (fetch) and resource (hilbert transform trendline), but it's vague about what exactly is being fetched. It doesn't specify if this is a calculation, indicator value, or time series data, nor does it distinguish from sibling tools like ht_dcperiod or ht_sine that also fetch Hilbert transform components.

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 many sibling tools for technical indicators (e.g., ht_dcperiod, ht_phasor, ht_sine, ht_trendmode) and general data fetching tools (e.g., time_series_daily), there's no indication of what makes this specific Hilbert transform trendline tool appropriate or when other tools should be preferred.

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 but fails to do so. It does not indicate whether this is a read-only or mutative operation, any rate limits, authentication needs, or what the output entails (e.g., data format or potential side effects).

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 concise with a single phrase, but this brevity leads to under-specification rather than efficiency. It is front-loaded but lacks necessary detail, making it insufficiently informative despite its short length.

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 implied by the tool name (involving Hilbert transforms and trend analysis), 4 parameters with 0% schema coverage, no annotations, and no output schema, the description is completely inadequate. It does not provide enough context for an agent to understand or use the tool effectively.

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 none of the 4 parameters (symbol, interval, month, datatype) are documented in the schema. The description adds no information about these parameters, such as their purposes, expected formats, or examples, 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 'Fetch hilbert transform - trend mode' restates the tool name 'ht_trendmode' with minimal elaboration, making it tautological. It specifies a verb ('Fetch') and resource ('hilbert transform - trend mode'), but lacks clarity on what the Hilbert transform is or what 'trend mode' entails, and does not distinguish it from sibling tools like 'ht_dcperiod' or 'ht_sine'.

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 any context, prerequisites, or comparisons to sibling tools, leaving the agent without direction on 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 the full burden of behavioral disclosure. It states 'fetch' implies a read operation, but doesn't cover critical aspects like authentication needs, rate limits, error handling, or what the output looks like (e.g., format, time periods covered). This leaves significant gaps for an agent to understand how to use it effectively.

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 with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place in conveying the basic 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 complexity of financial data fetching, no annotations, no output schema, and an undocumented parameter, the description is insufficient. It doesn't address output format, error cases, or usage context, leaving the agent with too many unknowns to use the tool reliably.

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 description doesn't mention the 'symbol' parameter at all. It fails to explain what 'symbol' represents (e.g., stock ticker, company identifier), expected format, or examples. For a single undocumented parameter, this is inadequate compensation.

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 'Fetch company income statement' clearly states the verb ('fetch') and resource ('company income statement'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'balance_sheet' or 'cash_flow' that also fetch financial statements, so it lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'balance_sheet' or 'cash_flow', nor does it mention prerequisites or context for usage. It merely states what the tool does without indicating appropriate 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?

No annotations are provided, so the description carries full burden but only states 'Fetch inflation' without disclosing any behavioral traits. It doesn't mention if this is a read-only operation, potential rate limits, authentication needs, data freshness, or what the output looks like, leaving critical gaps for an agent.

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 just two words, front-loaded and zero waste. However, this brevity comes at the cost of underspecification, but purely on conciseness, it's optimal.

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 (economic data fetching with a parameter), lack of annotations, no output schema, and low schema coverage, the description is completely inadequate. It doesn't provide enough context for an agent to understand what the tool does, how to use it, or what to expect in return.

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 one parameter 'datatype' with 0% schema description coverage, and the description adds no information about parameters. It doesn't explain what 'datatype' means, possible values, or how it affects the inflation data fetched, 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 'Fetch inflation' restates the tool name 'inflation' with a generic verb 'Fetch', making it tautological. It doesn't specify what type of inflation data (e.g., CPI, PPI, country, time period) or from what source, nor does it distinguish from siblings like 'cpi' which might provide similar data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'cpi', 'real_gdp', 'unemployment') that might relate to economic indicators, the description offers no context, prerequisites, or comparisons to help an agent choose appropriately.

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. 'Fetch' implies a read operation, but the description doesn't specify data source, update frequency, rate limits, authentication needs, or return format. For a financial data tool with zero 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 extremely concise at just two words, with zero wasted language. It's front-loaded with the essential action and resource, though this brevity comes at the cost of completeness.

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 financial data tools, no annotations, no output schema, and low parameter documentation, the description is completely inadequate. It doesn't address what data is returned, formatting, time ranges, or how this tool fits within the broader financial data ecosystem represented by the many sibling 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?

The schema has 0% description coverage for the single parameter 'symbol', and the description provides no additional parameter information. It doesn't explain what 'symbol' represents (e.g., stock ticker format like 'AAPL'), valid values, or how it affects the fetched transactions. With low schema coverage, the description fails to compensate.

