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 speeches are sorted by publication date (most recent first), which is useful behavioral context. However, it doesn't mention rate limits, authentication needs, error handling, or pagination behavior, leaving gaps for a read operation.

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 with zero waste. The first sentence states the purpose, and the second adds key behavioral detail (sorting). It's front-loaded and appropriately sized for a simple tool.

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

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

For a read-only tool with no annotations, 100% schema coverage, and no output schema, the description is minimally adequate. It covers purpose and sorting behavior but lacks details on return format (e.g., fields in speeches), error cases, or integration with sibling tools, leaving room for improvement.

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 fully documents both parameters (limit and since_date). The description doesn't add any parameter-specific details beyond what's in the schema, such as explaining how 'latest' interacts with since_date. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Get the latest Federal Reserve speeches' specifies the verb (get) and resource (speeches). It distinguishes from siblings by focusing on 'latest' (most recent) rather than filtering by speaker, type, or search terms, though it doesn't explicitly name alternatives.

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

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

The description implies usage context through 'latest' and sorting by publication date, suggesting this tool is for retrieving recent speeches. However, it doesn't explicitly state when to use this vs. siblings like get_speeches_by_speaker or search_speeches, nor does it mention exclusions or prerequisites.

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 that the tool returns 'full speech content and metadata', which adds useful context beyond the input schema. However, it lacks details on error handling, rate limits, or authentication needs, leaving behavioral gaps.

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

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

The description is two concise sentences with zero waste: the first states the purpose, and the second specifies the return value. It is front-loaded and appropriately sized for a simple 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 tool's low complexity (1 parameter, no output schema, no annotations), the description is mostly complete. It covers purpose and return value, but lacks error handling or behavioral details, which would be beneficial for full completeness.

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

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

Schema description coverage is 100%, so the schema already documents the doc_id parameter fully. The description adds no additional parameter details beyond what the schema provides, such as format examples or constraints, meeting the baseline for 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 clearly states the specific action ('Get') and resource ('a specific Federal Reserve speech by its document ID'), distinguishing it from siblings like get_latest_speeches or get_speeches_by_speaker. It specifies retrieving a single speech via ID rather than lists or filtered searches.

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 you have a specific document ID, contrasting with siblings that handle bulk retrieval or filtering. However, it does not explicitly state when not to use this tool or name alternatives, leaving some ambiguity about overlapping use cases.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions filtering by name, role, and date range but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (e.g., list of speeches with details). This is a significant gap for a tool with multiple parameters and no output 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, efficient sentence that front-loads the core purpose and lists key filters without unnecessary words. Every part earns its place, making it highly 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 complexity (4 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain behavioral traits like safety or performance, and without an output schema, it fails to describe what the tool returns (e.g., speech titles, dates, content). This leaves gaps for an agent to use it 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 schema description coverage is 100%, so the input schema already documents all parameters thoroughly (e.g., 'name' as partial match, 'role' with enum values, date formats). The description adds minimal value by listing the filter types but doesn't provide additional semantics beyond what's in the schema, meeting the baseline for high coverage.

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

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

The description clearly states the verb 'Get' and resource 'Federal Reserve speeches' with the specific constraint 'by a specific speaker', making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'get_speeches_by_type' or 'search_speeches', which might offer overlapping functionality, so it doesn't reach the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get_speeches_by_type' or 'search_speeches'. It lists filtering capabilities but doesn't specify scenarios or exclusions, leaving the agent to 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?

With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether this is a read-only operation, how results are returned (e.g., pagination, format), rate limits, or error handling. The description is minimal and adds little 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?

The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple filtering tool and front-loaded with the key information.

