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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only retrieval but does not disclose data source, update frequency, normalization method, or any side effects. Only the operation type and output subject are conveyed.

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

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

The description is a single, front-loaded sentence that communicates the core action and resource with zero wasted words. It is appropriately sized for a simple retrieval tool.

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

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

For a one-parameter retrieval tool with no output schema and no annotations, the description is minimally adequate: it identifies the returned data type but omits return format, frequency, and normalization details. It is complete enough for an agent to invoke the tool but leaves some contextual 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 single parameter has 100% schema description coverage ('Stock symbol in Yahoo Finance format'), so the schema already fully documents it. The description adds no additional meaning beyond what the schema provides, making the baseline score of 3 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 states a specific verb ('Get') and resource ('capital-gains distributions') and adds the scope qualifier 'normalized'. It is clear what data is returned and distinguishes itself from most sibling tools by naming a distinct financial data type.

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

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

There is no guidance on when to use this tool versus siblings like get_dividends or get_performance_analysis. The implied use case is retrieving capital-gains distributions, but no conditions, prerequisites, or alternatives are stated.

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

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

No annotations are provided, so the description carries the full burden. It does not state whether the operation is read-only, what the return format is, what permissions are required, or how the data is sourced. It only asserts that a cashflow statement is returned.

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 redundant or filler content. The core purpose is 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?

The input schema is complete and self-documenting, which covers parameter semantics. However, with no annotations and no output schema, the description does not clarify basic behavioral or return-value expectations for a financial data retrieval 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 both parameters are well documented in the schema, including the 'freq' enum and its default. The description adds no parameter meaning beyond the schema, so the baseline of 3 applies.

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

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

The description states a specific verb ('Get') and resource ('cashflow statement') and identifies the required input ('stock symbol'). It distinguishes the tool from siblings like get_income_statement by resource, though it does not explicitly differentiate among statement 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?

There is no guidance on when to use this tool versus alternatives such as get_income_statement or get_dividends, nor any prerequisites or exclusions. Usage is only implied by the resource name.

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

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

With no annotations, the description carries the full behavioral burden. 'Normalized' hints that values are standardized across sources, which is useful, but nothing is said about data freshness, rate limits, auth requirements, or what 'overview' actually contains.

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

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

One tightly written sentence with the resource and scope front-loaded and no filler. It is appropriately sized for a simple single-parameter read tool, though it is arguably too terse to be maximally useful.

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

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

For a one-parameter read tool with full schema coverage, the description is adequate but thin. With no annotations and no output schema, it leaves the return contents ('overview' of what fields?) and safety profile undefined.

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% and the single parameter is documented as Yahoo Finance format, so the baseline is 3. The description only reinforces that exactly one symbol is accepted (no batch/multi-symbol use), adding marginal value 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?

States a specific verb ('Get'), resource ('company overview'), and scope ('for one stock symbol'), so the agent knows this returns a broad profile rather than a single financial statement. It is distinguishable from most siblings by resource, though it does not name which sibling to prefer when a narrower metric is wanted.

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 versus the many sibling tools (get_rich_quote, get_income_statement, get_symbol_comparison, etc.). The agent must infer that 'overview' means a summary profile, and there is no stated exclusion or prerequisite.

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's function but doesn't describe traits such as rate limits, authentication needs, data freshness, error handling, or return format. This leaves significant gaps for a tool that likely interacts with external data sources.

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 is appropriately sized for a simple tool and front-loads the key information without unnecessary elaboration.

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

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like data source reliability, potential errors, or return structure. For a tool fetching real-time financial data, more context on limitations or usage constraints 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?

The schema description coverage is 100%, with the parameter 'symbol' fully documented in the schema as 'Stock symbol in Yahoo Finance format.' The description adds no additional meaning beyond what the schema provides, so it meets the baseline for high schema coverage without compensating value.

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

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

The description clearly states the action ('Get') and resource ('current stock price') with the specific condition ('based on stock symbol'). It distinguishes from siblings like get_historical_stock_prices and get_stock_price_by_date by specifying 'current', but doesn't explicitly contrast them in the description text.

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_stock_price_by_date or get_historical_stock_prices. It lacks any mention of prerequisites, exclusions, or comparative contexts with 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?

With no annotations, the description carries the full behavioral burden. 'Normalized' hints at adjusted/standardized data but is never explained, and there is no disclosure of date coverage, pagination, rate limits, or auth requirements for a financial data endpoint.

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

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

One short, front-loaded sentence with no wasted words. The only cost is that the unexplained qualifier 'normalized' occupies space that could have clarified behavior.

