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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Get') but doesn't reveal if this is a read-only operation, requires authentication, has rate limits, or what the output format might be. For a tool with no annotations, this leaves critical behavioral traits unspecified, though it doesn't contradict any annotations.

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

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

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word contributes directly to stating the tool's purpose, earning its place 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 lack of annotations and output schema, the description is incomplete for a tool that likely returns complex data. It doesn't specify what 'detailed company information' entails (e.g., financials, profile, metrics), leaving the agent uncertain about the response format. With no structured fields to compensate, the description should do more to clarify the output and behavioral 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 100%, with the parameter 'symbol' fully documented in the schema as 'Stock symbol (e.g., AAPL, MSFT)'. The description doesn't add any extra meaning beyond this, such as explaining what 'detailed company information' includes or how the symbol is used. Given the high schema coverage, a baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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

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

The description clearly states the verb ('Get') and resource ('detailed company information'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get-stock-quote' or 'get-etf-profile', which might also retrieve company-related data, leaving some ambiguity about what specific information this tool 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 siblings. It doesn't mention alternatives like 'get-stock-quote' for price data or 'get-etf-profile' for ETF details, nor does it specify prerequisites such as needing a stock symbol. This lack of context makes it harder for an agent to choose correctly 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't specify whether it's historical or real-time, the data format, any rate limits, authentication needs, or error conditions. For a data-fetching tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes to understanding, with no wasted verbiage or redundancy.

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

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

Given the complexity of a time-series data tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'daily time series data' includes (e.g., OHLC prices, volume), the time range covered, data freshness, or return format. Without structured fields to compensate, the description should provide more context to guide 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 description doesn't add any parameter-specific information beyond what's in the input schema, which has 100% coverage with clear descriptions for 'symbol' and 'market'. Since schema coverage is high, the baseline is 3. The description implies the tool uses these parameters but doesn't explain their interaction or provide examples beyond the schema's 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 clearly states the action ('Get') and resource ('daily time series data for a cryptocurrency'), making the purpose immediately understandable. It distinguishes from siblings like 'get-crypto-exchange-rate' (single rate) and 'get-crypto-monthly' (different timeframe), though it doesn't explicitly mention these distinctions. The description is specific but could be more precise about what 'daily time series data' entails.

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 siblings like 'get-crypto-monthly' or 'get-crypto-weekly' for different timeframes, or 'get-time-series' which might be a more general tool. There's no context about use cases, prerequisites, or exclusions, 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Get' implies a read-only operation, it doesn't specify whether this is a real-time query, cached data, rate-limited, requires authentication, or what happens with invalid symbols. For a financial data tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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

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

The description is a single, efficient sentence that gets straight to the point. It's appropriately sized for a simple lookup tool and wastes no words. Every word earns its place by conveying the core functionality.

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 low complexity (2 parameters, no nested objects) and 100% schema coverage, the description is minimally adequate. However, with no output schema and no annotations, the description should ideally mention what format the exchange rate is returned in (e.g., number, object with timestamp) or any limitations. It's complete enough for basic understanding but could be more informative.

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

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

The input schema has 100% description coverage, with both parameters clearly documented in the schema itself. The description adds no additional parameter semantics beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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

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

The description clearly states the verb ('Get') and resource ('current cryptocurrency exchange rate'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'get-crypto-daily', 'get-crypto-weekly', and 'get-crypto-monthly' tools, which likely provide time-series data rather than current rates. The description is specific 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. It doesn't mention the sibling crypto tools (daily, weekly, monthly) or explain that this is for real-time/current rates rather than historical data. There's also no mention of prerequisites, limitations, or when not 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. It states what the tool does but doesn't add context beyond that—missing details like rate limits, authentication needs, data freshness, error handling, or what 'monthly time series data' entails (e.g., format, date range). For a 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 a single, efficient sentence that front-loads the core purpose without unnecessary words. It's appropriately sized for a simple tool, with zero waste or redundancy, 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 complexity (a data retrieval tool with no annotations and no output schema), the description is incomplete. It doesn't explain the return values, data format, or any behavioral traits, leaving gaps for an AI agent to understand how to interpret results. With 100% schema coverage but missing output details, it falls short of being fully helpful.

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 what the input schema provides. Schema description coverage is 100%, with clear documentation for 'symbol' and 'market' parameters, so the baseline is 3. The description doesn't elaborate on parameter usage, constraints, or examples, but the schema adequately covers the semantics.

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

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

The description clearly states the verb ('Get') and resource ('monthly time series data for a cryptocurrency'), making the purpose immediately understandable. It distinguishes from siblings like get-crypto-daily and get-crypto-weekly by specifying the monthly frequency. However, it doesn't explicitly differentiate from get-time-series, which might also handle cryptocurrency data, leaving minor ambiguity.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like get-crypto-daily or get-crypto-weekly for different frequencies, or get-crypto-exchange-rate for real-time data, nor does it specify prerequisites or exclusions. Usage is implied only by the tool name and description, lacking explicit 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 the full burden of behavioral disclosure. It mentions 'Get weekly time series data' but fails to describe key behaviors such as data format, time range, rate limits, authentication needs, or error handling. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding how it 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 a single, efficient sentence that directly states the tool's purpose without any unnecessary words or fluff. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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 time series data retrieval, lack of annotations, and absence of an output schema, the description is insufficient. It doesn't explain what the returned data includes (e.g., open, high, low, close values), the time period covered, or any limitations, leaving the agent with incomplete information for proper 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 description coverage is 100%, with clear descriptions for both parameters ('symbol' and 'market'), so the schema does the heavy lifting. The description adds no additional meaning beyond what's in the schema, such as examples of valid symbols or market currencies, but this is acceptable given the high schema coverage, resulting in a baseline score of 3.