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

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

Given no annotations and no output schema, the description is incomplete for a tool with three parameters. It doesn't explain return values, error cases, or behavioral constraints, leaving significant gaps for the agent to operate effectively in a real-world 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%, so the schema fully documents all three parameters. The description mentions 'by document type' which aligns with the 'doc_type' parameter but doesn't add meaning beyond what the schema provides (e.g., explaining the enum values or date formats). Baseline 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the action ('Get') and resource ('Federal Reserve speeches') with specific filtering criteria ('by document type'). It distinguishes from siblings like 'get_latest_speeches' (no type filter) and 'get_speeches_by_speaker' (different filter), but doesn't explicitly contrast them, keeping it at 4 rather than 5.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'search_speeches' or 'get_speeches_by_speaker'. It mentions the filter criteria but doesn't specify use cases or exclusions, leaving the agent to 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe what statistics are returned, whether there are rate limits, authentication requirements, or what format the statistics come in. For a statistics tool with zero annotation coverage, this is inadequate.

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

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

The description is a single, efficient sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information.

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

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

For a statistics retrieval tool with no annotations and no output schema, the description is insufficient. It doesn't explain what statistics are returned (counts, averages, distributions?), the format of the response, or any limitations. The agent would be left guessing about the tool's behavior and output.

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 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't mention parameters since none exist, earning a baseline 4 for not creating confusion about non-existent 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 action ('Get statistics') and resource ('stored Federal Reserve speeches'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_speech' or 'get_latest_speeches' which retrieve speech content rather than statistics.

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 like 'search_speeches' or 'get_speeches_by_speaker'. The description implies this returns aggregated statistics rather than individual speeches, but doesn't explicitly state this distinction or provide usage context.

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

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

With no annotations provided, the description carries full burden but lacks critical behavioral details. It mentions that scanning index pages is 'slower but more thorough', which is useful, but doesn't disclose potential side effects (e.g., network calls, rate limits), authentication needs, or what 'fetch new' entails (e.g., updates a database). This leaves significant gaps for a tool that interacts with external sources.

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

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

The description is highly concise with two sentences that directly address the tool's function and optional behavior. Every word contributes meaning without redundancy, making it easy to parse quickly.

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

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

Given no annotations and no output schema, the description is incomplete for a tool that fetches from external sources. It doesn't explain what 'fetch new' means operationally (e.g., stores data, returns results), potential errors, or how results are handled, leaving the agent with insufficient context for reliable use.

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

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

Schema description coverage is 100%, so the schema fully documents both parameters. The description adds minimal value by mentioning 'RSS feeds and optionally index pages', which loosely relates to parameters but doesn't provide additional syntax or format details beyond what the schema already specifies.

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 ('Fetch new speeches') and resource ('from the Federal Reserve website'), specifying it checks RSS feeds and optionally index pages. It distinguishes from siblings like 'get_latest_speeches' by focusing on fetching new content rather than retrieving existing data, though it could be more explicit about this distinction.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get_latest_speeches' or 'search_speeches'. It mentions optional index page scanning but doesn't explain scenarios where this is preferable, leaving usage context unclear.

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 the search scope ('title and content') but lacks details on permissions, rate limits, pagination, error handling, or response format. For a search tool with zero annotation coverage, this is a significant gap in transparency about how the tool behaves beyond basic functionality.

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 highly concise and front-loaded with two sentences that directly state the tool's purpose and search scope. Every sentence earns its place without redundancy, making it efficient and easy for an agent to parse quickly.

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

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

Given the lack of annotations and output schema, the description is incomplete for a search tool. It doesn't explain return values, result ordering, or potential limitations (e.g., partial matches, case sensitivity). With 2 parameters and no structured output guidance, more context is needed for the agent to use this tool effectively.

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

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

Schema description coverage is 100%, with clear descriptions for both parameters ('query' and 'limit'). The description adds minimal value beyond the schema, only implying that the query searches 'title and content,' which doesn't provide additional syntax or format details. Baseline 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Search Federal Reserve speeches by keyword. Searches in title and content.' It specifies the verb ('Search'), resource ('Federal Reserve speeches'), and scope ('by keyword' with search fields). However, it doesn't explicitly differentiate from siblings like 'get_latest_speeches' or 'get_speeches_by_speaker' beyond the search functionality.

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

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

The description implies usage context through 'Search by keyword' and 'Searches in title and content,' suggesting this tool is for keyword-based searches rather than retrieval by other attributes. However, it doesn't explicitly state when to use this vs. alternatives like 'get_speeches_by_speaker' or provide any exclusions or prerequisites, leaving some ambiguity for the agent.

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