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

No annotations are provided, so the description carries full burden. It mentions 'list' (implying read-only) and scope details, but lacks critical behavioral information: authentication requirements, rate limits, pagination (given 'limit' parameter), data freshness, error handling, or output format. For a 9-parameter tool with no annotation coverage, this is insufficient.

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

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

Single sentence, front-loaded with core purpose, zero redundant words. Every element ('List aggregate bars', 'for a ticker', 'over a given date range', 'in custom time window sizes') contributes directly to understanding the tool's function.

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 high complexity (9 parameters, 5 required), no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It covers basic purpose but misses parameter explanations, behavioral context, output details, and sibling differentiation 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%, so the description must compensate. It only vaguely references 'ticker', 'date range', and 'custom time window sizes' (hinting at 'multiplier' and 'timespan'), leaving 6 other parameters (adjusted, limit, params, sort, from_, to) completely unexplained. The description adds minimal value beyond the schema's parameter names.

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 ('List aggregate bars') and target resource ('for a ticker'), with additional scope details ('over a given date range in custom time window sizes'). It distinguishes from siblings like 'get_daily_open_close_agg' by specifying custom time windows, but doesn't explicitly contrast with 'list_aggs' or other aggregation 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?

No explicit guidance on when to use this tool versus alternatives like 'get_daily_open_close_agg', 'get_grouped_daily_aggs', or 'list_aggs'. The description implies usage for time-series aggregation with custom windows but provides no context about prerequisites, limitations, or comparison to sibling tools.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what data is retrieved without mentioning critical behaviors like rate limits, authentication needs, data freshness (e.g., real-time vs. delayed), error handling, or whether it's a read-only operation. This leaves significant gaps for an AI agent to understand how to invoke it safely and 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 that front-loads the core functionality without any wasted words. It directly states the action and key inputs, 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 (financial data tool with 4 parameters), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't cover parameter details like 'adjusted' or 'params', behavioral aspects like data sources or limitations, or output format (e.g., JSON structure). This leaves the AI agent with insufficient information for reliable 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%, so the description must compensate. It mentions 'ticker and date' which maps to two of the four parameters (ticker, date), but ignores 'adjusted' and 'params'. For 'adjusted', it doesn't explain what adjustment means (e.g., for splits/dividends) or its default behavior. For 'params', it provides no context on its purpose or usage, leaving these 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 clearly states the verb 'Get' and specifies the resource 'daily open, close, high, and low' along with the required inputs 'ticker and date'. It distinguishes itself from siblings like get_previous_close_agg by focusing on a specific date's OHLC data rather than previous close. However, it doesn't explicitly differentiate from get_aggs or list_aggs which might offer similar aggregation 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 like get_aggs, get_previous_close_agg, or get_snapshot_ticker. It lacks context about prerequisites, such as market hours or data availability, and doesn't mention any exclusions or specific 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 the full burden of behavioral disclosure. It only states the action ('List') without any details on permissions, rate limits, pagination, response format, or whether it's read-only or mutative. For a tool with no annotations, 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 a single, efficient sentence with no wasted words. It's front-loaded and appropriately sized for a simple tool, 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 the complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'exchanges' entails, how parameters work, or what the output looks like. For a tool in a financial data context with many siblings, this leaves critical gaps.

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. With 3 parameters (asset_class, locale, params) and 0% schema description coverage, the schema provides only titles without explanations. The description fails to add any meaning, such as what these parameters filter or how they affect the listing.

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 'List exchanges known by Polygon.io' clearly states the action (list) and resource (exchanges), providing a basic purpose. However, it lacks specificity about what 'exchanges' means (e.g., stock, crypto, forex) and doesn't distinguish this tool from siblings like 'get_ticker_types' or 'list_tickers', which could also relate to exchange data. It's vague but not tautological.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools (e.g., 'get_market_status', 'list_tickers'), there's no indication of context, prerequisites, or exclusions. It's a generic list command without usage context.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states what the tool does, without mentioning any behavioral traits like authentication requirements, rate limits, error conditions, response format, or whether it's a read-only operation. This leaves critical operational context 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 just one sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it efficiently 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 complexity of a financial data tool with 3 parameters, no annotations, no output schema, and 0% schema description coverage, the description is insufficiently complete. It doesn't explain what details are returned, how to interpret results, or provide necessary operational context for proper 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?

With 0% schema description coverage and 3 parameters (ticker, as_of, params), the description provides minimal parameter context. It mentions 'at a specified point in time' which hints at the 'as_of' parameter, but doesn't explain the 'ticker' format, what 'params' might contain, or provide any examples. The description doesn't adequately 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 clearly states the verb ('Get details') and resource ('for a single futures contract'), making the purpose specific and understandable. It distinguishes from siblings like 'get_futures_product_details' by focusing on contracts rather than products, but doesn't explicitly mention how it differs from other contract-related tools like 'list_futures_contracts'.

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 single contract details (versus listing multiple contracts), it doesn't explicitly state this distinction or mention other contract-related tools like 'get_futures_snapshot' or 'list_futures_contracts' as alternatives.

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 implies a read-only operation ('Get details') but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'details' include (e.g., fields, format). For a tool with 4 parameters and no output schema, this leaves significant gaps in understanding how it 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 zero waste—front-loaded and to the point. Every word contributes to conveying the tool's purpose without redundancy or fluff.

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 (4 parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It lacks details on parameter usage, behavioral context, output format, and differentiation from siblings, making it insufficient for an agent to invoke the tool confidently.

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 but adds no parameter information. It mentions 'a specific day' which loosely relates to 'as_of', but doesn't explain 'product_code', 'params', or 'type', leaving 3 of 4 parameters undocumented. This fails to bridge the coverage gap 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 action ('Get details') and target resource ('a single futures product'), with the temporal constraint 'as it was at a specific day' adding specificity. However, it doesn't explicitly differentiate from sibling tools like 'get_futures_contract_details' or 'get_futures_snapshot', which likely serve related but distinct purposes.

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., 'get_futures_contract_details', 'get_futures_snapshot', 'list_futures_products'), the description lacks context about prerequisites, typical use cases, or comparisons to help the 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 must fully disclose behavioral traits. It only states the action without mentioning read/write nature, permissions, rate limits, output format, or pagination. This leaves the agent with no insight into how the tool behaves beyond its basic function.

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, short sentence, which is concise but under-specified. While it avoids verbosity, it lacks necessary detail, making it inefficient rather than appropriately sized. It is front-loaded but incomplete.

