Alpaca MCP Server

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 only states the action 'Add' with no details about idempotency, failure behavior, whether it appends or replaces, or any side effects. For a write operation, this is insufficient 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?

The description is a single, well-front-loaded sentence. Every word adds meaning, and there is no redundant or filler content. It is appropriately concise for a simple operation.

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 simplicity, complete schema coverage, and presence of an output schema, the description is minimally sufficient. However, it lacks any behavioral context or guidance about interaction with sibling tools, making it only complete enough for a straightforward selection but not for understanding side effects or error conditions.

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 both parameters described in the schema. The description adds minimal meaning beyond the schema, only tying 'by symbol' to the asset and 'specific watchlist' to the watchlist_id. It does not add syntax or additional semantics, 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?

The description uses a specific verb 'Add' with a clear resource ('an asset by symbol') and destination ('a specific watchlist'). It clearly distinguishes this from sibling tools like remove_asset_from_watchlist_by_id and update_watchlist_by_id.

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 the usage context (adding an asset to a watchlist) but does not explicitly state when to use this tool versus alternatives. It does not mention prerequisites like needing an existing watchlist or that the asset must be known, nor does it reference the opposing remove operation.

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 disclose safety-relevant behavior. It states the action but does not mention irreversibility, the full scope of orders affected (stocks, crypto, options), or potential side effects. This is a significant gap for a destructive mutation 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 a single, direct sentence with zero unnecessary words. It is perfectly concise and 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?

For a tool with no parameters and an output schema present, the description adequately states the operation's purpose and scope. However, it omits any caution or confirmation details that could be expected for a cancel-all operation, though these are more behavioral than contextual.

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 tool takes zero parameters, and the schema coverage is trivially 100%. Per the baseline for 0-param tools, the description does not need to add parameter information. No additional semantics are required.

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 'Cancel all open orders' uses a specific verb ('Cancel') and resource ('all open orders'), clearly distinguishing it from sibling tools like cancel_order_by_id and replace_order_by_id. The scope is unambiguous and operational.

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: when the goal is to cancel every open order at once. However, it does not explicitly mention alternatives (e.g., cancel_order_by_id) or exclusion conditions, so the usage guidance is implicit rather than explicit.

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, but it only states the core action ('Cancel'). It does not disclose implications such as irreversibility, restrictions on order state (e.g., only open orders), or error handling if the order no longer exists. The behavioral scope 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, concise sentence that is front-loaded with the action verb and resource. No extraneous words or redundancy.

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

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

For a tool with one parameter and no output schema, the description is minimally adequate but lacks context on side effects, exceptions, or what happens when the order cannot be canceled. Given the simplicity, this is a reasonable but not thorough description.

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 already fully describes the order_id parameter as a UUID string with the description 'order id', achieving 100% coverage. The tool description adds no additional meaning, 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?

The description clearly states the action ('Cancel') and the target resource ('a specific order'), with the qualifier 'by its ID' distinguishing it from bulk-cancel and other order operations. This is specific and 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 does not explicitly mention alternatives or exclusions. The phrase 'a specific order' implies single-order cancellation, contrasting with sibling tools like cancel_all_orders, but it does not name them or provide when-not-to-use guidance.

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?

There are no annotations, so the description carries the full burden. It discloses an important behavioral trait: sell orders remain queued when the market is closed and execute later. However, it does not mention the optional cancellation of existing orders, potential partial failures, or reversibility, which are significant for a mutation 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 concise and front-loaded: two sentences, the first stating the main action, the second adding a valuable edge-case caveat. No unnecessary words or redundancy.

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

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

The tool is simple with one optional parameter and an output schema. The description covers the core function and a key market-closed behavior, which is sufficient for most use cases. It could mention more about order types or failure modes, but overall it is reasonably 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?

The input schema fully describes the only parameter 'cancel_orders' with a clear conditional description. Schema coverage is 100%, so the description does not need to add parameter details; a baseline score of 3 is appropriate.

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

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

The description clearly states the tool's action and scope: 'Closes all open positions by placing sell orders for each.' This is specific and distinguishes it from the sibling 'close_position' which presumably targets a single position.

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 context that this tool is for liquidating all open positions, which differentiates it from single-position tools. However, it does not explicitly mention alternatives or when not to use it, though the context is strong enough to infer 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively discloses that the tool places a sell order and that if the market is closed, the order queues and executes at the next open. This exceeds minimal coverage, though it could mention order type or default full-close behavior.

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

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

The description is two concise sentences, front-loaded with the primary action and followed by an important behavioral note. Every sentence provides value 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?

Given the tool's moderate complexity, the description covers the core purpose and the notable queued-order behavior. An output schema exists, so return values need not be described. It lacks explicit mention that omitting qty/percentage closes the entire position, but the title and description imply a full close.

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 additional parameter semantics beyond the schema, such as the default behavior when neither qty nor percentage is provided, which would be valuable but is not present.

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: 'Closes a specific position for a single symbol by placing a sell order.' The verb 'closes' and the resource 'position' are specific, and 'for a single symbol' distinguishes it from sibling tools like close_all_positions.

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 a single position, contrasting with close_all_positions, but does not explicitly state when to use this tool over alternatives or provide exclusions. The queued order behavior is a usability note, not a direct alternative comparison.

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. It transparently indicates this is a mutation (creates) and specifies required inputs, but it does not disclose what happens upon success, whether the locate is a hard check, or any permission requirements. The schema adds some behavioral detail (e.g., HTTP 400 for invalid quantities), but the description itself is thin beyond the basic action.

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

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

The description is a single sentence that front-loads the action and purpose. Every word contributes value, with no filler or redundancy.

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

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

The tool has 4 parameters and an output schema, and the description plus detailed schema provide enough context for an agent to select and invoke the tool correctly. It could mention preconditions or the locate life cycle, but the combination of description and schema covers the essential information.

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

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

Schema description coverage is 100%, so the baseline is 3. The description restates which parameters are required and optional but adds no new semantic information beyond the schema's already-detailed descriptions (e.g., round lots, decimal string for limit_price).

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 'Creates' with a clear resource ('locate request for a short sale'), and explicitly lists required versus optional parameters. It clearly distinguishes itself from sibling tools like get_locates and get_locate, which query existing locates.

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 clearly states this tool is for creating a locate request and identifies the minimum required inputs (symbol and quantity). It does not explicitly direct users to alternatives (e.g., get_locates for checking existing requests), but the creation context is unambiguous enough for an agent to infer when it should 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?

There are no annotations, so the description carries the full burden. It does not disclose any side effects, whether duplicates are allowed, authentication requirements, or failure modes. It merely restates the core action without additional behavioral context.

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

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

The description is a single, focused sentence that leads with the verb and resource. It is concise, with no filler or redundant information, and 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?

The tool is simple, the schema fully documents inputs, and an output schema exists. However, the description lacks usage guidance and behavioral caveats, making it minimally viable but incomplete for an agent to confidently select it among the many watchlist-related siblings.

