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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but fails to mention critical details such as whether it's read-only, if it has rate limits, authentication requirements, or what the output format looks like (e.g., list of news items with fields). This leaves significant gaps for an agent to understand the tool's 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 a single, efficient sentence that directly states the tool's purpose without any unnecessary words or fluff. It is appropriately sized and front-loaded, making it easy to parse quickly.

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

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

Given the complexity of a news retrieval tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., news items structure), potential errors, or behavioral traits like pagination or sorting. This leaves the agent with insufficient context for effective use.

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

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

The input schema has 100% description coverage, clearly documenting both parameters (limit and category) with details like max value and enum options. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline for adequate but not enhanced 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 verb 'Get' and the resource 'all news from FantasyPros', making the purpose understandable. However, it doesn't differentiate from the sibling tool 'get_sport_news', which likely serves a similar purpose with different scope or filtering.

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 like 'get_sport_news' or other siblings. The description lacks context about use cases, prerequisites, or exclusions, leaving the agent with minimal 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets' information, implying a read operation, but doesn't cover aspects like permissions, rate limits, response format, or whether it's safe/destructive. This leaves significant gaps for a tool with 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, efficient sentence with zero waste, clearly front-loading the purpose. It's appropriately sized for a simple tool, 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 with parameters. It lacks behavioral context, usage guidance, and details on return values, making it inadequate for full agent understanding despite the clear 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 description coverage is 100%, so the schema already documents both parameters fully. The description adds no additional meaning beyond implying 'sport' is required and 'playerId' is optional for filtering, which is already clear from the schema. 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 verb 'Get' and resource 'player information' with scope 'for a specific sport', making the purpose understandable. However, it doesn't differentiate from potential sibling tools like 'get_rankings' or 'get_projections' that might also involve player data, missing full sibling 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_rankings' or 'get_projections', nor does it mention prerequisites or exclusions. It only implies usage by stating the purpose without 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 the full burden of behavioral disclosure but only states the action without details on permissions, rate limits, data freshness, or response format. It doesn't explain if this is a read-only operation, how projections are generated, or any constraints beyond the input parameters, leaving significant gaps in 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, efficient sentence with zero waste, front-loaded with the core action. It's appropriately sized for a simple tool, avoiding unnecessary elaboration while clearly stating the purpose in a concise manner.

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 output schema, no annotations), the description is incomplete. It doesn't cover behavioral aspects like data sources, update frequency, or error handling, and with no output schema, it fails to explain return values. This leaves the agent with insufficient context for effective use.

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

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

The description adds no meaning beyond the input schema, which has 100% coverage with clear descriptions for all 4 parameters (e.g., sport with enum, season, week, position). Since the schema fully documents the parameters, the baseline score is 3, as the description doesn't compensate or provide additional semantic context.

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

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

The description states the basic purpose ('Get player projections for a sport') with a clear verb and resource, but it's vague about what 'projections' entail (e.g., statistical forecasts, fantasy points) and doesn't distinguish it from sibling tools like get_players or get_rankings, which might overlap in scope. It provides minimal differentiation beyond the tool name.

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

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

The description offers no guidance on when to use this tool versus alternatives like get_players or get_rankings, nor does it specify prerequisites or context for usage. It lacks explicit when/when-not instructions or named alternatives, leaving the agent to infer usage based on the tool 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 the full burden of behavioral disclosure. It states what the tool does but doesn't cover critical aspects like whether it's a read-only operation, requires authentication, has rate limits, or what the return format looks like. This leaves significant gaps for a tool that fetches data.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'consensus rankings' entail, how results are structured, or any behavioral traits like data freshness or limitations. For a data-fetching tool with 3 parameters, this leaves too much unspecified.

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 parameters are well-documented in the schema. The description doesn't add any extra meaning beyond the schema, such as explaining how 'consensus rankings' are derived or the significance of 'scoring' types. 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 verb ('Get') and resource ('consensus rankings for a sport'), making the purpose understandable. However, it doesn't differentiate this tool from sibling tools like 'get_players' or 'get_projections' that might also relate to sports data, missing specific 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?

No guidance is provided on when to use this tool versus alternatives like 'get_players' or 'get_projections'. The description lacks context on use cases, prerequisites, or exclusions, leaving the agent to infer usage based on tool names alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get news' but does not clarify aspects such as data freshness, rate limits, authentication needs, or potential side effects. For a read operation without annotations, this leaves significant behavioral traits undocumented.

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: 'Get news for a specific sport.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity, 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 no annotations and no output schema, the description is incomplete. It does not explain return values, error handling, or behavioral constraints. For a tool with three parameters and read-only nature implied by 'Get', more context is needed to fully guide an AI agent, such as what the news output looks like or any limitations.

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 all parameters well-documented in the schema (e.g., 'sport' with enum values, 'limit' with min/max, 'category' with enum). The description adds no additional meaning beyond the schema, such as explaining parameter interactions or usage nuances, so it meets the baseline for high schema coverage without enhancement.

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 'Get news for a specific sport' clearly states the verb ('Get') and resource ('news for a specific sport'), making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'get_all_news' (which might fetch news across all sports), leaving room for ambiguity in sibling 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_all_news' or other siblings. It lacks explicit instructions on context, prerequisites, or exclusions, offering only a basic statement of function without comparative or situational advice.

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