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 high complexity (15 parameters, 0% schema coverage, no output schema, no annotations), the description is severely incomplete. It does not explain parameter usage, behavioral aspects, or output, leaving the agent unable to use the tool effectively without guessing.

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% with 15 parameters, all undocumented in the schema. The description adds no parameter information, failing to explain what parameters like 'product_code_gt' or 'ticker_any_of' mean or how they affect results. It does not 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 'Get snapshots for futures contracts' restates the tool name with minimal elaboration, making it a tautology. It specifies the resource (futures contracts) and action (get snapshots) but lacks detail on what 'snapshots' entail or how it differs from sibling tools like get_snapshot_all or get_snapshot_ticker, 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. With multiple snapshot-related siblings (e.g., get_snapshot_all, get_snapshot_ticker), the description fails to indicate context, prerequisites, or exclusions, offering no help 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 only states what the tool does ('Get grouped daily bars'), without mentioning any behavioral traits such as whether it's a read-only operation, potential rate limits, authentication needs, or what the output looks like. For a tool with 6 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 a single, efficient sentence with no wasted words, making it appropriately concise. It's front-loaded with the core action, though it could be more structured if it included additional details. The brevity is a strength, but it borders on under-specification given 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 (6 parameters, 1 required, no output schema, and no annotations), the description is incomplete. It doesn't explain the parameters, output format, or behavioral aspects, making it inadequate for an agent to use the tool effectively. The lack of sibling differentiation and usage guidelines further reduces 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 schema description coverage is 0%, meaning none of the 6 parameters (e.g., 'adjusted', 'include_otc', 'locale', 'market_type', 'params', 'date') are explained in the schema. The description adds no meaning beyond the schema, failing to compensate for this gap. It doesn't clarify what any parameter does or how they affect the 'grouped daily bars,' leaving all 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 states the tool 'Get[s] grouped daily bars for entire market for a specific date,' which provides a basic verb+resource+scope. However, it's vague about what 'grouped daily bars' and 'entire market' mean, and it doesn't distinguish this tool from siblings like 'get_aggs' or 'list_aggs,' which seem related to aggregates. The purpose is understandable but lacks specificity and 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 offers no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or comparisons to sibling tools like 'get_aggs' or 'get_daily_open_close_agg,' leaving the agent to guess based on the name alone. There's no explicit or implied context 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 carries the full burden of behavioral disclosure. The description only states what the tool does at a high level without any information about rate limits, authentication requirements, data freshness, error conditions, or what format the trade data will be returned in. This is inadequate for a tool that presumably makes external API calls.

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 one sentence with no wasted words. It's front-loaded with the core purpose and uses clear, direct language. While it's arguably too brief given the tool's complexity, it earns full marks for conciseness.

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 3 parameters, 0% schema coverage, no annotations, and no output schema, the single-sentence description is completely inadequate. It doesn't explain what data will be returned, how to interpret parameters, what the tool's limitations are, or how it differs from similar sibling tools. 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?

With 0% schema description coverage and three parameters (from_, to, params), the description provides no information about what these parameters mean, what format they should be in, or what values are acceptable. The description mentions 'crypto pair' which hints at the relationship between from_ and to, but doesn't explain the params parameter at all.

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 ('most recent trade for a crypto pair'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_last_trade' or 'get_last_forex_quote', which appear to serve similar functions for different asset classes.

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 multiple sibling tools that appear related (e.g., 'get_last_trade', 'get_last_forex_quote', 'get_snapshot_crypto_book'), there's no indication of when this specific crypto trade tool is appropriate versus other market data 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 full burden for behavioral disclosure. It states only what the tool does ('get'), not how it behaves - no information about rate limits, authentication needs, data freshness, error conditions, or what 'most recent' means (real-time? last recorded?). This leaves critical behavioral aspects 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 maximally concise - a single sentence with no wasted words. It's front-loaded with the core purpose. While it's too brief to be helpful, it achieves perfect conciseness by stating only the essential action without any fluff.

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 3 parameters, no annotations, no output schema, and 0% schema description coverage, the description is completely inadequate. It doesn't explain what data is returned, how parameters work, behavioral constraints, or differentiation from similar tools. The minimal description fails to provide the context needed 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?

With 0% schema description coverage and 3 parameters (from_, to, params), the description provides no parameter information whatsoever. It doesn't explain what 'from_' and 'to' represent (currency codes? symbols?), what format they should be in, or what the optional 'params' object might contain. 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 'Get the most recent forex quote' clearly states the action (get) and resource (forex quote), but it's vague about scope and doesn't differentiate from siblings like 'get_last_quote' or 'get_real_time_currency_conversion'. It specifies 'forex' which helps somewhat, but lacks precision about what constitutes a 'quote' (bid/ask? mid? volume?).

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 on when to use this tool versus alternatives is provided. With many sibling tools dealing with quotes, trades, and currency data, the description doesn't indicate if this is for real-time data, historical data, or how it differs from 'get_last_quote' or 'get_real_time_currency_conversion'. No 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action without mentioning any behavioral traits like data freshness, rate limits, authentication needs, error handling, or response format. This is inadequate for a tool with no 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 a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently conveys the core purpose 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 financial data retrieval, no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on behavior, parameter usage, output format, and differentiation from siblings, making it insufficient for an AI agent to use the tool effectively without additional context.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'ticker symbol' which aligns with the 'ticker' parameter, but does not explain the 'params' parameter (which can be an object or null) or provide any additional semantics, format examples, or constraints for either parameter.

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

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

The description clearly states the verb 'Get' and the resource 'most recent quote for a ticker symbol', making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_last_trade' or 'get_last_forex_quote', which might retrieve similar data for different asset types, so it 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, such as 'get_last_trade' for trades or 'list_quotes' for multiple quotes. It implies usage for ticker symbols but does not specify contexts, exclusions, or prerequisites, leaving the agent to infer based on the name alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('Get the most recent trade') without any information on permissions, rate limits, error handling, or what the return format looks like. 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 a single, clear sentence with no wasted words. It is front-loaded with the core purpose, making it highly efficient and easy to parse, which is ideal for conciseness.