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 both parameters (name and symbols), so the schema already documents them. The description does not add any extra parameter semantics, warranting the baseline score of 3.

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

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

The description clearly states the action ('Creates') and the resource ('a new watchlist'), and adds the detail 'with specified symbols,' which distinguishes it from sibling tools that retrieve or modify watchlists.

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

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

No guidance is provided on when to use this tool versus alternatives such as update_watchlist_by_id or add_asset_to_watchlist_by_id. The description states only the action, leaving the agent to infer the appropriate context from the tool name and sibling list.

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, description must disclose behavioral traits. It only states the action 'delete' without mentioning permanence, cascading effects, auth requirements, or error behavior. Minimal value beyond the name.

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 zero waste; front-loaded verb and object.

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 is simple with one well-documented parameter; description is adequate for basic usage, though it omits behavioral details like return codes or idempotency, which are not critical given low complexity.

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 covers 100% of parameter with description 'watchlist id', so baseline 3 applies. Description adds no additional meaning to the parameter.

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

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

Description uses specific verb 'Delete' with resource 'watchlist' and qualifier 'by its ID', clearly distinguishing from sibling operations like update_watchlist_by_id or get_watchlist_by_id.

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

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

No explicit when-to-use or alternative mention. Usage is implied by the name and action, but the description lacks guidance on prerequisites or distinctions from other watchlist operations.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action without explaining side effects, reversibility, or any submission requirements. No mention of potential outcomes or special conditions, making it insufficiently transparent for an action that modifies an option position.

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 of 10 words, front-loaded with the verb 'Submits.' It contains no redundant information and is efficiently 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?

This is an action tool with no output schema and no annotations. The description fails to provide context such as when the instruction is valid, what happens after submission, or any restrictions. Given the existence of the closely related exercise_options_position, more explanatory detail is required to fully understand the tool's behavior and constraints.

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 one parameter with a description ('Option contract symbol or ID'), giving 100% coverage. The tool description adds the qualifier 'held option contract,' clarifying that the parameter must refer to a contract in the user's position, which goes beyond the schema's generic phrasing and improves semantic clarity.

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 ('Submits') and a resource ('do-not-exercise instruction for a held option contract'), clearly distinguishing it from the sibling exercise_options_position. The 'do-not-exercise' phrasing directly contrasts with the exercise action, making the purpose 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?

No guidance is provided on when to use this tool versus exercise_options_position or other alternatives. The description does not mention prerequisites, timing, or exclusions, leaving the agent to infer usage solely from the name and generic 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, the description must cover behavioral disclosure. It reveals the primary effect (converting option to underlying asset), which is valuable, but it does not mention reversibility, cash requirements, expiration constraints, or whether it applies to both calls and puts. This is a moderate level of 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, concise sentence that immediately states the action and result. Every word contributes value, and the structure is front-loaded with the key verb.

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

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

The description is too brief for a financial action tool with no annotations or output schema. It does not clarify behavior for both call and put options (the phrase 'converting it into the underlying asset' is call-centric and may mislead for puts), nor does it mention prerequisites, return values, or side effects. This leaves significant gaps in context.

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

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

The input schema already fully describes the only parameter ('Option contract symbol or ID.'), so schema coverage is 100%. The tool description adds no additional parameter meaning, hence baseline score of 3 is appropriate.

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

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

The description clearly states the tool's function with a specific verb ('exercises') and resource ('held option contract'), and adds the key consequence ('converting it into the underlying asset'). This distinguishes it from siblings like 'do_not_exercise_options_position' and 'place_option_order'.

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 the use case (exercise an option you hold) but does not explicitly explain when to use it versus alternatives, nor mention any prerequisites or exclusions. The sibling tool 'do_not_exercise_options_position' is not referenced, so guidance on when not to use this tool is absent.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that a list is returned, without mentioning pagination, default ordering, or that this is a read-only operation. Key behaviors like the 'direction' default and page_token usage are omitted from the description, though they appear in the schema.

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, concise sentence that is front-loaded with the core purpose. It contains no redundant information and earns its place by clearly stating what the tool does.

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?

Despite having a rich schema and output schema, the description is minimal. It does not clarify how this tool relates to the sibling get_account_activities_by_type, nor does it explain key behaviors like pagination or date filtering. This is inadequate for a tool with 8 parameters and a complex schema.

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 covers 100% of the parameters with detailed descriptions, so the baseline is 3. The tool description adds no additional parameter semantics beyond what the schema already provides, so the score remains at the baseline.

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 ('Returns') and identifies the resource ('account activities') with examples. It is clear but does not explicitly distinguish from the sibling tool get_account_activities_by_type, which also returns account activities but in a more filtered manner.

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_account_activities_by_type. It does not mention whether this returns all activities or how to filter, leaving the agent to infer usage from the parameter schema.

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, but it only states the return value. It fails to mention pagination, ordering, or any other behavioral characteristics that are not already evident from the schema.

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, making it concise. However, it is so brief that it may under-specify; still, it is appropriately sized for the minimal content it provides.

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 7 parameters and an output schema, the description is too sparse. It doesn't explain the concept of activity types, the date filtering options, or pagination behavior, leaving the agent to rely on the schema without higher-level context.

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

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

Schema description coverage is 100%, and the schema already provides detailed descriptions for all 7 parameters. The description adds no extra parameter semantics beyond what the schema offers, so the baseline score of 3 is appropriate.

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

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

The description uses a specific verb ('Returns') and resource ('account activity entries') with a clear qualifier ('for a specific type of activity'), which distinguishes it from sibling tools like get_account_activities. It effectively communicates the tool's core function.

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 does not mention that get_account_activities exists for broader queries or any other conditions for using this 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?

No annotations are provided, so the description carries the behavioral disclosure burden. It explicitly conveys a read-only operation ('Retrieves') and indicates the current state of the configuration, adding context beyond the tool name. While it does not discuss error conditions or permissions, the zero-parameter, read-only nature makes this adequate, though slightly more detail on response traits could push it higher.

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 leads with the action and includes a concise list of the settings covered. There is no filler or redundant 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?

The tool has zero parameters and includes an output schema for response details, so the description's job is simply to state what the tool does and what it covers. The sentence fully achieves this, making the description complete for this simple read-only 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?

This tool has zero parameters, so the baseline is 4 per the rubric. The description cannot add parameter-specific meaning because there are none; the description's enumeration of output contents is the relevant semantic contribution.

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 'Retrieves' and clearly identifies the resource as 'account configuration settings', while enumerating key settings (trading restrictions, margin, PDT checks, options level). This differentiates it from siblings like get_account_info and update_account_config.

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 clearly implies when to use this tool: whenever the agent needs the account's configuration settings, such as margin or PDT status. It does not explicitly mention alternatives or exclusion criteria, but the specificity of the listed settings provides enough contextual guidance to distinguish it from other account-related 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 of behavioral disclosure. It only says 'retrieves and formats,' but does not explain what 'formats' means, whether authentication is required, data freshness, or any side effects. Basic read-only behavior is implied but not explicitly disclosed.