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 ('Get') and resource ('weekly time series data for a cryptocurrency'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from its sibling 'get-crypto-daily' or 'get-crypto-monthly', which would require mentioning the specific weekly aggregation to earn 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 like 'get-crypto-daily' or 'get-crypto-monthly', nor does it mention any prerequisites or exclusions. It merely states what the tool does without context for selection.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'sorting capabilities' but doesn't cover other critical aspects: whether this is a read-only operation, rate limits, authentication needs, pagination behavior (beyond the 'limit' parameter), error handling, or data freshness. For a data-fetching tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It directly states what the tool does ('Get upcoming earnings calendar data for companies with sorting capabilities'), earning its place with zero waste. This is appropriately sized for the tool's complexity.

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 output schema, no annotations), the description is incomplete. It lacks details on behavioral traits (e.g., read-only nature, rate limits), output format, error conditions, and differentiation from siblings like 'get-historical-earnings'. Without annotations or an output schema, the description should provide more context to fully inform an agent, but it falls short.

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 100%, with all parameters well-documented in the input schema. The description adds minimal value beyond the schema, mentioning 'sorting capabilities' which aligns with 'sort_by' and 'sort_order' parameters but doesn't provide additional context like default behaviors or usage examples. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't significantly enhance parameter understanding.

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: 'Get upcoming earnings calendar data for companies with sorting capabilities'. It specifies the verb ('Get'), resource ('earnings calendar data'), and scope ('upcoming', 'for companies'), but doesn't explicitly differentiate from sibling tools like 'get-historical-earnings', which might handle different timeframes. The description is specific but lacks sibling distinction.

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 'get-historical-earnings' for past data or 'get-stock-quote' for real-time quotes, nor does it specify prerequisites or exclusions. Usage is implied through the description but not explicitly stated.

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

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

With no annotations provided, the description carries full burden but offers minimal behavioral disclosure. It mentions what information is returned but doesn't address critical aspects like data freshness, rate limits, authentication requirements, error conditions, or whether this is a real-time or cached data source. The description is functional but lacks 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 a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a simple lookup tool, though it could be slightly more front-loaded by starting with the most critical information about ETF data retrieval.

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 single-parameter lookup tool with no output schema, the description provides adequate context about what information is returned but lacks details about the return format, data structure, or potential limitations. Given the simplicity of the tool and good schema coverage, it's minimally viable but could benefit from more complete operational guidance.

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

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

Schema description coverage is 100% with the single 'symbol' parameter well-documented in the schema. The description adds no additional parameter information beyond what the schema provides, but doesn't need to compensate for gaps. The baseline 3 is appropriate when the schema adequately documents 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 action ('Get') and resource ('ETF profile information') with specific details about what information is included (holdings, sector allocation, key metrics). It distinguishes from sibling tools by focusing on ETFs rather than stocks, crypto, or earnings data, though it doesn't explicitly name 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 implies usage for ETF data retrieval, but provides no explicit guidance on when to use this tool versus alternatives like get-stock-quote or get-company-info for similar financial data needs. There's no mention of prerequisites, limitations, or specific scenarios where this tool is 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. It states what the tool does but doesn't describe how it behaves: no information about rate limits, authentication requirements, data freshness, error handling, or return format. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding operational behavior.

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

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

The description is a single, efficient sentence that communicates the core purpose without unnecessary words. It's appropriately sized for a straightforward data retrieval tool and front-loads 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 moderate complexity (retrieving financial data with filtering parameters), no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'historical earnings data' includes (e.g., EPS, revenue, dates), how results are structured, or any behavioral constraints. The agent would need to guess about the return format and operational behavior.

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

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

Schema description coverage is 100%, with all parameters well-documented in the schema itself. The description doesn't add any parameter information beyond what's already in the schema (e.g., it doesn't explain what 'historical earnings data' includes or how the limits work). Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the verb ('Get') and resource ('historical earnings data for a specific company'), making the purpose immediately understandable. It distinguishes from siblings like 'get-earnings-calendar' (future events) and 'get-stock-quote' (current price), though it doesn't explicitly mention these distinctions.

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. While the description implies it's for historical earnings, it doesn't specify when to choose this over 'get-company-info' (which might include earnings) or 'get-earnings-calendar' (which focuses on future earnings). No 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data but doesn't cover critical aspects like rate limits, authentication requirements, data freshness, error handling, or response format. For a data retrieval tool with 10 parameters, this leaves significant behavioral gaps.