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, 0% schema description coverage, and no output schema, the description is insufficient. It does not provide enough context for the agent to understand behavioral traits, parameter details, or return values, making it incomplete for practical 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 are undocumented in the schema. The description mentions 'ticker symbol', which aligns with the 'ticker' parameter, but it does not explain the 'params' parameter at all. This partial coverage 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 clearly states the tool's purpose with a specific verb ('Get') and resource ('most recent trade for a ticker symbol'), making it immediately understandable. However, it does not explicitly differentiate from sibling tools like 'get_last_crypto_trade' or 'get_last_quote', which reduces its score from a perfect 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools available (e.g., 'get_last_crypto_trade', 'get_last_quote', 'list_trades'), there is no indication of context, prerequisites, or exclusions, leaving the agent to infer usage based on the name alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions retrieving 'upcoming' holidays and 'open/close times', which implies read-only behavior and temporal scope, but lacks details on permissions, rate limits, response format, or error handling. For a tool with zero annotation coverage, this is insufficient.

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

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

The description is a single, efficient sentence that front-loads the core functionality ('Get upcoming market holidays and their open/close times') with zero wasted words. It's appropriately sized for the tool's apparent simplicity.

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 covers the basic purpose but lacks essential details like parameter usage, behavioral traits, or return values, making it inadequate for reliable agent invocation in a complex financial data context.

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

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

Schema description coverage is 0%, with one parameter ('params') documented only as an object or null with a default. The description adds no information about parameters, such as what 'params' might include (e.g., date ranges, market identifiers) or how to use them. It 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 clearly states the tool's purpose with a specific verb ('Get') and resource ('upcoming market holidays and their open/close times'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_market_status' or 'get_futures_schedules', which might also involve market timing information, 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. With many sibling tools related to market data (e.g., 'get_market_status', 'get_futures_schedules'), there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on the name alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'current trading status' which implies real-time or near-real-time data, but doesn't specify update frequency, rate limits, authentication requirements, or what 'status' includes (e.g., open/closed, hours, holidays). For a tool with no annotation coverage, 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 extremely concise with just one sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration. It's appropriately sized for a simple tool 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 complexity of financial market data and the lack of annotations, output schema, and parameter documentation, the description is incomplete. It doesn't explain what 'trading status' means, what data is returned, how current the information is, or any limitations. With no structured fields to rely on, the description should provide more context 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?

The input schema has one parameter ('params') with 0% description coverage and no documentation in the schema. The description provides no information about parameters, not even mentioning that parameters are optional (as indicated by required parameters: 0). With 0% schema coverage, the description doesn't compensate for the lack of parameter documentation, but since there's only one optional parameter, the baseline remains at 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 tool's purpose as 'Get current trading status of exchanges and financial markets' with a specific verb ('Get') and resource ('trading status of exchanges and financial markets'). However, it doesn't explicitly differentiate from sibling tools like 'get_market_holidays' or 'list_futures_market_statuses', which might provide related but different information.

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 (e.g., 'get_market_holidays', 'list_futures_market_statuses'), there's no indication of how this tool differs or when it's the appropriate choice. The description only states what it does, not when 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 the tool retrieves data ('Get'), implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, or details the return format (e.g., JSON structure, error handling). For a tool with no 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 functionality, making it easy to understand at a glance. There's no wasted text, and it's appropriately sized for the simple operation described.

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 3 parameters), no annotations, 0% schema description coverage, and no output schema, the description is incomplete. It covers the basic purpose but lacks details on parameters, behavioral traits, return values, and differentiation from siblings, making it inadequate for full contextual understanding.

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 'specific ticker', which maps to the required 'ticker' parameter, but doesn't explain the 'adjusted' or 'params' parameters. With 0% schema description coverage and 3 total parameters (1 required, 2 optional), the description fails to compensate for the lack of schema details, leaving most parameters undocumented and their purposes unclear.

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

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

The description clearly states the tool's purpose: 'Get previous day's open, close, high, and low for a specific ticker.' It specifies the verb ('Get'), resource ('previous day's open, close, high, and low'), and target ('specific ticker'). However, it doesn't explicitly differentiate from sibling tools like 'get_daily_open_close_agg' or 'get_aggs', which likely provide similar 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. It doesn't mention prerequisites, exclusions, or compare it to sibling tools such as 'get_daily_open_close_agg' or 'get_aggs', which might offer overlapping or related functionality. Usage is implied by the purpose 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('Get real-time currency conversion') without details on permissions, rate limits, data sources, or output format. This is insufficient for a tool with potential real-time data implications.

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 sentence ('Get real-time currency conversion.'), which is front-loaded and wastes no words. It efficiently states the core purpose 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 (real-time data conversion), lack of annotations, 0% schema coverage, no output schema, and five parameters, the description is incomplete. It fails to provide necessary context on behavior, parameters, or output, making it inadequate 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%, so the description must compensate for all parameters. It mentions 'currency conversion' but does not explain the five parameters (e.g., 'from_', 'to', 'amount', 'precision', 'params'), their roles, or expected formats. This leaves parameters largely undocumented.

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

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

The description states the tool's purpose ('Get real-time currency conversion'), which is clear but vague. It specifies the verb ('Get') and resource ('currency conversion'), but lacks detail on scope or differentiation from siblings like 'get_last_forex_quote'. It's not tautological but remains generic.

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, nor does it reference sibling tools. This leaves the agent without 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 mentions 'Get a snapshot' which implies a read-only operation, but doesn't specify data freshness, rate limits, authentication needs, or output format. This leaves critical behavioral traits undefined for a tool with multiple 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 no wasted words, making it front-loaded and easy to parse. However, it's overly concise given the tool's complexity, sacrificing necessary detail 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 tool has 4 parameters with 0% schema coverage, no annotations, no output schema, and multiple sibling tools, the description is incomplete. It doesn't address parameter usage, behavioral constraints, or differentiation from alternatives, leaving significant gaps 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 for undocumented parameters. It doesn't explain any of the 4 parameters (e.g., what 'market_type' values are valid, how 'tickers' interacts with 'all', what 'params' object contains, or the meaning of 'include_otc'). This fails to add meaning 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 states the tool 'Get a snapshot of all tickers in a market' which provides a clear verb ('Get') and resource ('snapshot of all tickers'), but it's vague about what a 'snapshot' entails (e.g., price data, volume, etc.). It doesn't differentiate from sibling tools like 'get_snapshot_ticker' or 'list_universal_snapshots', leaving ambiguity about scope and 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?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'get_snapshot_ticker' (likely for single tickers) and 'list_universal_snapshots' (possibly broader), the description lacks context on use cases, prerequisites, or exclusions, offering no help in 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. It states the tool gets a snapshot but doesn't disclose behavioral traits such as whether it's a read-only operation, requires authentication, has rate limits, returns real-time or historical data, or what format the snapshot includes. For a tool with no annotations, this leaves critical gaps in understanding how it 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 and directly states the tool's purpose, 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 no annotations, 0% schema coverage, no output schema, and 2 parameters (one required, one optional), the description is incomplete. It doesn't explain the tool's behavior, parameter usage, or return values, making it inadequate for an agent to use this tool effectively without additional context.