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 is efficient and avoids excessive detail. The phrase 'and formats' is slightly vague and does not add much actionable value, but overall 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?

Given the tool's simplicity (no parameters) and the presence of an output schema, the description is adequate. It identifies the core resource and data elements ('balances and status'). However, it could slightly benefit from noting that it returns current data or clarifying the 'formats' aspect, though the output schema likely covers return structure.

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 tool has zero parameters and 100% schema description coverage, so there are no parameter semantics to explain. Per the guideline, this yields a baseline of 4. The description adds no unnecessary parameter information, which 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 what the tool does: 'Retrieves and formats the current account information including balances and status.' It uses a specific verb ('retrieves') and resource ('current account information') and adds distinguishing detail ('balances and status') that separates it from siblings like get_account_config or get_account_activities.

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 about when to use this tool versus alternatives. It doesn't mention exclusions, prerequisites, or scenarios where another tool (e.g., get_account_config) would be more appropriate. The context signals show no such guidance in the 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 of behavioral disclosure. It warns about the large unfiltered response size and advises filtering, which is important behavioral context beyond the schema. It doesn't mention pagination or rate limits, but the warning is the most critical behavioral trait for this list endpoint, so a 4 is appropriate.

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 zero wasted words. It front-loads the purpose, includes an essential warning, and names the alternative tool. Every sentence contributes 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?

Given the output schema exists, return values don't need explanation. The description covers the essential usage context: it's a list tool with optional filters, warns about the large response, and directs to a more specific sibling tool. This is complete for a filtered-list tool with fully documented schema.

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 each parameter already having a detailed description, especially the attributes enum. The description adds a hint to use status, asset_class, or exchange for narrowing, but doesn't add new syntax or 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 uses a specific verb and resource: "Get all available assets with optional filtering." It explicitly distinguishes from the sibling tool get_asset by stating "To look up a single asset, use get_asset instead," making the scope clear.

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 explicit when-to-use guidance by warning that the unfiltered response is very large and instructing to always narrow results with status, asset_class, or exchange. It also names the alternative tool (get_asset) for single-asset lookups, which is clear exclusion guidance.

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 must carry the full burden of behavioral disclosure. It only states the return format (JSON) and does not mention whether the operation is read-only, requires permissions, or if there are any side effects. This is a significant gap for a tool with no annotation support.

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

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

The description is a single, front-loaded sentence with no filler. Every word contributes to understanding the tool's action, scope, and output format.

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 that there are no parameters and an output schema exists, the description is sufficient. It specifies what the tool does ('retrieves all current positions'), the scope ('in the portfolio'), and the return format ('as JSON'), which is complete for a simple read-only listing 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 tool has zero parameters, so the schema trivially covers 100% of parameters. The baseline of 4 applies since there is no parameter information to add; the description correctly focuses on what the tool returns.

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

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

The description clearly states the verb 'Retrieves' and the resource 'all current positions in the portfolio', making it distinct from singular siblings like get_open_position and portfolio history tools. The 'all' and 'current' wording provides specific scope.

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

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

The description implies use when a complete snapshot of current positions is needed, but it does not explicitly mention when not to use it or point to alternatives such as get_open_position for a single position. Guidance 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.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'retrieves and formats' but doesn't explain data freshness, potential errors, required permissions, or any limitations. The vagueness of 'formats' also leaves room for ambiguity about the output shape.

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 wasted words. It is front-loaded with the action and resource, making it easy to parse quickly.

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

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

For a simple single-parameter read tool with an output schema, the description is minimally sufficient. However, it lacks context about where this fits relative to snapshot tools and what asset classes are supported, so it's not fully 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?

The parameter schema fully describes symbol_or_asset_id (including CUSIP acceptance), achieving 100% coverage. The description adds no extra parameter semantics, 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 verb 'retrieves and formats' and the resource 'detailed information about a specific asset', which is distinct from sibling tools like get_all_assets that list assets. It precisely indicates the scope of a single asset.

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

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

No guidance is provided on when to use this tool versus alternatives such as get_stock_snapshot or get_crypto_snapshot. There is no mention of asset classes, use cases, or exclusions, leaving the agent to infer applicability.

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 discloses a critical behavioral trait: omitting date bounds yields an extremely large multi-year response. It also implies formatting behavior. This is valuable beyond what the schema provides.

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, purpose first, followed by a critical warning. Every sentence earns its place, with 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?

Given the output schema exists, the description need not explain return values. It covers the main pitfall (large response) and the tool's purpose. Combined with high schema coverage, the description is complete for this 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 coverage is 100%, so the baseline is 3. The description adds meaningful guidance by specifying the date format (YYYY-MM-DD) and emphasizing that both start and end are required in practice. This goes beyond the schema's date-time format and optional flags.

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 ('Retrieves and formats') with a clear resource ('market calendar') and scope ('for specified date range'). It distinguishes itself from sibling tools like get_clock by focusing on the calendar rather than current time.

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 explicitly instructs users to always provide start and end dates, with a warning about the consequences of omitting them. However, it does not mention alternative tools or exclusions, so it falls short of full usage guidance.

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 that the tool retrieves and formats data, indicating a read-only operation. However, it does not describe potential side effects, authentication requirements, or behavior when the market is closed (e.g., whether next open/close times are still returned). This minimal disclosure is adequate but leaves 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, well-structured sentence that front-loads the action ('Retrieves and formats') and the target information ('current market status and next open/close times'). No unnecessary words or repetition.

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 simple, has no parameters, and an output schema is present (per context signals). The description conveys the core purpose without needing to detail return fields. It could be slightly more specific about what 'market status' includes (e.g., open/closed, extended hours), but given the output schema, this is adequate.

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 tool has zero parameters, so the schema covers 100% of parameter semantics. The description adds no parameter-specific information, but none is needed. Per guidelines, a zero-parameter tool gets a baseline score of 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 clearly states the tool retrieves and formats current market status and next open/close times. It specifies a distinct resource (current market status, times) and is easily distinguishable from sibling tools like get_calendar, which focus on calendar dates rather than the current state.

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 implied usage is evident: when you need to know if the market is open and when it next opens/closes. However, it does not explicitly mention alternatives or provide exclusion criteria. Since get_calendar is a sibling tool that might be confused with this, additional guidance on when to use get_clock vs get_calendar would improve the score.

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

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

With no annotations provided, the description carries full burden. It indicates a read operation via 'Retrieves' but discloses no other behavioral traits such as 404/error handling, permissions, or what happens if the ID does not exist. The description is minimal and does not add value beyond the name and parameter schema.

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 concise sentence that directly states the action without unnecessary words. It is well-structured and 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 simplicity of the tool (one parameter, output schema exists) the description is adequate for basic usage. However, it lacks context on error cases, prerequisites, or how this fits with the plural sibling tool, leaving gaps for an AI agent.