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 single-parameter read tool with no output schema and no annotations, the description is minimally adequate. It omits return shape, date-range behavior, and any mention of the closely related upcoming-dividends sibling, which an agent would need to choose correctly.

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

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

Schema description coverage is 100% and there is a single parameter, so the schema already documents 'symbol' fully. The description adds no format or syntax detail beyond what the schema states, so the baseline of 3 applies.

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?

States a specific verb (get) and resource (dividend history) scoped to a stock symbol. The word 'history' implicitly distinguishes it from the sibling get_upcoming_dividends, but no sibling is named explicitly and the scope of 'history' is undefined.

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?

Usage is only implied: an agent can guess this retrieves past dividend records vs. the forward-looking get_upcoming_dividends or the tax-oriented get_capital_gains. No explicit when-to-use, prerequisites, or exclusions are stated.

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

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

No annotations are provided, so the description must carry the full behavioral burden. It discloses the temporal scope ('recent and upcoming') but omits auth needs, rate limits, return format, or whether it is a safe read-only operation, leaving significant behavioral gaps.

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

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

The description is a single sentence, front-loaded with the verb and resource. Every word earns its place, with no redundancy or wasted 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?

For a simple read-only list tool with two fully documented parameters, the description is minimally adequate. However, with no annotations and no output schema, it does not explain return values or safety profile, leaving notable gaps for an 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 coverage is 100%, so the schema fully documents both parameters. The description adds no additional meaning beyond the resource name; it does not clarify symbol format or the limit's effect, so it meets the baseline only.

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?

States a clear verb 'Get' and resource 'earnings dates' with scope 'recent and upcoming'. This distinguishes it from siblings like get_earnings_analytics and get_upcoming_dividends by resource type, but it does not explicitly name alternatives or clarify its unique scope relative to them.

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

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

No when-to-use guidance, prerequisites, or alternatives are provided. The description merely states what the tool does without indicating when an agent should select it over related tools such as get_earnings_analytics.

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

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

With no annotations, the description carries the full burden. It implies a read of two parallel histories and the limit param hints at pagination up to 100 rows each, but it never states whether results are capped, whether the histories are aligned by period, or anything about auth or return shape. Adequate-but-thin for a no-annotation 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?

A single front-loaded sentence with no filler, though it is arguably under-specified rather than truly concise given what it omits.

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?

A simple two-parameter read tool with full schema coverage and no output schema, so the bar is modest and the description covers the returned data. It still leaves the dual-history structure and limit semantics unstated in prose.

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 both symbol and limit are already documented in the schema, including the 1-100 range. The description adds no parameter-level detail, so the baseline 3 applies.

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

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

The description names a specific resource and its contents: earnings surprise history plus analyst estimate history. That is far more informative than a tautology, but it never distinguishes this from the adjacent get_earning_dates or get_recommendations siblings, so an agent still has to guess at the boundary.

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 when-to-use guidance, no prerequisites, and no mention of the near-identical sibling get_earning_dates. The agent is left to infer the intended scenario from the noun phrases 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 behavioral burden, yet it discloses nothing about the data source, rate limits, whether the response is paginated, or what the returned series looks like. For a read-only data fetch the risk is low, but the disclosure is essentially 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?

A single front-loaded sentence with no filler or repetition. It is efficient, though arguably under-specified rather than optimally concise.

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

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

All four parameters are documented by the schema with defaults, and no output schema exists so return values need not be explained. Still, a data-retrieval tool with no annotations would benefit from a note on the data source and the shape/frequency of returned prices.

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% and both enums (period, interval) plus the adjusted flag are self-documenting in the schema, so the baseline of 3 applies. The description adds no syntax, format, or default-value information 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?

States a specific verb (Get) and resource (historical stock prices), scoped to a stock symbol. It does not, however, distinguish itself from close siblings like get_stock_price_date_range, get_stock_price_by_date, or get_current_stock_price, which an agent must disambiguate by name alone.

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 versus get_current_stock_price, get_stock_price_by_date, or get_stock_price_date_range, and no mention of prerequisites or data source constraints. The agent is left to infer selection from tool names.

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

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

With no annotations, the description carries the full behavioral burden, yet it discloses nothing beyond an implicit read operation. It does not say whether results are limited in history, what currency/units the figures use, whether the call is rate-limited or authenticated, or what happens with an invalid symbol.

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?

A single front-loaded sentence with zero filler, which is structurally clean. It is arguably too terse for a financial-statement tool with no output schema, but nothing is wasted.