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

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

Schema description coverage is 0%, so the schema provides no parameter details. The description mentions 'crypto ticker' but doesn't explain what 'ticker' means (e.g., symbol format like BTC-USD) or what 'params' is for (e.g., optional filters or settings). It adds minimal value beyond the schema, 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 clearly states the action ('Get snapshot') and resource ('crypto ticker's order book'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_snapshot_all' or 'get_snapshot_ticker', which appear to be related snapshot tools, so it doesn't fully distinguish 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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools like 'get_snapshot_all' and 'get_snapshot_ticker', the description lacks any context about when this specific crypto order book snapshot is appropriate, 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 but offers minimal behavioral insight. It does not disclose if this is a read/write operation, rate limits, authentication needs, or what the output looks like (e.g., list format, timestamps). The phrase 'Get' implies a read operation, but lacks details on data freshness or 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 extremely concise with a single sentence, 'Get gainers or losers for a market.', which is front-loaded and wastes no words. However, this brevity contributes to underspecification rather than effective communication.

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 (4 parameters, 0% schema coverage, no annotations, no output schema), the description is severely incomplete. It does not explain the tool's behavior, parameter usage, or output, making it inadequate for an AI agent to invoke the tool correctly without external knowledge.

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 provides no information about the 4 parameters (direction, include_otc, market_type, params). It does not explain what values 'direction' accepts (e.g., 'gainers' vs 'losers'), what 'market_type' refers to, or the purpose of 'params'. 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 'Get gainers or losers for a market' states a vague purpose without specifying what 'gainers or losers' means (e.g., stocks, assets, price movements) or what 'snapshot' entails. It partially distinguishes from siblings like 'get_snapshot_all' by implying direction-based filtering, but lacks specificity about the resource or data format.

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., 'get_snapshot_all', 'get_snapshot_ticker'), the description fails to indicate scenarios, prerequisites, or exclusions, leaving the agent 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 must fully disclose behavior. It only states the action without details on permissions, rate limits, data freshness, or output format (e.g., real-time vs. historical). For a financial data tool with potential complexity, 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, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core action, though this brevity contributes to gaps in other dimensions. Every word earns its place, making it structurally sound.

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 data tool with 3 parameters, 0% schema coverage, no annotations, no output schema), the description is severely incomplete. It doesn't address behavior, parameter meanings, or output, failing to provide enough context for effective use by an AI agent.

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

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

Schema description coverage is 0%, so parameters are undocumented in the schema. The description adds no meaning beyond the tool name, failing to explain what 'option_contract', 'underlying_asset', or 'params' represent (e.g., ticker symbols, configuration options). This leaves parameters ambiguous 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 states the verb 'Get' and resource 'snapshot for a specific option contract', which clarifies the basic purpose. However, it's vague about what a 'snapshot' entails (e.g., price data, volume, Greeks) and doesn't differentiate from sibling tools like 'get_snapshot_all' or 'get_snapshot_ticker', 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 many sibling tools (e.g., 'get_snapshot_all', 'get_futures_snapshot'), the description lacks context for selection, such as specifying it's for options only or comparing to other snapshot tools. This omission reduces usability in a crowded toolset.

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 'Get snapshot' but doesn't clarify 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 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 one sentence: 'Get snapshot for a specific ticker.' It is front-loaded and wastes no words, making it easy to parse quickly. However, 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?

Given the complexity (3 parameters, no annotations, no output schema, and many sibling tools), the description is incomplete. It doesn't explain what a snapshot entails, how it differs from other tools, parameter meanings, or behavioral aspects. 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?

Schema description coverage is 0%, so the schema provides no parameter descriptions. The tool description mentions 'a specific ticker' but doesn't explain the three parameters (market_type, params, ticker) or their semantics. It fails to compensate for the lack of schema documentation, leaving parameters largely undefined.

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's purpose as 'Get snapshot for a specific ticker', which is clear but vague. It specifies the verb 'Get' and resource 'snapshot', but doesn't explain what a 'snapshot' contains or how it differs from sibling tools like get_ticker_details or get_snapshot_all. The purpose is understandable 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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., get_ticker_details, get_snapshot_all, get_snapshot_option), the description doesn't indicate scenarios where this tool is preferred, such as for real-time data versus historical aggregates. This leaves the agent without context 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. The description only states what the tool does ('Get detailed information'), but doesn't disclose any behavioral traits such as whether it's a read-only operation, if it requires authentication, rate limits, error handling, or what format the 'detailed information' returns. 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 with a single sentence: 'Get detailed information about a specific ticker.' It's front-loaded and wastes no words, making it easy to parse. 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?

Given the complexity (3 parameters, no schema descriptions, no annotations, no output schema), the description is completely inadequate. It doesn't explain what 'detailed information' entails, how parameters interact, or behavioral aspects. For a tool that likely returns financial data with multiple parameters, this minimal description leaves critical gaps for an AI agent 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 three parameters (ticker, date, params) have descriptions in the schema. The description adds no information about what these parameters mean, how they should be used, or what 'detailed information' includes. For example, it doesn't explain what 'params' expects or how 'date' affects the output. 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 'Get detailed information about a specific ticker' clearly states the verb ('Get') and resource ('detailed information about a specific ticker'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_snapshot_ticker' or 'list_tickers', which likely provide similar or overlapping functionality. The purpose is clear 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 like 'get_snapshot_ticker', 'list_tickers', and 'get_ticker_types', there's no indication of what makes this tool unique or when it should be preferred. No usage context, exclusions, or alternatives 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. It states this is a list operation, implying it's read-only, but doesn't disclose any behavioral traits like rate limits, authentication needs, response format, pagination, or error handling. For a tool with no annotation coverage, this is insufficient.

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

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

The description is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose 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 (3 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 the output, or any behavioral context, making it inadequate 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 3 parameters (asset_class, locale, params) are documented in the schema. The description adds no information about these parameters, failing to compensate for the coverage gap. This leaves the agent with no semantic understanding of the inputs.

