OptionsBell Options Flow

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 accurately describes the tool's behavior as returning coverage metrics (date ranges, counts) without mentioning any side effects. It is thorough for a read-only discovery tool with no 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?

Two sentences front-load the purpose and then add usage guidance. No redundant words, every sentence is meaningful and earns its place.

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

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

For a simple discovery tool with no parameters and no output schema, the description sufficiently explains the return content (date ranges, counts) and usage context. Minor gaps like missing output format are negligible given the tool's simplicity.

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

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

The input schema has zero parameters (100% coverage vacuously). The description adds value by explaining what the tool provides without needing parameter details, earning the baseline 4.

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

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

The description uses the specific verb 'Discover' and identifies the resource as 'data availability for the unusual-activity dataset and its daily aggregates.' It clearly distinguishes from sibling tools (e.g., get_unusual_activity) by being an exploratory/discovery tool.

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?

Explicitly states 'Call this first when unsure about available history,' providing a clear usage directive. This helps the agent decide when to invoke this tool over alternative data retrieval tools.

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

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

With no annotations provided, the description carries the full burden. It describes the output structure and interpretation but does not disclose data freshness, rate limits, or mutation behavior. The tool is likely read-only, but that is not explicitly stated.

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 concise at two sentences, with the key function upfront. The second sentence adds valuable interpretation. It is efficient with no redundancy.

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

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

For a tool with two optional parameters and no output schema, the description adequately explains the output structure (buckets with call/put splits) and provides interpretative context. It is sufficiently complete for an analytical tool.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no new information beyond the schema; it merely restates the date format and symbol format already defined in the input schema.

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

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

The description clearly states the tool's function: showing where unusual premium sits along the expiry axis in DTE buckets with call/put splits. It is distinct from sibling tools like get_flow_sentiment or get_iv_rank, which serve different 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?

The description provides interpretative guidance, explaining that heavy short-dated premium indicates event bets and long-dated indicates positioning. While it does not explicitly state when not to use the tool or name alternatives, the context is clear.

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 provided, but the description proactively discloses key behaviors: it returns only unusual flow (not full tape), aggregated daily, with specific metrics. It mentions the approximate history length. It does not address empty results or edge cases, but the core behavioral traits are well covered.

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?

Description is front-loaded with essential purpose and data scope. It is three sentences long, each providing useful detail. Some redundancy ('unusual options flow' vs 'passed the unusual filter') but overall 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?

With no output schema or annotations, the description compensates by listing output fields, data source, and time range. It covers the main functional aspects. Lacks mention of output format or pagination, but for a data retrieval tool with this complexity, it is sufficiently complete.

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

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

Input schema coverage is 100% with detailed descriptions for each parameter. The description adds minor value by noting default limit (90) and contextualizing time range (~75 days). It does not significantly enhance understanding beyond the schema, so baseline 3 is appropriate.

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

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

Description clearly states it provides per-symbol unusual options flow history, specifying the data source (filtered contracts), fields (volume, premium, ratios, IV, net delta, streak), time range (~75 days), and use cases (back-tests, trend analysis). This is highly specific and distinguishes it from related tools.

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

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

The description implies usage for historical analysis of unusual flow for a single symbol, with an example question. However, it does not explicitly contrast with sibling tools like get_symbol_flow or get_unusual_activity, nor state when not to use it. Still, the context is clear enough for an agent.

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

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

With no annotations, the description carries full behavioral disclosure burden. It explains the computation basis (call/put volumes, premium, net delta) and classification output, but does not disclose data freshness, rate limits, or error handling for missing data.

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?

Two efficiently crafted sentences. The first sentence immediately defines the output; the second describes the two usage modes. No redundant or extraneous 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 9 parameters, no annotations, and no output schema, the description provides sufficient context for core functionality: sentiment classification and snapshot vs. time series. Lacks details on return format, data coverage, and error states, but adequate for basic 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?

Schema description coverage is 78%. The description adds value beyond the schema by explaining the behavior of symbol (pass vs. omit), sector, and min_strength. It does not detail all parameters but covers the most important ones for primary uses.

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?

Clear verb+resource: 'Bullish/bearish classification of each symbol's unusual flow with a 0-9 strength score'. Distinguishes from sibling tools like get_symbol_flow and get_sector_flow by focusing on sentiment rather than raw flow 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?

Explicitly states two usage modes: pass a symbol for per-ticker time series or omit for cross-market snapshot. Mentions filtering by sector or minimum strength, providing clear context for parameter 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 present, so the description must cover behavioral traits. It discloses that the tool returns symbols with streak length and dominant side, but does not describe output format, sorting, rate limits, or what 'unusual' means. Adequate, but could be more transparent.

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?

Two sentences, no wasted words. Purpose and guidance are efficiently communicated.