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

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

The tool is low-complexity (two parameters, one required, no nested objects) and the schema is self-documenting, so the description is minimally sufficient to invoke it. With no output schema, however, it gives no hint about the shape of the returned statement or which periods are covered.

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 both parameters (symbol format, freq enum with default) are already fully documented in the schema. The description's phrase "for a given stock symbol" adds no meaning beyond that, making the baseline 3 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 states a specific verb (Get) and resource (income statement) scoped to a stock symbol, so an agent knows exactly what it returns. It does not, however, differentiate itself from adjacent financial-statement siblings like get_cashflow or get_company_overview, which a reader must disambiguate on their own.

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 when-to-use, when-not-to-use, or alternative guidance. It never mentions that get_cashflow covers the cash-flow statement or that get_company_overview may be the better entry point, so routing must be inferred from the name alone.

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

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

No annotations are provided, so the description must carry the full behavioral burden. It adds only 'normalized, bounded' (the latter partly duplicates the schema's limit) and does not disclose read-only status, data source, rate limits, or return format.

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?

A single front-loaded sentence with no filler; every word contributes to the tool's core purpose.

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

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

Minimum viable: the schema fully documents the parameters, so an agent can invoke it, but with no annotations and no output schema the description does not explain return shape or normalization details. It leaves meaningful behavioral context unstated.

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

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

Schema description coverage is 100%, so the schema already documents symbol, limit, start_date, and end_date. The description adds 'for a stock symbol' but no additional parameter syntax, defaults, or 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?

States a specific verb ('Get') and resource ('news') scoped to a stock symbol, clearly distinct from the many price and financial-statement siblings. However, 'normalized, bounded' are vague qualifiers and it does not explicitly name what it is not.

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?

Provides no when-to-use, when-not-to-use, or alternative-tool guidance among the many sibling data tools. Usage is only inferable from the resource name.

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. 'Bounded' hints at the per-side limit, but nothing is said about permissions, rate limits, pagination, or whether results are split into calls/puts — significant gaps for a 10-param read 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?

A single front-loaded sentence with no wasted words, though it is arguably too sparse for a tool with ten parameters.

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

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

With ten parameters, no annotations, and no output schema, a one-line description leaves too much unaddressed: the shape of the return (calls vs puts), the prerequisite expiration lookup, and how filters combine are all unstated.

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 every parameter is already documented in the schema; the description adds only the vague qualifier 'filtered, bounded'. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

States a specific verb (Get), resource (option chain), and scope (one expiration date), which implicitly separates it from siblings like get_option_expiration_dates and get_option_summary. It stops short of naming those siblings explicitly, so differentiation is left to inference.

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 phrase 'for one expiration date' implies a required expiration input but never states when to use this over get_option_summary or that get_option_expiration_dates is the natural prerequisite. No alternatives or exclusions are given.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not state that the operation is read-only, nor does it describe response format, rate limits, or any other behavioral trait 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, well-structured sentence that front-loads the core action and resource. Every word earns its place with zero redundancy.

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

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

For a simple retrieval tool with one parameter and no output schema, the description adequately conveys what is returned ('available option expiration dates'). It is nearly complete, though it could mention read-only behavior or formatting to be fully self-contained.

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% with the single 'symbol' parameter fully documented as 'Stock symbol in Yahoo Finance format.' The description adds no additional meaning beyond what the schema already provides, so the baseline 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 states a specific verb ('Get') and resource ('available option expiration dates for a stock symbol'), making the tool's purpose immediately clear. It does not explicitly differentiate from siblings like get_option_chain or get_option_summary, which may also surface expiration-related data, so it falls short of 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?

No when-to-use or when-not-to-use guidance is provided. There is no mention of alternatives (e.g., whether get_option_chain also returns expiration dates) or any context that would help an agent choose between this and sibling option 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 lists summary metrics but does not state whether the data is read-only, how fresh it is, what permissions are needed, or how the summary is computed.

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

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

The description is a single, front-loaded sentence with no wasted words. It efficiently lists the core metrics the tool summarizes.

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 and no annotations, the description should do more to explain the result shape and usage context. It lists the metrics covered, which is helpful, but leaves behavioral and selection details unaddressed.

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 input schema already documents symbol, expiration_date, and limit in detail. The description adds no parameter-level information beyond what the schema provides, making the baseline 3 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 states a clear verb ('Summarize') and a specific set of option data points: interest, volume, volatility, ratios, and max pain. It does not differentiate this tool from siblings like get_option_chain, but the purpose itself is unambiguous.