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 ('List') and resource ('all ticker types supported by Polygon.io'), making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from its many siblings (like 'get_exchanges' or 'list_tickers'), 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 numerous sibling tools available (e.g., 'get_exchanges', 'list_tickers'), there's no indication of context, prerequisites, or exclusions 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. While 'iterate through' suggests a read-only operation, it doesn't specify whether this is a streaming operation, how results are paginated, rate limits, authentication requirements, or what format the aggregate bars are returned in. For a tool with 9 parameters and no annotations, 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 extremely concise at just one sentence with no wasted words. It's front-loaded with the core functionality and efficiently communicates the basic operation. Every word earns its place in this minimal 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?

For a tool with 9 parameters, no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain what 'aggregate bars' are, how they're structured, what the iteration returns, or how to interpret the various parameters. The agent would struggle to use this tool effectively without significant trial and error or external knowledge.

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

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

With 0% schema description coverage and 9 parameters (5 required), the description provides minimal parameter guidance. It mentions 'ticker' and 'date range' (implied by 'from_' and 'to'), but doesn't explain the purpose of 'multiplier', 'timespan', 'adjusted', 'limit', 'sort', or 'params'. The description fails to compensate for the complete lack of schema descriptions, leaving most parameters semantically unclear.

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

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

The description clearly states the action ('iterate through') and resource ('aggregate bars for a ticker') with a scope ('over a given date range'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_aggs' or 'list_futures_aggregates', which appear to serve similar aggregate data retrieval functions.

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 like 'get_aggs', 'list_futures_aggregates', and 'get_grouped_daily_aggs' that likely retrieve similar financial data, the agent receives no help in selecting the appropriate tool for different scenarios or understanding this tool's specific use case.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action 'list' without any details on permissions, rate limits, pagination, or response format. For a tool with 45 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 sentence, which is concise but under-specified. It lacks structure and does not front-load critical information, making it inefficient for understanding the tool's purpose or usage beyond the bare minimum.

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 high complexity (45 parameters, 0% schema coverage, no annotations, no output schema), the description is completely inadequate. It does not address behavioral traits, parameter meanings, or output expectations, 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?

Schema description coverage is 0%, meaning none of the 45 parameters are documented in the schema. The description adds no information about parameters, such as their purposes, relationships, or usage 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 'List Benzinga analyst insights' restates the tool name with minimal elaboration, making it a tautology. It specifies the verb 'list' and resource 'Benzinga analyst insights' but lacks detail on scope or differentiation from siblings like 'list_benzinga_analysts' or 'list_benzinga_ratings', 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. The description does not mention any context, prerequisites, or exclusions, and it fails to distinguish this tool from sibling tools like 'list_benzinga_analysts' or 'list_benzinga_ratings', 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 the full burden of behavioral disclosure. It fails to describe any traits such as whether it's read-only, paginated, rate-limited, or what the output format is. The description is too vague to inform the agent about how the tool behaves beyond a basic listing action.

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

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

The description is extremely concise with a single sentence, 'List Benzinga analysts.', which is front-loaded and wastes no words. However, this conciseness comes at the cost of under-specification, but per the scoring rules, it earns a high score 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 high complexity (27 parameters, no annotations, no output schema), the description is completely inadequate. It does not explain the tool's purpose in depth, parameter usage, behavioral traits, or output, 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?

With 27 parameters and 0% schema description coverage, the schema provides only titles without explanations. The description adds no information about parameters, such as what 'benzinga_firm_id_gt' means or how 'limit' and 'sort' work, 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 'List Benzinga analysts' restates the tool name with minimal elaboration, making it a tautology. It specifies the resource ('Benzinga analysts') but lacks a clear verb beyond 'List' and provides no detail on scope, format, or what 'listing' entails, failing to distinguish it from sibling tools like 'list_benzinga_firms' or 'list_benzinga_analyst_insights'.

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 does not mention prerequisites, context, or exclusions, and with 27 parameters, it offers no help on filtering or when to choose it over other list tools like 'list_tickers' or 'list_benzinga_news', 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 carries the full burden of behavioral disclosure. It states it's a list operation, implying read-only behavior, but doesn't cover critical aspects like rate limits, authentication needs, pagination, error handling, or what the output looks like (e.g., format, fields). For a tool with 8 parameters and no output schema, this is a significant gap.

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

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

The description is extremely concise—a single sentence with no wasted words. It's front-loaded with the core purpose, making it easy to scan, though this brevity 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 the complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain parameter usage, behavioral traits, or output format, leaving the agent with insufficient information to use the tool effectively beyond a basic understanding of its purpose.

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 only mentions 'ticker' and doesn't explain any other parameters (e.g., date filters, limit, params), leaving them completely undocumented. This 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 clearly states the verb ('List') and resource ('Benzinga consensus ratings for a ticker'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_benzinga_ratings' or 'list_benzinga_analyst_insights', which likely provide related but different data, so it misses full 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. There are many sibling tools for financial data (e.g., 'list_benzinga_ratings', 'list_benzinga_analyst_insights'), but the description doesn't specify what makes consensus ratings unique or when to prefer this tool 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 must fully disclose behavioral traits. It offers no information on safety (e.g., read-only vs. destructive), permissions, rate limits, pagination, or output format. The description is too minimal to convey any behavioral context, leaving the agent uninformed.

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, under-specified sentence that lacks necessary detail, making it inefficient rather than concise. It does not front-load key information and wastes the opportunity to provide value, as it is too brief 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 high complexity (57 parameters), no annotations, no output schema, and 0% schema coverage, the description is completely inadequate. It fails to address purpose, usage, behavior, or parameters, leaving the agent unable to effectively select or invoke the tool.

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

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

With 57 parameters and 0% schema description coverage, the schema provides only titles without explanations. The description adds no parameter semantics, failing to explain what parameters like 'date_gt', 'eps_surprise_percent', or 'limit' do or how they filter earnings data, leaving all 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 'List Benzinga earnings' restates the tool name with minimal elaboration, making it a tautology. It lacks specificity about what 'earnings' entails (e.g., earnings reports, data, announcements) and does not differentiate from sibling tools like 'list_benzinga_news' or 'list_stock_financials', 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?

There is no guidance on when to use this tool versus alternatives. The description does not mention context, prerequisites, or exclusions, and it fails to reference any sibling tools (e.g., 'list_benzinga_news' for news or 'list_stock_financials' for financial data), providing 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 the full burden of behavioral disclosure. The description 'List Benzinga firms' reveals nothing about whether this is a read-only operation, whether it has side effects, what authentication might be required, rate limits, pagination behavior, error conditions, or response format. For a tool with 9 parameters and no annotation coverage, this is completely inadequate 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 maximally concise at just three words. While this represents severe under-specification rather than ideal conciseness, from a pure structural perspective, there is zero wasted language and the description is front-loaded with the core action. Every word earns its place, even though there are far too few words for adequate documentation.