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

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

Schema description coverage is 100%, so the schema already documents the 'id' parameter. The description's 'by ID' adds marginal emphasis but no new semantic detail, matching the baseline of 3.

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

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

The description clearly states the tool retrieves a single corporate action announcement by ID, which is a specific verb+resource+scope. It distinguishes from the sibling 'get_corporate_action_announcements' (plural) by indicating it operates on a single known ID.

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 'by ID' implies the tool is for fetching a specific announcement when the ID is known, but it does not explicitly differentiate when to use this versus the plural sibling tool or mention alternatives/exclusions. Guidance is implicit rather than explicit.

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 for behavioral disclosure. It does warn that broad queries can return very large responses, which is a useful performance trait. However, it does not disclose other behaviors such as pagination, rate limits, or any side effects. Given this is a read operation, the warning is the main behavioral note, but more context could be added.

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 only two sentences: the first states the core purpose, the second gives a crucial usage warning. There is zero wasted text, and the most important actionable advice is front-loaded. This is a model of conciseness.

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

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

Given the presence of an output schema (per context signals), the description does not need to explain return values. It covers the essential selection information: what the tool retrieves and how to scope invocations effectively. The guidance about broad queries is important context. While it could mention optional params beyond symbol, the schema already defines them, so the description plus schema is sufficiently complete for correct invocation.

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

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

The input schema has 100% parameter coverage, so the schema already provides full meaning for all six parameters. The description does not add new semantic details beyond the schema, though it suggests filtering by symbol and using narrow date ranges, which is more of a usage guideline than parameter semantics. This aligns with the baseline 3.

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

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

The description clearly states the tool retrieves corporate action announcements with specific types listed (dividends, mergers, splits, spinoffs). It uses a specific verb and resource, making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like get_corporate_action_announcement (singular) or get_corporate_actions, so it misses the differentiation that would earn a 5.

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

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

The description provides explicit practical guidance: 'Use a narrow date range and filter by symbol when possible — broad queries can return very large responses.' This tells the agent when to use the tool with constraints and warns about performance. It lacks explicit alternatives or exclusions, but gives clear context for invocation, earning a 4.

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

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

The description implies a non-destructive read operation ('retrieves') and mentions output formatting, but it does not disclose behaviors such as default date ranges, sorting, pagination, or any potential side effects. With no annotations provided, the description carries the burden but only partially addresses it.

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 concise sentence that directly states the tool's purpose without any wasted words. It is appropriately front-loaded and easy to parse.

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

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

The tool has 10 optional parameters and a complex query interface, yet the description offers no overview or usage context. It does not explain how this tool fits with siblings or what scenarios it is designed for, leaving the agent to rely entirely on the schema. The output schema exists, so return values are covered, but the description is still inadequate for the tool's complexity.

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 provides 100% coverage of parameter descriptions, so the description adds no additional semantic value. The baseline of 3 is appropriate since the schema already documents all parameters.

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

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

The description clearly states the tool retrieves and formats corporate action announcements, using a specific verb and resource. However, it does not differentiate from the sibling tool get_corporate_action_announcements, which likely serves a similar purpose, so it lacks distinctiveness.

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, nor any exclusions or prerequisites. It simply states what it does without contextual usage direction.

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

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

Annotations already declare readOnlyHint=true and openWorldHint=true, lowering the bar. The description adds valuable behavioral details: automatic lookback calculation when start is omitted, limit semantics ('Max total data points returned across all symbols'), and sort order. It doesn't mention pagination, but for a read-only historical data tool, this is sufficient context beyond the annotations.

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

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

The description is well-structured: a one-sentence purpose followed by a labeled Args block. Every parameter earns its place, and the text avoids redundancy. It is longer than minimal, but the parameter count (9) justifies the detail. The content is front-loaded with the main verb and resource.

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

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

Given the tool's complexity (9 parameters, 1 required), the description covers all parameters, defaults, lookback logic, and sort/limit behaviors. The output schema exists, so return value details aren't needed in the description. This is complete for an agent to select and invoke 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 0%, so the description carries the full burden, and it excels. The Args section explains each parameter's meaning, defaults, formats, and special behaviors—e.g., 'Inclusive start time', 'Max total data points across all symbols', 'Additional hours in the lookback'. This far exceeds the raw schema, making parameter semantics exceptionally clear.

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+resource: 'Retrieve historical price bars (OHLCV) for one or more cryptocurrencies.' This clearly distinguishes it from sibling tools like get_stock_bars and get_option_bars by explicitly naming crypto, and from get_crypto_latest_bar by indicating historical data. The purpose 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 clear context for when to use the tool (for crypto OHLCV data) and explains behavior for omitted start/end, but it does not explicitly name alternative tools or exclusions. The sibling tool list shows many bar/quote/trade tools, but the description itself doesn't state 'use this instead of get_stock_bars for crypto.' Thus it earns a 4 for clear context without explicit alternatives.

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

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: the loc parameter must always be 'us', and the tool only returns the latest minute bar. However, it does not address potential edge cases (e.g., what happens if another loc is passed) or mention the read-only nature explicitly, though 'Returns' implies it. The description is adequate but sparse.

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 concise sentences, front-loaded with the primary purpose. The first sentence states what the tool does, and the second gives a critical usage instruction. Every word contributes meaning; 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 simple tool with a rich output schema and fully described parameters, the description is mostly complete. It covers the essential purpose and the mandatory loc value. It could be improved by noting that this is for real-time latest data only and that historical data requires get_crypto_bars, but the absence is minor given the simplicity and schema support.

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 describes both parameters with 100% coverage, so a baseline of 3 applies. The description adds extra meaning for the loc parameter by specifying that it must always be set to 'us', which is not evident from the schema alone (since the enum lists multiple options). This guidance is valuable and raises the score.

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 a specific verb ('Returns') and resource ('latest minute bar for one or more crypto symbols'), which distinguishes it from related tools like get_crypto_bars (which likely returns historical bars) and other latest-data tools (trade/quote). It is unambiguous and leaves no doubt about the tool's function.

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 a useful parameter instruction ('always set loc to "us"'), which is a form of usage guidance. However, it does not explicitly mention when to use this tool versus alternatives such as get_crypto_bars or when a different loc value would be appropriate. The condition is implied by the word 'latest' but not stated.

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

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

With no annotations, the description discloses important behavioral traits: the response includes 'full order book depth and can be large'. It also highlights a required parameter value. However, it does not explicitly state that this is a read-only operation or mention rate limits.

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 short sentences each serve a distinct purpose: definition, mandatory parameter, and output size warning. No unnecessary filler or repetition.

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 a simple 2-parameter tool with an output schema present, the description covers the essentials: what it returns, the key parameter constraint, and the large response. The only minor gap is the potential confusion between the enum values and the directive to always use 'us'.

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%, but the description adds value by telling the agent to always set loc to 'us' despite the enum allowing other values. It also confirms that symbols can be a list ('one or more'), matching the comma-separated format.

