CalvingWatch Public Knowledge

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds behavioral context by stating the tool accesses 'public' information and returns a 'no-credentials website boundary', clarifying access restrictions and output scope beyond 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 a single, concise sentence that communicates the tool's function without extraneous words, earning its place 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?

With no output schema and no parameters, the description provides adequate context about return values (requirements and boundary). Could be slightly more detailed about the structure of the requirements, but sufficient for the tool's simplicity.

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?

No parameters exist, and schema coverage is 100%. The description adds meaning beyond the schema by specifying the nature of the returned data (camera-view requirements and boundary), justifying a baseline 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 public camera-view requirements and the no-credentials website boundary, making its purpose specific and distinguishable from sibling tools like get_market_route or get_public_summary.

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 when to prefer search_public_knowledge. No when-to-use or when-not-to-use criteria are included.

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 indicate read-only, idempotent, non-destructive behavior. The description adds value by specifying it returns public page and tester-interest status and explicitly states it does not decide farm eligibility, consistent with 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?

Single sentence with no wasted words. It is front-loaded with the core action and clearly 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 single parameter with enum and rich annotations, the description covers the basics but does not describe the response format or what exactly a 'market route' entails. Without an output schema, more detail would be helpful for 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 0%, so the description should compensate. It only mentions 'supported country' without elaborating on the country parameter or its effects. The enum values in the schema provide some clarity but the description adds no extra meaning.

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 clearly states it retrieves public page and tester-interest status for a supported country, and distinguishes it by noting it does not decide farm eligibility. However, it does not explicitly differentiate from sibling tools like get_public_summary.

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?

Implicit usage is clear from the purpose, but there is no explicit guidance on when to use this tool versus alternatives. The negative constraint (does not decide farm eligibility) provides some context but not enough for a higher 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to repeat these. It adds 'current' implying a snapshot, but no further behavioral details (e.g., caching, authorization, rate limits) are provided. The description adds minimal value beyond 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 a single sentence of 15 words, front-loaded with the action 'Get current', and every word contributes meaning. No waste 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 no parameters, no output schema, and annotations present, the description lists the content categories (product, publisher, pre-pilot status, first tester-offer facts), which is helpful. However, the lack of output schema means the agent does not know the exact structure or field names, but for a simple public summary this is likely sufficient. A 5 would require more detail on the format.

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?

There are no parameters, and schema description coverage is 100% by default. With 0 parameters, the baseline is 4, and the description does not need to add parameter-level information.

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 current public product, publisher, pre-pilot status, and first tester-offer facts. It uses a specific verb and resource, and it distinguishes from siblings which focus on other domains (camera requirements, market route, safety limits, public knowledge). However, the phrasing 'first tester-offer facts' is slightly vague, preventing 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?

No guidance is provided on when to use this tool versus alternatives like search_public_knowledge. The agent is left to infer based on the description alone. Explicit when-to-use or when-not-to-use conditions are 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which cover safety and idempotency. The description merely restates the read nature with 'Get' and adds no additional behavioral traits such as authentication requirements, rate limits, or data volatility. Thus, it provides no extra value 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 a single sentence of 10 words, succinctly listing the three output categories. It is front-loaded with the verb and immediately conveys the tool's purpose. Every word serves a clear function, with no 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 no output schema, so the description partially explains return values by listing three content types. However, it does not specify the format (e.g., structured document, plain text) or whether additional details are available. Given the simplicity (0 parameters, no nested objects), this is mostly adequate but leaves a minor gap in 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?

The tool has zero parameters, and the input schema is empty with 100% coverage. Per the guidelines, baseline score for 0 parameters is 4. The description does not need to elaborate on 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 three specific categories of safety-related information: monitoring limitations, urgent animal-welfare guidance, and prohibited claims. The verb 'Get' aligns with the tool name, and the resource 'safety limits' is expanded. This specificity distinguishes it from siblings like get_camera_requirements or get_market_route.

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 guidance on when to use this tool versus alternatives is provided. The description implies use for safety-related queries, but does not mention exclusions or criteria for when other tools (e.g., search_public_knowledge) might be more appropriate. The context is clear but lacks directive support.

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 read-only, idempotent, non-destructive. Description adds that it returns JSON paths, which is behavioral. However, no details on empty results, performance, or scope of search.

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, 14 words, front-loaded with key action. 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 one-parameter tool with rich annotations, the description covers the core purpose and output. Could include edge cases (no matches) or scope, but 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?

Schema coverage is 0%, so description must compensate. It mentions 'search string values', implying query is the search string, but no explanation of constraints (minLength, maxLength) or what inputs are valid. Minimal added value beyond 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?

Description clearly states verb 'search', resource 'reviewed public knowledge record', and output 'matching JSON paths'. It distinguishes from sibling tools (e.g., 'get_public_summary') which retrieve specific items rather than search.

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?

Purpose implies use when searching for string values in public knowledge, but no explicit when-not or alternative suggestions. No mention of how this differs from sibling tools beyond the verb.

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