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 (9 parameters, no schema descriptions, no annotations, no output schema) and the fact this appears to be part of a financial data API with many similar listing tools, the description is completely inadequate. It provides no context about what 'Benzinga firms' are, how they differ from regular firms/tickers, what data is returned, how results are filtered/sorted, or how this tool relates to the many other list_* tools in the sibling set.

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 9 parameters have descriptions in the schema. The tool description provides absolutely no information about any parameters - not what they do, not which are required, not how they interact, not what 'Benzinga_id_gt' versus 'Benzinga_id_gte' means, not what the 'params' object should contain. With 9 undocumented parameters and no compensation in the description, this is a severe deficiency.

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 'List Benzinga firms' is a tautology that essentially restates the tool name. It provides no additional specificity about what 'firms' means in this context or what distinguishes this listing operation from other list_* tools in the sibling set. While it does include the verb 'List' and resource 'Benzinga firms', it lacks any distinguishing details about scope, format, or 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 9 sibling tools that also begin with 'list_' (like list_tickers, list_trades, list_quotes), there is no indication of what makes 'Benzinga firms' different or when this specific listing operation is appropriate. The description offers no context about prerequisites, typical use cases, or relationships to other tools.

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

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

The description provides zero behavioral information beyond the basic 'List' action. With no annotations provided, the description carries the full burden but fails to disclose any behavioral traits: no information about pagination, rate limits, authentication requirements, data freshness, error conditions, or what constitutes 'guidance' in the response. For a tool with 45 parameters and complex filtering capabilities, this is a critical omission.

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 three words. While this is technically efficient, it represents under-specification rather than effective conciseness. For a tool with 45 parameters and complex functionality, this brevity is inadequate. However, it is front-loaded with the core action and resource, so it earns a baseline score rather than a lower one for being verbose or poorly structured.

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

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

The description is completely inadequate given the tool's complexity. With 45 parameters, 0% schema description coverage, no annotations, no output schema, and numerous sibling tools, the description provides only the most basic functional statement. It doesn't explain what 'guidance' means, how to filter results, what the response contains, or when to use this versus other data sources. For such a complex tool, this minimal description fails to provide the 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?

With 45 parameters and 0% schema description coverage, the description provides absolutely no information about any parameters. The schema shows complex filtering parameters (date ranges, fiscal periods, importance levels, ticker filters), but the description doesn't mention any filtering capabilities, required parameters, or how to use the extensive filtering options. The description fails completely to compensate for the schema's 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 'List Benzinga guidance' is a tautology that essentially restates the tool name. It provides the verb 'List' and resource 'Benzinga guidance', but lacks specificity about what 'guidance' means in this context (e.g., earnings guidance, analyst guidance, financial forecasts). It doesn't distinguish this tool from its many sibling tools that also list various financial data types.

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

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

The description provides absolutely no guidance about when to use this tool versus alternatives. With 45 sibling tools on the server including other Benzinga data tools (analyst insights, consensus ratings, earnings, news, ratings), there's no indication of when this specific guidance listing tool is appropriate versus those other data sources. No prerequisites, constraints, or comparison information is provided.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It fails to describe any traits such as whether it's read-only, requires authentication, has rate limits, returns paginated results, or what the output format might be, making it inadequate for a tool with 30 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 concise with a single sentence, it's under-specified rather than efficiently informative. The description lacks front-loaded critical details and doesn't earn its place by adding value beyond the tool name, making it ineffective 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 high complexity (30 parameters, 0% schema coverage, no annotations, no output schema), the description is completely inadequate. It doesn't address behavioral aspects, parameter meanings, or usage context, failing to provide the necessary information 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 30 parameters are documented in the schema. The description adds no information about parameters, failing to compensate for the coverage gap or explain what fields like 'author_gt' or 'tickers_any_of' mean, leaving them entirely 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 'List Benzinga news' restates the tool name with minimal elaboration, making it a tautology. It specifies the resource ('Benzinga news') but lacks a specific verb beyond 'List' and doesn't differentiate from sibling tools like 'list_ticker_news' or other Benzinga-related tools (e.g., 'list_benzinga_analyst_insights'), 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. It doesn't mention any prerequisites, context, or exclusions, nor does it reference sibling tools like 'list_ticker_news' for comparison, leaving the agent with no usage instructions.

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 fails to mention any aspects like read-only vs. destructive operations, authentication needs, rate limits, pagination, or response format. The single sentence offers no behavioral context 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?

While concise with a single sentence, the description is under-specified rather than efficiently informative. It lacks front-loaded critical details and fails to provide necessary context, making it ineffective despite its brevity. Every sentence should earn its place, but this one adds minimal value beyond the tool name.

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

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

Given the high complexity (57 parameters, no annotations, no output schema, and 0% schema coverage), the description is completely inadequate. It does not compensate for the lack of structured data, leaving the tool's functionality, behavior, and usage opaque. A list operation with many filtering options requires much more explanation to be usable.

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 57 parameters and 0% schema description coverage, the schema provides only titles without explanations. The description adds no information about parameters, such as their purposes, relationships (e.g., filtering by analyst ID or date ranges), or usage examples. This leaves all parameters semantically undocumented, severely hindering effective tool 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 'List Benzinga ratings' restates the tool name with minimal elaboration, making it a tautology. It lacks specificity about what 'ratings' entail (e.g., financial analyst ratings, stock ratings) and does not differentiate from sibling tools like 'list_benzinga_consensus_ratings', leaving the purpose vague and under-defined.

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 sibling tools like 'list_benzinga_consensus_ratings' or other data retrieval tools. The description offers no context, prerequisites, or exclusions, 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 carries full burden for behavioral disclosure. The description only states it 'lists' conditions but reveals nothing about permissions needed, rate limits, pagination behavior, response format, or whether this is a read-only operation. 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 maximally concise at just 5 words: 'List conditions used by Polygon.io.' It's front-loaded with the core action and resource. There's no wasted language or unnecessary elaboration. While under-specified, what's present is structurally 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 5 parameters with 0% schema coverage, no annotations, no output schema, and 56 sibling tools, the description is completely inadequate. It doesn't explain what 'conditions' are, how to use the parameters, what the tool returns, or when to choose it over alternatives. 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?