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 'Returns the latest orderbook for one or more crypto symbols', specifying the verb, resource, and scope. This distinguishes it from sibling tools like get_crypto_latest_trade and get_crypto_latest_quote.

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 clear context for when to use the tool and includes a critical operational instruction ('always set loc to "us"'). It does not explicitly name alternatives or exclusions, but the large response warning helps set expectations.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that loc is required and should be 'us' and that multiple symbols are supported, but it does not explicitly indicate that the operation is read-only, nor does it cover error conditions, rate limits, or any side effects. This is minimal disclosure for a tool that could be used without additional safety context.

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

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

The description is only two sentences, both front-loaded with essential information. The first sentence states the purpose, and the second gives a critical parameter instruction. Every word earns its place, with 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 simple tool with only two parameters and an output schema, the description is largely sufficient. It conveys the core functionality and the key loc constraint. The only notable gap is the lack of guidance on when to prefer this over sibling tools, but that belongs to the usage dimension. Given the low complexity, the description covers what an agent needs to invoke it correctly.

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

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

Schema coverage is 100% with descriptions for both loc and symbols. The description adds the directive to always set loc to 'us', which is a meaningful recommendation beyond the schema's enum listing. It also clarifies that symbols can be one or more, reinforcing the comma-separated format. This additional value justifies a score above the baseline of 3.

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

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

The description clearly states the tool's function: 'Returns the latest quote for one or more crypto symbols.' It identifies the resource (crypto quotes) and action (retrieve latest). It distinguishes from trade or bars tools by resource type, but does not explicitly compare with sibling quote tools like get_crypto_quotes, 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?

The description provides no guidance on when to use this tool versus alternatives such as get_crypto_latest_trade or get_crypto_quotes. The only usage instruction, 'always set loc to "us"', is parameter-level advice, not tool-selection guidance. Thus, it does not help an agent decide between this and other quote-related 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 must carry the disclosure burden. It does indicate a read-only operation ('returns') and communicates the required loc constraint, but it omits details such as response structure for multiple symbols, error behavior, or rate limits. The output schema covers return format, mitigating some risk.

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, front-loaded with the core function. 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?

For a simple latest-trade tool with an output schema and full parameter descriptions, the description covers the essential operation and the critical loc value. It lacks explicit sibling differentiation, but output schema reduces the need to describe the return format. Overall sufficient for invocation.

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

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

Schema coverage is 100%, providing baseline 3. The description adds value by instructing the agent to always set loc to 'us', which disambiguates the enum and prevents incorrect selections. It also confirms the required nature of loc beyond the schema's required array.

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 ('returns'), identifies the resource ('latest trade'), and scopes it to 'one or more crypto symbols', clearly distinguishing it from sibling tools like get_crypto_trades (historical trades) or get_stock_latest_trade.

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 provides a clear parameter-level directive ('always set loc to "us"') but does not explicitly state when to choose this tool over sibling tools like get_crypto_trades or get_crypto_latest_quote. The tool name implies the use case, so usage context 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.

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

With annotations already declaring readOnlyHint=true, the description adds valuable behavioral context beyond that: it explains the automatic lookback computation when start is omitted and the 'limit' parameter's cross-symbol semantics. It does not contradict the read-only annotation, and there are no destructive concerns.

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 efficiently structured: a one-sentence purpose, a note about the start-omitted behavior, then a clear Arg list. Every line is informative, and the length is appropriate for a tool with 8 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?

The description covers the tool's behavior comprehensively: parameter formats, defaults, time-zone semantics, and cross-symbol limits. Since an output schema exists, the lack of explicit return-value documentation is not a gap. It is complete for a historical-quotes 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?

Given the schema has 0% per-parameter description coverage, the description fully compensates by documenting every parameter: symbols format with examples, start/end RFC 3339 and omission behavior, units for days/hours/minutes, limit range (1-10000), and sort values. This far exceeds the bare schema.

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

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

The description opens with a specific verb and resource: 'Retrieve historical bid/ask quotes for one or more cryptocurrencies.' This clearly distinguishes it from sibling tools like get_crypto_latest_quote (latest rather than historical) and get_crypto_bars (bars, not bid/ask quotes).

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 establishes clear context by specifying 'historical' quotes, implying it is for past data rather than current/latest quotes. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.

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 discloses a critical constraint (loc must always be 'us') and lists the included data components, but does not mention safety profile, rate limits, or response format beyond what the output schema already covers. It 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 concise sentences: the first states purpose and contents, the second gives a specific parameter instruction. No unnecessary words, and the most important usage constraint (loc='us') 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?

The description covers the tool's main purpose and a key constraint. Since an output schema exists, return structure is already documented. It lacks a note about sibling tools or when not to use it, but for a straightforward snapshot read operation, it is largely 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 coverage is 100% for both parameters. The description adds value by emphasizing that loc is required and should always be set to 'us' (despite other enum options), and clarifies that symbols accepts one or more comma-separated crypto symbols, enhancing parameter understanding.

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

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

The description clearly states the tool returns a snapshot for one or more crypto symbols, listing its contents (latest trade, quote, minute bar, daily bar, previous daily bar). This specific verb+resource+scope distinguishes it from sibling tools like get_crypto_latest_trade or get_crypto_bars.

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 usage instruction for the loc parameter ('always set loc to "us"'), which is helpful. However, it does not explicitly mention alternatives or when to use this tool versus sibling snapshot-related tools, so usage guidance 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.

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

Annotations already declare readOnlyHint: true and openWorldHint: true, so the safe-read nature is established. The description adds valuable behavioral context: automatic start computation from lookback parameters when start is omitted, inclusive time ranges, limit across all symbols, and default values. This goes beyond the annotations without contradicting them.

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 and well-structured: a one-sentence purpose, a brief note on start behavior, then a clear bullet-like arg list. Each parameter has a concise explanation without unnecessary elaboration. It is front-loaded with the main verb and resource.

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 8 parameters, 1 required, no schema descriptions, and an output schema present, the description covers all functional aspects: how to specify symbols, time range options, lookback logic, limit constraints, and sort behavior. It does not need to explain return values because an output schema exists, and it provides enough context to invoke 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 description coverage is 0%, so the description must fully explain all 8 parameters, and it does. It provides meaning, defaults, examples, and conditional behavior for each parameter (e.g., symbols format, start/end inclusivity, lookback combination, limit range, sort order). This fully compensates for the lack of schema descriptions.

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: "Retrieve historical trade data for one or more cryptocurrencies." This clearly distinguishes it from sibling tools like get_crypto_latest_trade (latest trade), get_crypto_bars (OHLC bars), and get_crypto_quotes (quotes). The scope is explicit and 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 implies usage for historical trade data and provides detailed parameter semantics, but it does not explicitly compare with alternatives or state when not to use this tool. No exclusions or alternative tool names are mentioned, leaving the selection decision to inference from the tool name and sibling list.