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 'Fetch insider transactions' clearly states the action (fetch) and resource (insider transactions), providing basic purpose. However, it doesn't specify what constitutes 'insider transactions' (e.g., stock trades by executives) or distinguish this tool from potential siblings like 'company_overview' or 'balance_sheet' that might contain related financial data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for financial data (like company_dividends, earnings_calendar, stock_quote), there's no indication of whether this tool is for real-time data, historical analysis, or regulatory filings, nor any prerequisites or exclusions 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?

No annotations are provided, so the description carries the full burden. 'Fetch' implies a read operation, but it doesn't disclose behavioral traits such as data freshness, rate limits, authentication needs, or what the return format looks like (e.g., date range, fields included). This leaves significant gaps for an agent to understand how to interact with it effectively.

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 just two words ('Fetch IPO calendar'), front-loaded with the key action and resource. There is no wasted language, making it efficient and easy to parse for an AI agent.

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 financial data tools and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the IPO calendar includes (e.g., dates, companies, status), how results are structured, or any limitations. For a tool in a server with many similar siblings, more context is needed to ensure proper usage.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it correctly avoids mentioning any. A baseline of 4 is appropriate as it doesn't mislead or omit necessary parameter 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 'Fetch IPO calendar' clearly states the action (fetch) and resource (IPO calendar), providing a specific purpose. However, it doesn't distinguish this tool from sibling tools like 'earnings_calendar' or 'company_earnings', which also fetch calendar data, so it misses full differentiation.

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 many sibling tools related to calendars and financial data (e.g., 'earnings_calendar', 'company_earnings'), there is no indication of context, prerequisites, or exclusions for usage.

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

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

The description provides no behavioral information beyond the basic purpose. With no annotations provided, it doesn't disclose whether this is a read-only operation, what data sources it uses, any rate limits, authentication requirements, error conditions, or what the output format looks like. For a financial data tool with 6 parameters, this leaves critical behavioral aspects unspecified.

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 maximally concise with just 4 words that directly state the tool's purpose. There's zero wasted language or unnecessary elaboration. While it's arguably too brief given the complexity of the tool, it's perfectly structured and front-loaded with the essential information.

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

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

Given the tool's complexity (6 parameters, financial calculations, no annotations, no output schema), the description is completely inadequate. It doesn't explain what the Kaufman adaptive moving average is, how it differs from other moving averages, what the parameters mean, what data it returns, or any behavioral characteristics. For users unfamiliar with this specific technical indicator, the description provides insufficient 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?

With 0% schema description coverage for all 6 parameters, the description carries the full burden of explaining parameter meaning. However, it provides no information about any parameters - not explaining what 'symbol', 'interval', 'month', 'time_period', 'series_type', or 'datatype' mean, their expected formats, or how they affect the calculation. This leaves all parameters completely 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 clearly states the verb ('fetch') and resource ('Kaufman adaptive moving average'), making the purpose specific and understandable. However, it doesn't differentiate this tool from its many siblings (e.g., sma, ema, dema, trima, wma) which also fetch moving averages, leaving room for confusion about when to choose this particular moving average type.

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 100+ sibling tools including many other technical indicators (sma, ema, rsi, macd, etc.), there's no indication of what makes the Kaufman adaptive moving average unique or when it's preferred over other moving averages or indicators.

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. 'Fetch listing status' gives no information about whether this is a read-only operation, what data sources it uses, rate limits, authentication requirements, or what format the output takes. It's completely inadequate for understanding 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 concise at just two words, which could be appropriate if it were informative. However, this brevity results in under-specification rather than efficient communication. While front-loaded, it fails to provide necessary context, making the conciseness more of a deficiency than a virtue.

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 has 3 undocumented parameters, no annotations, no output schema, and numerous similar siblings, the description is completely inadequate. It doesn't explain what the tool returns, how parameters interact, or when to choose it over alternatives. For a financial data tool with this complexity, much more context is needed.

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 3 parameters (symbol, date, state) with 0% description coverage, meaning none have explanations in the schema. The description 'Fetch listing status' adds no information about what these parameters mean, their expected formats, or how they affect the query. For example, it doesn't clarify if 'state' refers to a geographic region, market state, or something else.

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 'Fetch listing status' is a tautology that essentially restates the tool name 'listing_status' with a generic verb 'fetch'. It doesn't specify what kind of listing (stock, commodity, etc.), what status information is retrieved, or how it differs from similar tools like 'market_status' or 'stock_quote' in the sibling list. The purpose is vague and lacks differentiation.

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 'market_status', 'stock_quote', and various time series tools, there's no indication of context, prerequisites, or exclusions. Users must guess based on the name alone, which is insufficient for effective tool selection.

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