With 5 parameters and 0% schema description coverage, the description provides zero information about what 'asset_class', 'data_type', 'id', 'params', or 'sip' mean in this context. The schema only provides titles without descriptions, and the description doesn't mention parameters at all. 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 'List conditions used by Polygon.io' states a clear verb ('List') and resource ('conditions'), but it's vague about what 'conditions' are in this financial data context. It doesn't differentiate from sibling tools like 'list_tickers' or 'list_exchanges' that also list resources. The purpose is understandable but lacks specificity about the domain.

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 56 sibling tools on the server, there's no indication of when 'conditions' are relevant compared to other list operations like 'list_tickers' or 'list_exchanges'. The agent receives no usage context, prerequisites, or exclusions.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what data is retrieved ('historical cash dividends') without any information about permissions required, rate limits, pagination behavior, data freshness, error conditions, or what format the data returns. For a data retrieval tool with 6 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 3 words, with zero wasted language. It's front-loaded with the core purpose and contains no unnecessary elaboration. While this conciseness comes at the cost of completeness, the description itself is structurally optimal for its 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 (6 parameters, no annotations, no output schema, 0% schema description coverage), this description is completely inadequate. A tool with multiple filtering parameters and no structured documentation needs a description that explains parameter usage, return format, and behavioral constraints. The current description provides none of this essential context.

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

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

With 0% schema description coverage and 6 parameters, the description provides no information about any parameters. The schema shows parameters like 'dividend_type', 'ex_dividend_date', 'frequency', 'limit', 'params', and 'ticker', but the description doesn't mention any of them, explain their purposes, or provide examples of valid values. This leaves the agent with no guidance on how to use the tool effectively.

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 'Get historical cash dividends' clearly states the verb ('Get') and resource ('historical cash dividends'), making the tool's purpose immediately understandable. It doesn't explicitly distinguish from sibling tools like 'list_splits' or 'list_ticker_news', but the specificity of 'cash dividends' provides reasonable differentiation within this 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. With many sibling tools available (like 'get_ticker_details', 'list_splits', or other financial data tools), there's no indication of when historical cash dividends are the appropriate data to retrieve versus other financial metrics or data types.

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 aggregates' but doesn't specify if this is a read-only operation, what permissions might be needed, rate limits, pagination behavior, or error handling. For a tool with 10 parameters and no annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence with no wasted words. It's front-loaded and gets straight to the point, making it easy to parse quickly. However, this conciseness comes at the cost of detail, but within the dimension's scope, it's 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 the complexity (10 parameters, no annotations, no output schema, and 0% schema coverage), the description is inadequate. It doesn't explain what 'aggregates' are, how to interpret the numerous window parameters, or what the tool returns. For a data-fetching tool with many inputs, more context is needed to guide effective 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?

Schema description coverage is 0%, meaning none of the 10 parameters have descriptions in the schema. The description only vaguely references 'a futures contract' and 'a given time range,' which partially maps to 'ticker' and some window parameters but doesn't explain what 'aggregates' include, the meaning of 'resolution,' 'sort,' 'limit,' or 'params.' It adds minimal value beyond the schema's property names.

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 'Get aggregates for a futures contract in a given time range,' which provides a basic verb+resource+scope. However, it doesn't distinguish this tool from siblings like 'get_aggs' or 'list_aggs,' leaving ambiguity about what makes it specific to futures contracts versus other aggregation tools. The purpose is clear 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 siblings like 'get_futures_snapshot' or 'list_futures_quotes,' there's no indication of whether this tool is for historical data, real-time aggregates, or specific use cases. No exclusions or prerequisites are mentioned, leaving the agent to guess based on 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. It mentions 'paginated list,' which hints at output behavior, but fails to describe critical traits like rate limits, authentication needs, error handling, or what 'paginated' entails (e.g., page size, token). This is a significant gap for a tool with 9 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 no wasted words. It is front-loaded with the core 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 complexity (9 parameters, no annotations, no output schema), the description is incomplete. It lacks details on parameter usage, behavioral constraints, and output format, which are essential for effective tool invocation. The mention of 'paginated' is a minimal start but insufficient for full context.

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

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

Schema description coverage is 0%, meaning all 9 parameters are undocumented in the schema. The description does not add any meaning beyond the tool name—it does not explain what parameters like 'active,' 'as_of,' or 'product_code' do, nor their expected formats. This leaves parameters entirely unexplained.

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 'Get[s] a paginated list of futures contracts,' which clearly identifies the verb ('get') and resource ('futures contracts'). However, it lacks specificity about scope (e.g., all contracts or filtered) and does not differentiate from siblings like 'list_futures_products' or 'get_futures_contract_details,' making it 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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention any context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone among many sibling tools.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does ('Get market statuses'), without mentioning any behavioral traits such as whether it's a read-only operation, if it requires authentication, rate limits, pagination, or what the output format might be. For a tool with 5 parameters and no output schema, this lack of context is a significant gap.

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

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

The description is a single, efficient sentence: 'Get market statuses for futures products.' It is front-loaded and wastes no words, making it easy to parse. However, given the tool's complexity (5 parameters, no annotations), this brevity borders on under-specification rather than optimal conciseness.

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 fails to explain key aspects: what market statuses include, how parameters filter results, the return format, or behavioral constraints. With no output schema and low parameter documentation, the description should provide more context to help the agent 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 (limit, params, product_code, product_code_any_of, sort) are documented in the schema. The description does not add any meaning beyond the schema—it doesn't explain what these parameters do, their expected values, or how they affect the query. With 0% coverage and no compensation in the description, the parameters remain largely opaque.

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 'Get market statuses for futures products' clearly states the action (get) and resource (market statuses for futures products), providing a basic understanding of the tool's function. However, it doesn't differentiate this tool from potential sibling tools like 'get_market_status' or 'get_futures_snapshot', which might offer similar or overlapping functionality. The purpose is clear but lacks specificity about scope or uniqueness.

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 sibling tools like 'get_market_status' (which might cover broader markets) and 'get_futures_snapshot' (which could include status data), there's no indication of context, prerequisites, or exclusions. Usage is implied by the name but not explicitly stated, 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. 'Get a list' implies a read-only operation, but it doesn't specify whether this is a real-time query, cached data, paginated results, rate limits, authentication requirements, or what 'including combos' means operationally. The description provides minimal behavioral 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 at just 8 words in a single sentence. Every word earns its place by specifying the resource type and inclusion of combos. There's no wasted language or 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?

For a tool with 12 parameters, no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain what data is returned, how results are structured, what 'combos' means, or how the numerous filtering parameters work together. The description leaves too many open questions 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?