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

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

The tool has 6 parameters and no output schema. The description is adequate for an agent to understand the basic purpose but lacks details on output structure, default behavior for optional parameters, and what constitutes 'unusual'. Could be more complete.

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

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

Schema description coverage is 67%, so the schema already explains many parameters. The description adds context for the 'side' parameter (dominant side call/put) and 'min_streak' (N+ consecutive days), but does not significantly enhance other parameters like 'limit' or 'symbols'.

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 it returns 'symbols with unusual options activity on N+ consecutive trading days' with dominant side, and directly addresses the use case: 'where does money keep showing up?' This distinguishes it from siblings like get_unusual_activity (single prints) and get_symbol_flow (single symbol).

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 clear guidance: use this for persistent signals over consecutive days rather than single prints. It implies an alternative (single print tools) but doesn't explicitly exclude situations where it should not be used.

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 exist, so description carries full burden. It mentions the prerequisite of 20+ days of history and the two behavioral modes. However, it does not disclose error handling, rate limits, authorization needs, or response format. This is adequate but not comprehensive.

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?

Two sentences, front-loaded with core purpose and prerequisite. The second sentence covers both modes efficiently. No redundant text, but slightly more structured formatting (e.g., separating modes) could improve clarity.

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

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

Given 6 parameters and no output schema, the description covers the main dual-mode usage and a key prerequisite. However, it omits details on return values, the meaning of limit, max_rank, and lookback_days. It provides enough for basic use but lacks completeness for advanced parameter 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?

Out of 6 parameters, only 'symbol' has a schema description (17% coverage). The description explains the dual behavior based on symbol presence and provides an example using side and min_rank. Other parameters like limit, max_rank, and lookback_days are not explained. More compensation is needed for 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 computes IV rank and percentile per symbol against rolling history. It distinguishes two modes: pass a symbol for time series, omit for a ranked snapshot with filtering. This is specific and differentiates from sibling tools that focus on other metrics.

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 explicitly explains when to pass a symbol (for time series) and when to omit it (for snapshot). It provides a concrete example using side=put&min_rank=0.8. While it doesn't explicitly exclude other scenarios, the guidance is clear and actionable.

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 discloses the returned metrics (breadth score, call/put ratio, regime label, signal counts) and mentions per-trading-day granularity. However, it does not address safety (read-only nature), rate limits, authentication requirements, or behavior with missing data.

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 two sentences with no wasted words. The first sentence lists key outputs, and the second provides the use case. It is front-loaded and efficient.

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

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

Given no output schema, the description partially explains return fields (breadth score, call/put ratio, regime label, signal counts). It defines regimes as bullish/bearish/mixed. However, it does not explain 'signal counts' in detail or default behavior of optional parameters. The tool has 3 optional params, and the schema covers most, so completeness is good.

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 67% (date_from and date_to have descriptions, limit does not). The description adds no additional meaning to parameters beyond what the schema provides. It mentions 'per trading day' but does not explain the limit parameter or parameter interactions.

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 explicitly states the tool returns market-wide breadth metrics with specific values (breadth score 0-100, call/put ratio, regime label, signal counts) and provides a clear use case question. It distinguishes from sibling tools by focusing on aggregate market regime rather than individual symbols or sectors.

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

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

The description gives a clear use case ('what's the overall tone of the unusual-flow tape?') but does not explicitly state when not to use it or mention alternative tools. However, the context of sibling tools (e.g., get_symbol_flow, get_sector_flow) implies it's for broad market assessment.

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

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

With no annotations, the description carries the burden. It discloses that the tool returns day-over-day OI change per symbol (total, calls, puts) and hints at interpretation ('fresh positioning'). It does not mention permissions, rate limits, or data freshness, but no contradictions exist.

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

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

Two sentences, front-loaded with key information, no extraneous content. Every word contributes to clarity.

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

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

With 6 parameters and no output schema, the description lacks clarity on return format (e.g., how total/calls/puts are structured, whether response is a list or map). It needs more detail to fully enable an agent to use the tool correctly.

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

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

Schema coverage is 67%. The description adds meaning for the 'symbol' parameter by explaining its omission triggers market-wide view. Other parameters (date, side, limit, min_prev_oi, min_change_pct) are not elaborated beyond the schema. The description partially compensates but does not cover all parameters fully.

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?

Title and description clearly define the tool: day-over-day open-interest changes per symbol, with options for individual symbol or market-wide gainers/losers. It distinguishes itself from sibling tools by focusing specifically on OI changes.

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?

Description explicitly states when to use the tool ('fresh positioning being built or unwound') and provides two usage modes (symbol or market-wide view). However, it does not explicitly exclude alternatives or mention when not to use it, though context from sibling names implies specialization.

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

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

With no annotations, the description carries full burden. It describes what the tool returns but does not disclose read-only nature, data freshness, or any side effects. Behavioral details beyond the output are absent.