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

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

The description gives no guidance on when to use this tool versus alternatives such as get_option_chain or get_option_expiration_dates. Usage is only implied by the tool name and the metrics listed.

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 supplied, so the description carries the full burden. It does not explain what 'adjusted' means (adjusted close?), what metrics the analysis produces (returns, correlation, benchmark-relative performance), or whether it is read-only. For a computation tool with no output schema, this is a substantial 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?

A single efficient sentence with the core action and scope front-loaded and no filler. It is concise, though its brevity is partly the source of the missing detail rather than an intentional structural choice.

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 annotations, no output schema, and five parameters, the definition should say more about what the analysis returns and how symbols/benchmark combine. As written, an agent knows the inputs only from the schema and has no idea what output to expect.

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 all five parameters, including the optional benchmark_symbol, are already documented in the schema. The description adds no parameter-level meaning (e.g., how benchmark_symbol affects results), so baseline 3 applies.

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?

States a specific verb (Analyze) and resource (adjusted performance) with scope (multiple symbols, date range). It is clear, but it does not differentiate itself from siblings like get_symbol_comparison or get_historical_stock_prices, which an agent could plausibly pick for similar requests.

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 when-to-use guidance, no prerequisites, and no alternative tools named. With ~20 sibling retrieval tools, the description leaves the agent to infer that this is the multi-symbol comparative analysis option rather than, say, a raw price fetch.

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 action ('Get') but doesn't describe any traits like whether it's a read-only operation, potential rate limits, data freshness, or what the output format looks like (e.g., list of recommendations, summary). This is a significant gap 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 a single, efficient sentence that directly states the tool's purpose without any unnecessary words. 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 of financial data tools, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'analyst recommendations' entail (e.g., buy/sell ratings, target prices), how results are returned, or any behavioral aspects, leaving the agent with insufficient context for effective use.

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

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

The schema description coverage is 100%, with the single parameter 'symbol' fully documented in the schema as 'Stock symbol in Yahoo Finance format.' The description adds no additional meaning beyond this, so it meets the baseline for high schema coverage without compensating value.

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 ('analyst recommendations'), specifying it's for a given symbol. However, it doesn't differentiate from sibling tools like get_news or get_current_stock_price, which might also provide related financial data, so it doesn't reach the highest clarity level.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone among many financial data siblings.

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 implies a read-only retrieval but does not state that explicitly, nor does it describe data freshness, permissions, rate limits, or what 'normalized' means. This is a significant gap for a tool with zero 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 a single front-loaded sentence with zero waste. It is appropriately sized for a simple one-parameter tool.

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

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

With no output schema and no annotations, the description should compensate by explaining what a 'normalized quote snapshot' contains, how it differs from sibling quote tools, and any return format details. It does not, leaving an agent without enough context to understand the result or select this tool confidently over alternatives.

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

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

Schema description coverage is 100%, so the single symbol parameter is already fully documented in the schema. The description adds only 'one stock symbol,' which reinforces what the schema already states and provides no additional semantic detail. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description states a specific verb and resource: 'Get a normalized quote snapshot for one stock symbol.' It is clear what the tool does, but it does not distinguish itself from siblings like get_current_stock_price or get_stock_price_by_date, leaving ambiguity about which quote tool to select.

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 offers no context, exclusions, or prerequisites, so an agent must infer usage from the name alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool's function but lacks details on error handling, data sources (e.g., Yahoo Finance implied by schema but not confirmed), rate limits, or authentication needs. For a read operation with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It uses minimal words to convey the essential action and inputs, making it easy for an agent to parse quickly. Every word earns its place, with no 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 tool's low complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks behavioral context and usage guidelines. Without annotations or output schema, the description should ideally add more about return values or error cases, but it's sufficient for a simple lookup 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?

The schema description coverage is 100%, with clear descriptions for both parameters ('date' and 'symbol'). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 the stock price for a given stock symbol on a specific date.' It specifies the verb ('Get'), resource ('stock price'), and key constraints ('on a specific date'). However, it doesn't explicitly differentiate from siblings like 'get_current_stock_price' or 'get_historical_stock_prices', 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. It doesn't mention siblings like 'get_current_stock_price' (for current prices) or 'get_historical_stock_prices' (for multiple dates), leaving the agent to infer usage from context alone. This lack of explicit comparison or exclusion criteria limits its utility.

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

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing beyond the query shape. It does not say what price fields are returned, the data granularity (daily vs. intraday), the data source/basis, whether ranges are limited by history, or whether this is a read-only call. The only real disclosure is that the range is inclusive.