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 full burden of behavioral disclosure. It clearly states what the tool returns (bid/ask prices, sizes, yield-to-maturity) and the required input format, which gives the agent an accurate mental model. It does not cover error handling or latency, but for a read-only quote retrieval this is sufficient.

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 the core purpose front-loaded in the first sentence and a concrete example and output details in the second. Every sentence adds value, with no redundant or filler content.

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 simplicity and the existence of an output schema, the description sufficiently covers purpose, input requirements, and return content. It does not explain edge cases like invalid ISINs, but the combination of schema descriptions and output schema makes it complete enough for an agent to use the tool effectively.

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

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

The input schema already fully describes both parameters (ising list and trade_size) with 100% coverage. The description reinforces the isins parameter with an example but adds no additional meaning for trade_size. Thus it merely meets the baseline without exceeding what the schema provides.

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: returning latest quotes for fixed income securities. It specifically names the asset class (bonds, treasuries) and distinguishes it from sibling quote tools for stocks, crypto, and options. The verb 'Returns' is precise and actionable.

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 usage context by telling the agent to provide a comma-separated list of ISINs, including an example. It implies this is the tool for fixed income quotes. However, it does not explicitly state when not to use it or mention alternative tools, so it lacks explicit exclusions.

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

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

With no annotations, the description carries the full disclosure burden but merely restates the tool's name. It does not mention data freshness, supported symbol formats, error conditions, or return value nuances, providing little beyond the obvious.

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 concise, front-loaded sentences with no wasted words. The examples are useful without adding excessive length.

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

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

For a simple read-only tool with an output schema, the description is minimally sufficient but lacks clarity on which indices are supported and how this differs from get_index_values. An agent may need additional context to select the correct 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 input schema already fully documents the symbols parameter as a comma-separated list. The description repeats this and adds three examples, which is marginal added value. Since schema coverage is 100%, 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 tool returns latest values for market indices, with specific examples (SPX, VIX, DJI). However, it does not distinguish this from the sibling tool get_index_values, 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?

The description only explains how to format the symbols parameter, not when to use this tool versus alternatives. No context or exclusions are provided, leaving the agent to guess applicability.

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 that the tool supports pagination, sorting, and date range filtering, and that it returns historical values (implying a read-only operation). However, it does not provide deeper behavioral context such as default time ranges, pagination token usage, or any side effects. This is adequate but minimal for a 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?

The description is two sentences long, front-loaded with the core purpose, and every sentence earns its place. It avoids redundancy and is easily scannable.

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 an output schema and six parameters, so the description does not need to explain return values or parameter details. It covers the high-level capabilities (historical values, pagination, sorting, date filtering) relevant for selection and initial invocation. It does not mention edge cases like defaults for 'start' and 'end', but those are documented in the schema, making the description sufficient for its purpose.

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

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

Schema description coverage is 100%, so the input schema already documents all parameters thoroughly. The description's only parameter hint is 'Provide a comma-separated list of index symbols,' which duplicates the schema description for 'symbols' and adds no new meaning. Therefore, the description adds no value beyond the schema, matching the baseline.

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 a specific action: 'Returns historical values for market indices over a time interval.' This distinguishes it from the sibling tool get_index_latest_values by emphasizing 'historical' values, making the purpose 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 provides clear context: it is for historical index values with date range filtering, pagination, and sorting. It also instructs the user to 'Provide a comma-separated list of index symbols.' While it does not explicitly name alternative tools for latest values, the phrase 'historical values' implicitly guides usage away from get_index_latest_values.

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 for behavioral disclosure. It only says 'Returns' without detailing error behavior, authentication requirements, side effects, or its read-only nature. It also does not clarify what happens when the ID does not 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?

The description is a single, front-loaded sentence that directly states the tool's purpose. There is no wasted wording or redundant 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?

For a simple single-ID retrieval tool, the description combined with the complete input schema and output schema provides an adequate core contract. However, it could benefit from noting its relationship to get_locates or handling of missing IDs, so it is slightly above the minimum viable.

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

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

The input schema has 100% coverage with a clear description for locate_id, so the schema already documents the parameter. The description's phrase 'by its ID' adds no additional semantic detail beyond what the schema 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 uses a specific verb ('Returns') and a specific resource ('a single locate request by its ID'), clearly distinguishing it from sibling tools like get_locates (plural, likely listing) and get_locate_quotes. It precisely identifies the tool's function.

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

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

The description provides no guidance on when to use this tool versus alternatives such as get_locates or get_locate_quotes. It lacks any mention of prerequisites, exclusions, or alternative conditions, so the 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. It discloses that the tool returns data (read-only), but it does not mention any additional behavioral traits such as data freshness, rate limits, required permissions, or handling of invalid symbols. The description adds minimal context beyond the basic read operation, which is insufficient for a tool with no annotation support.

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

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

The description is two short sentences, front-loaded with the core purpose and followed by a concise usage instruction. Every word earns its place, with no redundancy or irrelevant information. This is an example of efficient writing.

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?

This is a simple single-parameter read tool with an output schema available, so the description covers the essential purpose and invocation. The main gap is not differentiating from similar sibling tools like 'get_locates', but given the low complexity and presence of an output schema, the description is sufficiently complete for correct use.

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

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

Schema coverage is 100% with the 'symbols' parameter already described as a comma-separated list with a max of 100 unique symbols. The description merely repeats this ('Provide a comma-separated list of symbols'), adding no new semantic meaning. According to the rubric, a baseline of 3 is appropriate when the schema fully covers parameter semantics.

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

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

The description clearly states the tool's function: 'Returns locate availability and pricing for one or more symbols.' It uses a specific verb ('returns') and identifies a distinct resource ('locate availability and pricing'), which differentiates it from sibling tools like get_stock_quotes or get_locates. The scope is explicit, making the purpose 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 implies when to use this tool (when you need locate quotes for symbols) and gives input instructions ('Provide a comma-separated list of symbols'). However, it does not provide explicit alternatives or exclusions, such as explaining the difference between this tool and the similar 'get_locates' or 'get_locate' siblings. Usage context is clear but not differentiated.

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 full burden for behavioral disclosure. It mentions the sort order (creation date descending) but omits pagination behavior, result limits, and any details about the date timezone semantics that are only in the schema. For a read tool, this is a minimal but present 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?

The description is two sentences long, front-loads the core purpose, and contains no filler or redundant information. Every word 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?

With an output schema present, return values are covered. However, given the absence of annotations and the large set of sibling tools, the description does not hint at when to use this list endpoint versus the singular get_locate, nor does it mention pagination for large result sets. The rich schema partially compensates, but the description itself is 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?

The schema provides 100% coverage with detailed descriptions for all six parameters, including formats, enums, and pagination token mechanics. The description adds no extra meaning beyond summarizing that filtering is by status, symbol, or date range, 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 clearly states it returns locate requests for the account and lists the filter dimensions (status, symbol, date range). It uses a specific verb and resource. While it does not explicitly differentiate from the sibling get_locate, the plural 'requests' strongly implies a list operation, so it mostly distinguishes itself.