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

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

The description is a single, efficient sentence that front-loads the core purpose ('Get historical options chain data for a stock') and adds a useful qualifier ('with advanced filtering and sorting capabilities'). Every word earns its place with zero waste or redundancy.

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

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

Given the complexity (10 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain what 'historical options chain data' entails, the response structure, data sources, limitations, or error scenarios. For a tool with rich filtering/sorting capabilities and no output schema, more context is needed 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?

The schema description coverage is 100%, so the schema already documents all 10 parameters thoroughly with descriptions, patterns, enums, and defaults. The description adds minimal value beyond the schema by mentioning 'advanced filtering and sorting capabilities', which aligns with parameters like filters and sort options but doesn't provide additional semantic context.

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

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

The description clearly states the verb ('Get') and resource ('historical options chain data for a stock'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get-realtime-options' or 'get-stock-quote', which would require a 5. The mention of 'advanced filtering and sorting capabilities' adds specificity but not sibling distinction.

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 'get-realtime-options' or 'get-stock-quote'. It mentions capabilities but doesn't specify use cases, prerequisites, or exclusions. This leaves the agent without contextual direction for 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 the full burden of behavioral disclosure. It states the tool retrieves 'realtime options chain data' but lacks details on rate limits, authentication needs, data freshness, or error handling. For a tool with real-time data and potential computational complexity (Greeks calculation), this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose ('Get realtime options chain data') and includes key features ('optional Greeks and filtering') without unnecessary words. Every part earns its place, making it highly concise and well-structured.

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

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

Given the complexity of real-time options data with Greeks calculation, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, data structure, or behavioral traits like latency or limitations. For a tool with 4 parameters and potential heavy computation, more context is needed to guide 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 100%, so the schema already documents all parameters thoroughly. The description adds minimal value by mentioning 'optional Greeks and filtering,' which loosely maps to 'require_greeks' and 'contract' but doesn't provide additional syntax, format, or usage context beyond the schema. This meets the baseline for high schema coverage.

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

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

The description clearly states the tool's purpose: 'Get realtime options chain data for a stock with optional Greeks and filtering.' It specifies the verb ('Get'), resource ('realtime options chain data'), and key features ('optional Greeks and filtering'), which distinguishes it from siblings like get-historical-options or get-stock-quote. However, it doesn't explicitly differentiate from all siblings (e.g., get-historical-options), keeping it from a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It mentions 'optional Greeks and filtering' but doesn't specify scenarios where this is preferred over other tools like get-historical-options or get-stock-quote. There's no mention of prerequisites, timing considerations, or exclusions, leaving usage context implied at best.

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 what the tool does but doesn't reveal any behavioral traits such as whether it's real-time or delayed, rate limits, authentication needs, error handling, or what format the quote information includes. 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 a single, clear sentence that front-loads the essential information ('Get current stock quote information'). There's no wasted words or unnecessary elaboration, making it efficient and easy to parse.

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 lack of annotations and output schema, the description is incomplete for a tool that likely returns complex financial data. It doesn't specify what 'quote information' includes (e.g., price, volume, timestamp), nor does it address potential behavioral aspects like data freshness or error cases. For a tool in a financial context with many siblings, 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 100% description coverage, with the single parameter 'symbol' clearly documented in the schema itself. The description doesn't add any additional meaning beyond what the schema provides, such as examples of valid symbols or constraints. Given the high schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('current stock quote information'), making it immediately understandable. However, it doesn't explicitly differentiate from siblings like 'get-company-info' or 'get-time-series' which might also provide stock-related data, 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 siblings like 'get-company-info' and 'get-time-series' that could overlap, there's no indication of when this specific quote-fetching tool is appropriate versus other data retrieval tools in the set.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets' data, implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, authentication needs, data freshness, or error handling. For a tool with no annotations, 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 a single, efficient sentence that front-loads the core purpose ('Get daily time series data for a stock') and adds a key constraint ('with optional date filtering'). There's no wasted language, and it's appropriately sized for the tool's complexity, making it easy for an agent 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 moderate complexity (5 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and hints at date filtering, but lacks details on behavioral aspects, usage context, and output format. Without annotations or an output schema, the description should do more to compensate, such as explaining the return data structure or typical use cases, leaving room for improvement.

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 minimal value beyond the input schema, which has 100% coverage. It mentions 'optional date filtering,' which aligns with the 'start_date' and 'end_date' parameters in the schema, but doesn't provide additional semantics like date format hints or interactions between parameters. Since the schema already fully describes all parameters, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

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: 'Get daily time series data for a stock with optional date filtering.' It specifies the verb ('Get'), resource ('daily time series data for a stock'), and scope ('optional date filtering'), which is clear and specific. However, it doesn't explicitly differentiate from sibling tools like 'get-stock-quote' or 'get-historical-earnings,' which might offer overlapping or related data, so it falls short of a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It mentions 'optional date filtering' but doesn't clarify scenarios where this is preferred over other tools like 'get-stock-quote' for real-time data or 'get-historical-earnings' for earnings-related time series. Without explicit when-to-use or when-not-to-use instructions, the agent lacks context for tool selection among siblings.

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