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?

A single, front-loaded sentence with no filler or redundancy. It is efficient, though its brevity is partly under-specification rather than tight craftsmanship.

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 3-required-parameter data-retrieval tool with no annotations and no output schema, the description leaves key questions unanswered: what price values come back, at what interval, and how it differs from the many sibling price tools. It is complete enough to fire a call but not to call it correctly with confidence.

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

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

Schema description coverage is 100%, so the schema already documents symbol, start_date, and end_date with formats, establishing the baseline of 3. The description adds one genuine semantic detail beyond the schema: the date range is inclusive, which affects how the agent sets start_date/end_date.

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

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

The description states a specific verb and resource ('Get stock prices for a symbol over an inclusive date range'), so the agent knows it retrieves time-series price data rather than a single quote. However, it does not distinguish itself from close siblings such as get_historical_stock_prices, get_stock_price_by_date, or get_current_stock_price, which is exactly where an agent needs help choosing.

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 when-to-use, when-not-to-use, or alternative-tool guidance is given. With at least three sibling tools that look like plausible substitutes (get_stock_price_by_date, get_historical_stock_prices, get_current_stock_price), the description should route the agent but leaves selection entirely to inference.

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

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only lookup but says nothing about return format, error behavior for unknown symbols, rate limits, or what 'normalized' actually means for the split 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?

One short sentence with the verb and resource front-loaded and zero wasted words. Appropriately sized for a simple single-parameter lookup tool.

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

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

For a low-complexity tool with one fully documented parameter and no output schema, the description covers the essential purpose but leaves return shape and 'normalized' semantics undefined. Adequate but minimal.

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% and the single 'symbol' parameter is fully documented in the schema. The description adds no syntax or format detail beyond what the schema already conveys, so the baseline 3 applies.

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?

States a specific verb ('Get') and resource ('normalized stock split history') for a symbol. This is clearly distinct from siblings like get_dividends and get_capital_gains, though it does not explicitly name or contrast with any of them.

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

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

No indication of when to use this tool versus alternatives such as get_dividends or get_capital_gains, nor any prerequisites or context for invoking it. The agent must infer usage entirely from the name.

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

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

No annotations are provided, so the description carries the full behavioral burden. 'Compare current quote data' implies a read-only operation, but it says nothing about return shape, whether the comparison is side-by-side, latency/rate-limit behavior, or how the 1-20 limit is enforced. For a zero-annotation tool this leaves real 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?

One sentence, front-loaded with the verb and scope, with no filler or redundancy. Appropriate size for a single-parameter read tool.

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

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

For a simple one-parameter read tool with full schema coverage and no output schema, the essentials are covered. A brief note on what the comparison returns or how it differs from the single-symbol tool would complete it, but nothing critical is missing.

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

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

Schema description coverage is 100% and the single parameter already documents 'One to 20 Yahoo Finance symbols to compare,' including the format and bound. The description adds only the plural 'symbols' framing, so it does not meaningfully extend 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?

States a specific verb (compare) plus resource (current quote data) and scope (multiple symbols), which separates it from the single-symbol get_current_stock_price and get_rich_quote siblings. It does not name those siblings explicitly, so differentiation is inferable rather than stated.

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

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

There is no when-to-use guidance and no mention of alternatives such as get_current_stock_price (single symbol) or get_rich_quote (deeper per-symbol data). An agent must infer the multi-symbol use case purely from the word 'multiple'.

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

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

With no annotations, the description carries the full burden. It hints that results may be absent ('when Yahoo provides them'), which is useful, but never confirms this is a read-only lookup, nor mentions auth, rate limits, or what an empty response means.

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?

A single front-loaded sentence with no filler. The availability clause is compact and relevant, though the sentence is sparse enough that it could have carried one more clarifying clause at no cost.

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 one-parameter read tool with no output schema, the description covers the essentials (what data and the possibility of absence). It omits return shape details and any indication of how rates are represented, leaving modest 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?

Schema description coverage is 100% for the single 'symbol' parameter, so the schema already defines format expectations. The description adds no syntax or format detail beyond that, making the baseline 3 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?

States a specific verb ('Get') and resource ('upcoming dividend dates and rates'), which implicitly distinguishes it from the sibling get_dividends (presumably historical). However, it never explicitly names that sibling or draws the boundary, so differentiation is left to inference.

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 versus get_dividends or get_earning_dates, and no prerequisites stated. The clause 'when Yahoo provides them' is an availability caveat, not usage guidance.

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