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

No annotations are provided, so the description carries the full burden. 'Add two numbers' accurately describes a pure, stateless, non-destructive operation. For such a simple arithmetic tool, this is sufficient transparency, though it could explicitly state that it has no side effects.

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 conveys the essential action without any unnecessary words. It is highly concise and structured effectively.

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 extreme simplicity (add two numbers), the description is largely complete. It could mention the return value (the sum), but that is easily inferred. The lack of output schema does not significantly degrade completeness here.

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% – the description does not explain the two parameters 'a' and 'b' or their roles beyond what the schema already provides. With no additional meaning added, this dimension is severely lacking.

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 'Add two numbers', specifying the verb 'add' and the resource 'two numbers'. This distinguishes it from sibling tools like sub, mul, div, mod, and sqrt, which perform different operations.

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. For example, it does not explain when addition is preferred over subtraction or multiplication. The usage context is entirely implied.

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 it retrieves a list but doesn't specify if it's read-only, safe, paginated, or has any side effects. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that directly states the tool's function without any fluff. 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 tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. However, it lacks details on behavioral aspects like safety or output format, which would be helpful for an agent to use it correctly, especially without annotations.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is fine here, but it could hint at any implicit constraints (e.g., sorting or limits), though not required. Baseline is high due to no 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 verb ('Get') and resource ('list of all available habitats'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'getMonsterByHabitat' or 'getMonsters', which also retrieve data but with different scopes or filters, so it lacks 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. It doesn't mention scenarios where this tool is preferred over siblings like 'getMonsterByHabitat' (which filters by habitat) or 'getMonsters' (which retrieves monsters instead of habitats), leaving the agent without 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the 'exact match only' constraint, which is useful behavioral context beyond basic functionality. However, it lacks details on error handling, rate limits, authentication needs, or what the return format looks like (e.g., list of monsters with specific fields).

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: two sentences that efficiently convey purpose and usage guidelines without wasted words. The first sentence states the core functionality, and the second provides critical procedural advice, both earning their 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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is fairly complete. It covers purpose, usage guidelines, and a key behavioral constraint ('exact match only'). However, without annotations or an output schema, it could benefit from more details on return values or error cases, but it's adequate for basic 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 already documents both parameters ('habitat' and 'limit') with descriptions. The description repeats the guidance about calling 'getHabitats' for the 'habitat' parameter but doesn't add new semantic meaning beyond what the schema provides. 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 monsters by habitat (exact match only).' It specifies the verb ('Get'), resource ('monsters'), and constraint ('by habitat, exact match only'). However, it doesn't explicitly differentiate from siblings like 'getMonsters' (which might fetch all monsters) or 'getMonsterByName' (which filters by name rather than habitat).

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 usage guidance: 'for best results, first call getHabitats to get a list of available habitats, then find the most appropriate one to use with this tool.' This tells the agent when to use this tool (after retrieving habitat list) and references a sibling tool ('getHabitats') as a prerequisite, offering clear alternatives and 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information' but doesn't specify what that includes (e.g., stats, abilities, weaknesses), whether it's a read-only operation, error handling for invalid IDs, or performance characteristics like rate limits. This leaves significant gaps for agent understanding.

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 unnecessary words. It is front-loaded with the core 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 lookup tool with one parameter and no output schema, the description is minimally adequate. However, it lacks details on the returned data structure (e.g., what 'detailed information' entails) and behavioral aspects like error cases, which would help an agent use it correctly. The absence of annotations exacerbates these gaps.

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

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

The schema description coverage is 100%, with the parameter 'monsterId' clearly documented as 'ID of the monster to retrieve'. The description adds no additional semantic context beyond what the schema provides, such as format examples or valid ranges. Given the high schema coverage, 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 clearly states the verb ('Get detailed information') and resource ('about a specific monster by ID'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'getMonsterByName' or 'getMonsterByHabitat', which also retrieve monster information but use different identifiers.

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 sibling tools like 'getMonsterByName' (for name-based lookup) or 'getMonsterByHabitat' (for habitat-based filtering), nor does it specify prerequisites such as needing a valid monster ID.

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 key behavioral traits: partial matching and a limit of 5 results, which are valuable beyond basic 'get' functionality. However, it lacks details on error handling, authentication needs, or rate limits, leaving gaps for a tool with no annotation coverage.

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

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

The description is extremely concise and front-loaded: a single sentence that efficiently conveys the core functionality and key constraints. Every word earns its place, with no wasted text 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 tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally complete. It covers the basic operation and behavioral constraints but lacks details on output format or error cases. For a simple lookup tool, this is adequate but leaves room for improvement in contextual richness.

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 'name' parameter as 'Name of the monster to search for (can be partial).' The description adds no additional meaning beyond this, merely restating 'partial match.' Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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 monsters by name' specifies the verb (get) and resource (monsters). It distinguishes from siblings like getMonsterById and getMonsters by focusing on name-based retrieval. However, it doesn't explicitly differentiate from getMonsterByHabitat, which is a similar lookup but by different criteria.

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 'partial match, returns up to 5 matches,' suggesting it's for fuzzy name searches with result limits. However, it doesn't explicitly state when to use this versus alternatives like getMonsterById (exact ID match) or getMonsters (full list). No guidance on prerequisites or exclusions is provided.

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 filtering, sorting, and pagination but doesn't describe important traits like whether this is a read-only operation, what happens with invalid filters, rate limits, authentication requirements, or the format of returned results. For a list retrieval tool with zero annotation coverage, this leaves significant 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, efficient sentence that front-loads the core purpose ('Get a list of monsters') and then succinctly lists the key capabilities. Every word earns its place with no redundancy or unnecessary elaboration.

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

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

Given no annotations and no output schema, the description is incomplete for a tool with four parameters and nested objects. It doesn't explain what the returned list looks like, how errors are handled, or important behavioral aspects like default values or constraints. For a list retrieval tool with filtering capabilities, more context is needed to be fully helpful.

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 all four parameters thoroughly. The description adds minimal value by mentioning 'optional filtering, sorting, and pagination' which aligns with the schema but doesn't provide additional semantic context beyond what's already in the parameter descriptions. This meets 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 verb ('Get') and resource ('list of monsters'), making the purpose immediately understandable. It distinguishes itself from siblings like getMonsterById or getMonsterByName by indicating it returns a list rather than a single entity. However, it doesn't explicitly differentiate from getMonsterByHabitat which also involves 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?

The description implies usage through 'optional filtering, sorting, and pagination', suggesting this tool is for general queries rather than specific lookups. However, it doesn't explicitly state when to use this versus alternatives like getMonsterByHabitat or getMonsterById, nor does it provide any exclusions or prerequisites for usage.

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