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

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

Single sentence with clear listing of outputs. Front-loaded purpose, no wasted words.

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?

Tool has simple optional params and no output schema. Description covers return fields adequately. Could mention default order or pagination but not critical.

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 coverage is 50% (date described, limit not). The description adds context about 'day's' but does not explain the limit parameter or additional constraints beyond the schema.

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

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

The description clearly states the tool aggregates unusual options premium by GICS sector and lists specific fields returned. It distinguishes from per-symbol tools like get_symbol_flow.

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

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

The description implies usage for sector-level rollup but does not explicitly state when to use or when to prefer alternatives like get_symbol_flow or get_unusual_activity. No 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 must fully disclose behavioral traits. It mentions sorting by Vol/OI and contracts, but does not state that the operation is read-only, describe any potential side effects, or explain auth needs or rate limits. The term 'unusual' is undefined. Minimal behavioral disclosure.

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?

Two sentences, front-loaded with key purpose and usage guidance. No filler or redundant information. Efficiently communicates the tool's role.

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 8 parameters, no output schema, and no annotations, the description is too brief. It fails to explain return format, pagination, or how date filtering works. For a moderately complex tool, the description leaves significant gaps for the agent.

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

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

Schema description coverage is 50% (4 of 8 parameters have descriptions). The description adds no parameter-specific information beyond the overall purpose. It does not clarify how parameters interact (e.g., date range vs single date) or provide additional context for undocumented parameters like min_voloi or min_premium. Does not compensate for schema gaps.

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?

Description clearly states the tool returns 'every unusual contract on a single ticker, sorted by Vol/OI'. The verb 'get' is implied, resource is specified (unusual contracts on a single ticker), and it distinguishes from siblings by focusing on one specific stock rather than multiple or aggregate metrics.

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?

Explicitly says 'Use when the question is about one specific stock's unusual options flow'. This provides clear context, though it lacks explicit when-not-to-use statements or alternative tool names. Still strong guidance relative to most descriptions.

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 provided; description does not disclose behavioral traits such as whether the tool is read-only, authentication requirements, or data freshness. It only states what the tool returns without side-effect information.

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

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

Two short, front-loaded sentences with zero waste. Every word adds value.

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

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

No output schema and no explanation of return format or ordering beyond 'ranked by estimated premium'. For a tool with five parameters, more context on output structure would be beneficial.

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?

Parameter schema covers 80% (actual 100% in provided schema) with descriptions for all five parameters. Description adds minimal value beyond 'estimated premium', which aligns with min_premium default. Baseline 3 adequate but not enhanced.

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?

Clearly states verb 'get' and resource 'top prints of the day', with a specific explanation: 'biggest options bets ranked by estimated premium'. Distinguishes from sibling tools like get_flow_history by focusing on premium-ranked top prints.

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?

Includes a usage hint: 'Perfect for what were the largest options trades today?'. Implicitly tells when to use but does not explicitly exclude alternatives or mention when not to use.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It states it is a scan of options activity, but fails to mention whether it is read-only, any rate limits, data freshness, or side effects. The description is not sufficiently transparent for a data retrieval tool.

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 three sentences, front-loaded with the tool's core function, followed by filter/columns overview and an example. Every sentence adds value, with no wasted words. It is concise and well-structured.

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

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

Without an output schema, the description explains return fields (strike, expiry, volume, etc.), which is good. It also mentions the dataset origin. However, it does not cover pagination, default ordering, or the behavior when date_from/date_to are omitted. Despite these minor gaps, it is largely complete for a scanning tool.

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

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

Schema description coverage is 100%, so the baseline is 3. The description summarizes the filter categories (Vol/OI ratio, premium, IV, days-to-expiration) but does not add significant new meaning beyond what the schema already provides. It provides a high-level overview without deeper context.

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

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

The description clearly states the tool is a contract-level unusual options activity scan across 7,000+ US stocks, listing specific filters and output columns. It also provides an example use case, effectively distinguishing it from sibling tools like get_symbol_flow or get_flow_history.

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

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

The description gives an example question ('what unusual put buying hit TSLA today?') indicating a use case, but does not explicitly state when to use this tool over alternatives or when not to use it. With 12 sibling tools, more explicit guidance would be helpful.

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 provided, so description carries full burden. It states it's a liveness check with no API key needed, but does not disclose response format or side effects (e.g., if it returns a simple success message).

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?

Two sentences, front-loaded with key purpose. No unnecessary words.

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 no parameters and no output schema, the description is sufficiently complete for its simplicity.

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

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

Schema coverage is 100% (no parameters), so description does not need to add parameter info. Baseline score of 3 is appropriate.

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

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

The description clearly states the tool is a 'liveness check' for the server, distinguishing it from sibling tools that retrieve 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?

It mentions 'No API key required' implying it can be used without auth, but does not explicitly state when to use vs alternatives. Usage is implied rather than explicit.

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