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 given on when to use this tool versus alternatives like get_locate (singular) or create_locate. The description only explains what the tool does, not when it should be chosen. There are no exclusions or alternative tool mentions.

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 discloses that results are based on real-time SIP data and that both gainers and losers are returned, which is useful behavioral context. However, it does not specify the calculation period, sorting, or any potential rate limits, leaving some transparency 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 that is front-loaded and free of unnecessary words. It conveys the purpose and data source economically, every word 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?

The tool is simple and provides an output schema, so the description doesn't need to explain return structure. It covers the essential purpose and data source. The description is complete enough for this level of complexity, though additional caveats (e.g., market hours) could be added.

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 fully explains both parameters (market_type and top). The tool description adds no parameter-specific information beyond what the schema 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 clearly states the tool's function: returning top market movers (gainers and losers) using real-time SIP data. It is specific about the resource and differentiates from sibling tools like get_most_active_stocks by focusing on movers rather than activity.

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 does not provide explicit guidance on when to use this tool versus alternatives. It only states what the tool returns, leaving the agent to infer usage context. No exclusions or sibling comparisons are mentioned.

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

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

With no annotations, the description must disclose behavior but provides only a general screening action and the ranking metric. It does not mention output structure, time frame (per day), or limitations, placing the burden on the schema instead.

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 concise sentence that front-loads the purpose and includes the key differentiating detail (volume or trade count). No filler or redundancy.

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

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

Given the simple structure with output schema and complete parameter descriptions, the description is minimally viable. However, it lacks usage differentiation from get_market_movers and does not explicitly clarify 'per day' semantics, leaving some context 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% and documents both 'by' and 'top' clearly. The description adds no new parameter detail beyond restating the 'by' metric, 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?

Description uses the verb 'screens' and clearly identifies the resource (most active stocks) and the ranking criteria (by volume or trade count). It distinguishes from quote/bar retrieval siblings, but does not explicitly contrast with the similar get_market_movers.

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

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

No guidance on when to use this tool versus alternatives. It does not mention scenarios, prerequisites, or exclusions, and the overlap with get_market_movers is unaddressed.

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 return type (headlines, summaries, URLs, ticker symbols) but does not mention pagination behavior, result limits, or content inclusion flags—these are left to the schema. The behavior is not misleading, but the description adds only modest transparency beyond the schema's parameter descriptions.

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 filler. The first sentence immediately states the core function, and the second covers filtering and output. Every word adds value, making it highly efficient and 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 has 8 optional parameters and an output schema, the description is reasonably complete. It covers the main use case (filtering and retrieving news) without explaining return values in detail, which is appropriate since the output schema exists. It could mention pagination or limits, but those are well-defined in the schema, so the description suffices for initial selection and invocation.

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

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

Schema description coverage is 100%, so each parameter already has a description. The tool description summarizes key filtering dimensions (symbols, date range, sort order) but does not add detail beyond the schema. This aligns with the baseline of 3 when schema covers parameter semantics.

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

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

The description explicitly states 'Retrieves news articles for stocks and crypto,' which is a specific verb+resource combination. It clearly differentiates from sibling tools like quotes, bars, and trades, which retrieve market data rather than news. The mention of 'headlines, summaries, URLs, and associated ticker symbols' further clarifies the tool's purpose.

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

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

The description says 'Filter by symbols, date range, and sort order,' which establishes the tool's typical usage context. While it doesn't explicitly exclude alternatives or name when-not-to-use, the sibling list shows no other news retrieval tool, so the usage context is clear without needing exclusions.

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

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

Annotations are absent, so the description carries the burden. It indicates a read operation via 'Retrieves' and implies no mutation, but it does not disclose behavior on missing positions, authentication requirements, or any formatting details. This is a minimal but not misleading 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?

The description is a single concise sentence that earns its place without fluff. 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?

Given the simple nature of the tool, one parameter, and an output schema that covers return structure, the description is mostly complete. However, it lacks any contextual guidance on when to prefer this over get_all_positions, leaving a minor gap.

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 parameter with 100% coverage ('symbol or assetId'). The description adds no additional parameter semantics beyond the generic reference to a 'specific open position'.

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 verb 'Retrieves' and specifies 'details for a specific open position', clearly distinguishing it from sibling tools like get_all_positions. The term 'formats' adds a hint about output structure, though it's slightly vague. Overall, it states a specific verb and resource.

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 usage guidance is provided. The description does not mention when to use this tool instead of getting all positions or closing a position, nor does it specify prerequisites or exclusions.

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

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the core purpose. It does not mention pagination, default time ranges, real-time access implications, or the fact that the limit applies to the total number of data points, though some of this is available in the schema.

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

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

The description is a single, clear sentence with no wasted words. It is front-loaded with the key purpose and reads efficiently.

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 rich input schema and presence of an output schema, the description is minimally acceptable. However, it does not provide behavioral context such as how to handle pagination or the availability of real-time data, which might be important for a tool with 7 parameters. The description is sufficient for a basic understanding but not fully complete for decision-making.

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 thoroughly documents all parameters. The description adds no additional parameter-level information. Baseline of 3 is appropriate given the high schema coverage.

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

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

The description uses a specific verb ('Retrieves') and clearly identifies the resource ('historical bar (OHLCV) data for one or more option contracts'). This unambiguously distinguishes it from sibling tools like get_stock_bars and get_crypto_bars, which focus on different asset classes.

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

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

No guidance is provided on when to use this tool versus alternatives. The description only states what it does, not when to choose it or exclude other options. There is no mention of alternatives, prerequisites, or typical use cases.

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

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

No annotations are provided, so the description carries the burden. It adds a key behavioral trait: 'The response can be very large,' which warns about payload size. However, it doesn't disclose pagination behavior or data source (e.g., real-time vs delayed), which could affect invocation.

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 with no fluff. First sentence states the purpose, the second provides usage guidance. Immediately front-loaded with the action.

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 12 parameters and a rich output schema, the description covers the essential purpose and filtering guidance. It doesn't explain pagination, but the schema includes page_token descriptions. It lacks explicit comparison to sibling tools, but the content (trade, quote, IV, greeks) helps differentiate. Overall adequate for a complex 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 coverage is 100%, so baseline is 3. The description adds value by highlighting the most relevant filter parameters (type, strike_price_gte/lte, expiration_date, limit) and their purpose in narrowing results. This gives the agent actionable guidance beyond schema descriptions.

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 'Retrieves option chain data for an underlying symbol' with a specific verb and resource, listing included data (trade, quote, IV, greeks). This distinguishes it from sibling tools like get_option_contract or get_option_snapshot.

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 does not explicitly name alternative tools, but it provides clear context for when filtering is needed ('The response can be very large. Use the type... parameters to narrow results'). This implies usage for broad chain queries but lacks explicit exclusion or alternative references.

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. 'Retrieves' implies a read-only operation, but the description does not disclose any behavioral traits such as potential error responses, required permissions, or differences from similar snapshot/quote tools. It adds minimal value beyond the tool name.