With 12 parameters and 0% schema description coverage, the description provides no information about any parameters. It doesn't explain what 'as_of', 'asset_class', 'limit', or any other parameters mean or how they affect the results. 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 clearly states the verb 'Get' and resource 'list of futures products (including combos)', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_futures_contracts' or 'get_futures_product_details', which limits its score to 4 rather than 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 siblings like 'list_futures_contracts' and 'get_futures_product_details' available, there's no indication of when this list operation is preferred or what distinguishes it from other listing 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 full burden. It only states what the tool does ('Get quotes'), with no disclosure of behavioral traits such as whether it's read-only or mutative, rate limits, authentication needs, pagination, error handling, or what 'quotes' entail (e.g., price data). This leaves critical gaps for an AI 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 a single, efficient sentence with zero waste—'Get quotes for a futures contract in a given time range.' It is appropriately sized and front-loaded, 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 (14 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavior, parameter usage, return values, and differentiation from siblings. While concise, it doesn't provide enough context for an AI agent to reliably invoke this tool without guesswork.

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%, with 14 parameters (1 required). The description mentions 'time range' and 'futures contract', which loosely maps to parameters like 'timestamp' and 'ticker', but adds no meaningful semantics beyond the schema titles (e.g., no format for dates, no explanation of 'params' object, no guidance on using 'limit' or 'sort'). It fails 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 clearly states the action ('Get quotes') and resource ('for a futures contract'), specifying the scope ('in a given time range'). It distinguishes from general 'list_quotes' by specifying 'futures', but doesn't explicitly differentiate from other futures-related siblings like 'list_futures_trades' or 'list_futures_aggregates'.

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 minimal guidance by mentioning 'in a given time range', which hints at when to use it (for time-based queries). However, it offers no explicit when-not-to-use advice, no prerequisites, and no comparison to alternatives among the many sibling tools (e.g., vs. 'list_futures_trades' for trade data).

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 'Get[s] trading schedules,' implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns paginated results, or handles errors. For a tool with 5 parameters and no annotation coverage, this lack of behavioral context is a significant gap.

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

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

The description is a single, efficient sentence with no wasted words: 'Get trading schedules for multiple futures products on a specific date.' It is front-loaded and appropriately sized for its purpose, 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 (5 parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It lacks details on parameter usage, behavioral traits, output format, and differentiation from siblings. While conciseness is good, it doesn't provide enough context for effective tool invocation in this data-rich environment.

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 (limit, params, session_end_date, sort, trading_venue) are documented in the schema. The description only vaguely implies 'on a specific date,' which might relate to 'session_end_date,' but doesn't explain any parameters' purposes, formats, or interactions. This fails to compensate for the low schema coverage, leaving parameters largely unexplained.

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 trading schedules for multiple futures products on a specific date.' It specifies the verb ('Get'), resource ('trading schedules'), and scope ('multiple futures products on a specific date'), which is clear and actionable. However, it doesn't explicitly differentiate from its sibling 'list_futures_schedules_by_product_code', which appears to be a more specific variant, so it doesn't fully achieve 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 any prerequisites, such as required parameters or date formats, nor does it compare to sibling tools like 'list_futures_schedules_by_product_code' or other futures-related tools (e.g., 'get_futures_contract_details'). This leaves the agent with minimal 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 'Get schedule data,' implying a read-only operation, but fails to detail aspects like pagination, rate limits, authentication needs, error handling, or the format of returned data. This leaves significant gaps for an agent to understand how to interact with the tool 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 and directly states the tool's function, 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 9 parameters (1 required), 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain parameter usage, return values, or behavioral traits, making it incomplete for effective agent operation in this context.

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

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

Schema description coverage is 0%, meaning none of the 9 parameters have descriptions in the schema. The tool description does not mention any parameters, such as 'product_code' (required) or filtering options like 'session_end_date_gt,' leaving their purposes and usage completely undocumented. This 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 states the tool 'Get schedule data for a single futures product across many trading dates,' which provides a clear verb ('Get') and resource ('schedule data'), but it's somewhat vague about what 'schedule data' entails. It doesn't distinguish this tool from sibling tools like 'list_futures_schedules' or 'get_futures_contract_details,' leaving ambiguity in its 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 siblings like 'list_futures_schedules' and 'list_futures_contracts,' the description lacks context on prerequisites, filtering capabilities, or comparative use cases, offering no help in 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 the full burden of behavioral disclosure. It states the tool retrieves trades but lacks details on permissions, rate limits, pagination, return format, or whether it's a read-only operation. The description is too minimal to adequately inform an agent about behavioral traits beyond the 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 no wasted words. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration, 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 (14 parameters, 1 required), no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks essential details about parameter usage, behavioral context, and output expectations, making it inadequate for an agent to effectively use this tool 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?

The schema description coverage is 0%, meaning none of the 14 parameters are documented in the schema. The description only mentions 'time range' and 'futures contract', which loosely relates to parameters like 'ticker' and timestamp fields, but it fails to explain the purpose of most parameters (e.g., 'limit', 'sort', 'params', various comparison operators). This does not 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 clearly states the action ('Get trades') and resource ('for a futures contract') with a scope ('in a given time range'), which provides a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'list_trades' or 'list_futures_aggregates', which might have overlapping functionality.

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. There are many sibling tools (e.g., 'list_trades', 'list_futures_aggregates') that might serve similar purposes, but the description offers no context about prerequisites, exclusions, or comparative 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action ('Get inflation data') without mentioning critical traits like whether it's a read-only operation, requires authentication, has rate limits, or what the output format is. This leaves significant gaps for an agent to understand how to interact with the tool safely and 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 and to the point, though it could benefit from more detail given the tool's complexity. The brevity is appropriate but leads to under-specification.

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 (9 parameters, 0% schema coverage, no output schema, and no annotations), the description is incomplete. It doesn't address parameter usage, behavioral traits, or output expectations, making it inadequate for an agent to use the tool effectively without additional context or trial-and-error.

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 provides no information about the 9 parameters (e.g., 'date', 'limit', 'sort'). It fails to explain what these parameters do, their expected formats, or how they affect the data retrieval, leaving the agent to infer usage from schema titles alone.

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 'Get inflation data from the Federal Reserve' which provides a clear verb ('Get') and resource ('inflation data'), but it's vague about what specific data is retrieved (e.g., time series, metrics, or reports). It doesn't distinguish from siblings like 'list_treasury_yields' or other data-fetching tools, 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. The description lacks context about use cases, prerequisites, or comparisons to sibling tools (e.g., 'list_treasury_yields' for other economic data), offering no help in tool selection.

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