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

No annotations are provided, so the description carries the behavioral disclosure burden. It communicates the essential behavior—comparing specified metrics across 2-3 tickers—but does not discuss data freshness, read-only status, error handling, or ordering. For a non-destructive comparison tool, the core behavior is reasonably clear.

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 with no filler. The action, resource, scope, and specific metrics are all front-loaded in a compact, readable way.

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 one well-described parameter and an output schema, the description is mostly complete: it states purpose, scope, and exact metrics. It lacks explicit sibling routing and deeper behavioral context, but the multi-ticker framing is sufficient to differentiate it from most sibling tools.

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

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

The input schema already fully describes the 'tickers' parameter, including the 2-3 constraint, symbol format, and an example. With 100% schema coverage, the description adds little beyond reinforcement, so the baseline score 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 uses a clear verb ('Compare') and a specific resource ('key metrics'), listing exact metrics and a 2-3 ticker scope. It distinguishes itself from sibling single-ticker tools by emphasizing multi-ticker comparison, though it does not explicitly name alternatives.

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

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

Usage is implied by the multi-ticker framing: an agent can infer this tool is for comparing several tickers rather than fetching a single quote or overview. However, there is no explicit guidance on when to prefer it over siblings like get_financial_ratios_tool or get_stock_quote_tool.

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 behavioral burden. It clearly discloses the output scope, including that the business description is truncated. For a read-only overview tool, this is adequate, though it does not mention error or empty-data handling.

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 concise sentences: the first states the action, the second enumerates the return fields. No filler, no repetition, and the main purpose is front-loaded.

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, one required parameter, and the presence of an output schema, the description is largely complete. It could add how unavailable fields are returned, but the listed fields and truncation caveat cover most of what an agent needs.

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 ticker description already provides a format example and search_ticker fallback guidance. The tool description adds no new parameter semantics beyond reusing 'ticker symbol'.

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 company profile overview for a ticker symbol') and enumerates the returned fields, making its domain distinct from siblings like get_stock_quote_tool or get_financial_ratios_tool. It doesn't explicitly name a sibling, but the field list is sufficient for differentiation.

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

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

The schema's ticker description gives an explicit conditional routing rule: if only a company name is available, call search_ticker first. This covers the main identification ambiguity, though it does not state when to prefer this tool over the other financial 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 burden of behavioral disclosure. It implies a read-only retrieval through the verb 'Get' and shows no destructive intent, but it does not disclose data freshness, availability, access requirements, or handling of missing ratios. The output schema covers return shape, yet broader behavioral context is minimal.

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 states the action, the target resource, and representative output fields without filler. It is concise, scannable, and every word contributes to understanding the 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 single-parameter getter with an output schema, the description is nearly sufficient for invocation. However, it lacks usage routing relative to sibling tools and gives little non-obvious behavioral context, leaving moderate completeness 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 input schema fully documents the single ticker parameter with 100% coverage. The description merely echoes 'for a ticker' and adds no new semantic detail beyond the schema, 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 clearly states the action ('Get') and the resource ('key financial ratios for a ticker') and lists concrete outputs (P/E, EPS, ROE, debt-to-equity). It is reasonably distinct from siblings, though it does not explicitly differentiate itself from overlapping tools like get_company_overview_tool or compare_stocks_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?

There is no guidance on when to use this tool versus alternatives. It does not mention preferred conditions, exclusions, or related sibling tools, so an agent has to infer usage solely from the tool name and brief description.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the kind of data returned (OHLC) and does not describe ordering, adjustment behavior, timezone handling, error behavior, or whether the operation is strictly read-only beyond the verb 'Get'.

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 filler. Every word contributes to identifying the resource and data type.

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 two-parameter retrieval tool with complete schema documentation and an output schema present, the description is adequate to enable invocation. It does not cover usage distinctions or behavioral edge cases, but those are covered in other dimensions and the tool name/sibling context supplies additional orientation.

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

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

Schema description coverage is 100%, with ticker and period both documented in the input schema, including permitted period values and the default. The description itself adds no parameter-level meaning beyond mentioning 'ticker', 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 uses a specific verb and resource: 'Get historical OHLC price data for a ticker.' It clearly distinguishes this tool from sibling tools like get_stock_quote_tool (current quote vs historical) and get_company_overview_tool (fundamentals vs price data).

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

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

The word 'historical' implies when this tool is appropriate, but the description does not explicitly say when to use it over get_stock_quote_tool or mention any exclusions. Usage context is implied rather than 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, and the description gives no information about side effects, read-only nature, permissions, or other behavioral aspects. The tool appears to be a read operation, but this 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 a single, efficient sentence that conveys all necessary information without redundancy.

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

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

While the description covers the basic purpose and parameters, it lacks context about output format, error handling, or relationships to sibling tools. The presence of an output schema is noted but not described, leaving some ambiguity.

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?

Both parameters are fully described with clear semantics. 'ticker' specifies an exact stock ticker symbol, and 'quarterly' clearly explains the boolean behavior and default 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), the resource (income statement), and specific data fields (revenue, net income, margins). It is precise and distinguishes from sibling tools like get_financial_ratios_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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention any conditions or scenarios that would favor this tool over 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 present, so the description carries the burden of explaining behavior. It clearly discloses the quote fields and market state examples, but it does not mention read-only side-effect absence, data freshness/delay, authentication needs, or behavior for invalid tickers.

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 tightly written sentences with the core purpose front-loaded and the return payload summarized compactly. There is no redundancy or filler.

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

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

For a single-parameter quote tool with an output schema present, the description covers the core purpose and expected return data. The main gap is the lack of explicit behavioral caveats and alternative routing in the description itself, but nothing essential to invoking the tool 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%, so the baseline is 3. The tool description adds no parameter meaning beyond the word 'ticker symbol'; the schema already supplies exact-symbol guidance, examples, and the search_ticker fallback.

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 opens with a specific verb and resource: 'Get the current stock quote for a ticker symbol.' It then itemizes quote-specific fields such as live price, previous close, day high/low, volume, and market state, which clearly differentiates it from historical, overview, and ratio siblings.

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 when to use it through the word 'current' and the quote-specific return fields, so an agent can infer it is not for historical or fundamental analysis. However, it does not explicitly name alternative tools or state when-not-to-use conditions; the schema's search_ticker fallback is helpful but not part of the tool description.

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 and does well: it states the tool returns up to 5 ranked candidate matches and lists the returned fields. It does not explicitly mention no-match/error behavior, but the read-only search semantics are clear from the description.

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?

Three concise sentences, each earning its place: purpose, when-to-use, and return behavior. The most important information is front-loaded, and there is no redundant filler.

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 resolver, the description covers what input to provide, what the tool does, and what comes back. The presence of an output schema covers formal return structure. A small gap is the absence of explicit failure or no-match behavior, but that is minor for tool selection.

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

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

The schema has 100% description coverage for its single parameter, so the baseline is 3. The description adds examples like 'Apple' and 'Tata Motors' and reinforces partial-name support, but it does not substantially go beyond the schema's own 'Full or partial company name' explanation.

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 a specific verb ('Resolve') and clear resource: a company name to stock ticker symbol(s). It distinguishes itself from sibling tools by establishing that it maps names to tickers, whereas siblings like get_stock_quote_tool operate on already-known tickers.

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?

'Use this first when you have a company name rather than an exact ticker' gives explicit guidance on when to invoke the tool. It implies the inverse condition (do not use it when you already have an exact ticker), though it does not name specific sibling alternatives.

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