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, concise sentence that is front-loaded with the verb and resource. It contains no redundant words and is easy to scan.

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

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

The description is adequate for a simple single-parameter retrieval tool, especially given the presence of an output schema. However, it lacks guidance on how to format symbols or distinguish this tool from the many similar option-related siblings (e.g., 'get_option_snapshot', 'get_option_latest_quote'). The completeness is sufficient but not enriched.

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 covers 100% of the single parameter ('symbol_or_id' with 'symbol or contract ID'). The tool description merely repeats this information and adds no extra semantic detail, such as the expected format of a symbol or how to use a contract ID. Baseline 3 applies because schema coverage is high.

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

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

The description clearly states the verb ('Retrieves'), the resource ('option contract'), and the method ('by symbol or contract ID'). It explicitly says 'single', which distinguishes it from the plural sibling 'get_option_contracts' and other option-related tools like 'get_option_chain'.

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 this tool is for retrieving a single option contract when you have a symbol or contract ID. However, it does not explicitly mention alternatives or when not to use it (e.g., for batch lookups use 'get_option_contracts'). It provides clear context but no exclusions.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only implies a read-only operation via 'Retrieves' but omits important behaviors like pagination, default filters (e.g., active contracts only), or any side effects. This is insufficient for a tool with such a broad filter set.

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, direct sentence with no extraneous content, making it concise and front-loaded. However, its brevity leaves out valuable context, so it loses a point for being too sparse relative to the tool's complexity.

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

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

Despite a rich schema and output schema, the description is minimal and does not address the tool's complexity, such as whether it supports pagination, how it relates to get_option_contract, or what kind of data is returned. This makes the description incomplete for an agent to confidently select and invoke the tool.

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

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

The schema has 100% parameter description coverage, so the schema itself documents all parameters. The description adds no additional meaning beyond the resource type, earning the baseline score of 3 as per the rubric.

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 retrieves option contracts for underlying symbols, using a specific verb and resource. However, it does not distinguish itself from sibling tools like get_option_contract (singular) or get_option_chain, which could be confused for similar functionality.

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

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

No guidance is provided on when to use this tool versus alternatives. The description merely states what it does, without mentioning suitable scenarios or exclusions, leaving the agent to infer usage from the tool name and parameters 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. It does indicate a read-only operation via 'Retrieves', but it doesn't disclose any additional behavioral traits like idempotency, safety, or whether it's a static map vs. dynamic query. For a simple lookup tool, this is adequate but lacks depth.

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, front-loaded with the main action and purpose. Every word earns its place. It's efficient and clear without any fluff.

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

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

Given the tool's simplicity (0 parameters, output schema present), the description is complete. It explains what the tool does and why it's useful, and the output schema covers return values. The context signals confirm no hidden complexity, so nothing 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?

The tool has zero parameters, and the schema confirms no required inputs. With 0 params, the baseline is 4. The description doesn't need to explain parameters, and the mapping functionality is self-explanatory. The baseline for 0 parameters is appropriate.

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

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

The description clearly states the tool's function: 'Retrieves the mapping of exchange codes to exchange names for option market data.' This is a specific verb and resource, and the 'useful for interpreting exchange fields' distinguishes it from sibling option data tools. It's a reference lookup, not a data retrieval 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?

The description provides clear usage context: 'Useful for interpreting exchange fields returned by other option data tools.' This implies when to use it, but it doesn't explicitly state when not to use it or mention alternatives. It gives a strong contextual clue without formal exclusions.

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

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

There are no annotations, so the description carries the full burden for behavioral disclosure. It states the action and output content but doesn't delve into nuances like latency, indicative feed modifications, or formatting specifics. The schema's feed description covers some of this, but the description itself adds limited behavioral context beyond the basic retrieval.

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 immediately states the purpose and key output attributes. It is front-loaded with the action and resource, with no filler or redundant wording.

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 simplicity (2 parameters, output schema provided), the description offers a clear overview. It doesn't explicitly mention multi-symbol support or the feed parameter, but those are fully covered in the schema. The combination of the description and structured data is sufficient for a basic read tool, though a bit more context about output format could be added.

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% for both parameters, so the baseline is 3. The description doesn't add any parameter-level detail beyond what the schema already provides, so it neither elevates nor reduces the score.

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 phrase 'Retrieves and formats' and clearly identifies the resource as 'latest quote for one or more option contracts.' It also lists concrete content (bid/ask prices, sizes, exchange information), which distinguishes it from sibling tools like get_option_latest_trade or get_stock_latest_quote.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the feed selection trade-offs or suggest scenarios where this tool is preferred. Although the schema's feed description gives some context, the main description lacks any usage direction.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the obvious action and does not mention potential delays, feed differences, data source implications, or any limitations. Without this, the agent cannot anticipate the behavior beyond the basic function.

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

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

A single, concise sentence communicates the core functionality without any unnecessary words. The structure is front-loaded with the verb and resource.

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 simplicity, the presence of a complete output schema, and full schema descriptions for parameters, the description is adequate. It could be enhanced with usage guidance, but the essential information for invoking the tool is present.

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 parameters (feed, symbols) have descriptive schema text. The tool description itself adds no additional parameter meaning, 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 (retrieves), the resource (latest trade), and the scope (one or more option contracts). It distinguishes itself from sibling tools like get_option_latest_quote (quotes vs. trades) and get_option_trades (historical vs. latest).

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

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

The description provides no guidance on when to use this tool versus alternatives such as get_option_latest_quote or get_option_trades. It does not mention scenarios, prerequisites, or exclusions. The usage context is implied by the name but not explicitly stated.

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

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

No annotations are provided, so the description must convey behavior. It only lists content fields and says 'comprehensive', but fails to disclose important behaviors such as pagination (limit/page_token), feed distinctions (opra vs indicative), or that snapshots may reflect trade/quote timestamps. This is a significant gap for a tool with such parameters.

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

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

The description is a single sentence, front-loaded with the primary action ('Retrieves comprehensive snapshots') and ends with the key inclusions. No wasted words; every component 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?

The schema and output schema are rich, so not explaining return format is acceptable. However, the description lacks behavioral context (pagination, feed selection) and usage guidance, which are critical for an agent to select and invoke this tool correctly among many option-related siblings. It is adequate but not 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?

The schema has 100% description coverage for all five parameters, including meanings, defaults, and constraints. The tool description adds no parameter-specific semantics 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 uses a specific verb ('Retrieves') and resource ('comprehensive snapshots of option contracts'), and explicitly lists the included data fields (latest trade, quote, implied volatility, Greeks). This clearly distinguishes it from sibling tools like get_option_latest_quote or get_option_chain, which target narrower or different 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 phrase 'comprehensive snapshots' implies this is for broad option data rather than a single latest quote or trade, but no explicit alternatives are mentioned. There is no direct 'when to use vs. when not to use' guidance, leaving the agent to infer from the word 'comprehensive'.

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