contractor-quote-check

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 safety profile is covered. The description adds useful behavioral context by specifying that the review targets 'missing or unclear sections' and works on a single quote, which clarifies the scope of analysis 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, front-loaded sentence that immediately states the use case. Every word contributes meaning, 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?

Given the tool's simplicity (one parameter, output schema present) and the description's clear explanation of what it does and when to use it, the description is complete for an agent to correctly select and invoke the tool. No additional context is needed.

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, 'text', with 100% coverage and a clear description ('Contractor quote or estimate text'). The tool description does not add further parameter information, so the baseline score 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 the tool's function: 'structured review of one contractor quote for missing or unclear sections.' It specifies the verb ('review'), the resource ('contractor quote'), and the scope ('one'), distinguishing it from sibling tools like compare_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 begins with 'Use this when a user wants...' which provides an explicit trigger condition. However, it does not mention when not to use the tool or alternative tools for scenarios like comparing multiple quotes, so it lacks the full exclusions/alternatives for 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent understands this is a safe, read-only operation. The description adds the specific automation-opportunity focus but does not disclose any additional behavior (e.g., how the input is processed or what the output contains), though the output schema exists to cover return values.

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: 'Use this when a user wants a workflow reviewed for AI/MCP automation opportunities.' It contains no filler, works in the trigger condition, and is immediately actionable.

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 low-complexity tool with one optional parameter, robust safety annotations, and an output schema, the description adequately covers when to use it and what it does. It could briefly note that the workflow is supplied via the 'text' parameter, but the overall package is sufficient for an agent to 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 one optional 'text' parameter with zero description coverage. The description mentions 'workflow' but never explicitly maps it to the 'text' parameter, leaving the connection implicit. Since the description carries the burden of explaining parameters in this low-coverage situation, it fails to compensate.

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 ('reviewed') and resource ('workflow'), with a focused purpose of identifying AI/MCP automation opportunities. It distinguishes this tool from siblings like audit_quote and the various build_* checklists, which target different objects or outcomes.

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 explicitly says 'Use this when a user wants a workflow reviewed for AI/MCP automation opportunities,' giving a clear trigger condition. It does not mention alternatives or exclusions, but no sibling tool competes for this exact task, so the context is sufficient.

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 destructiveHint=false, so the safety profile is clear. The description adds no behavioral details beyond the purpose, but nothing contradicts the annotations. With annotations doing the heavy lifting, a baseline 3 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?

A single, front-loaded sentence that contains no fluff. It tells the user exactly when to invoke the tool, making it highly efficient.

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 two-parameter tool with a full output schema and strong annotations, the description covers the primary use case. However, the optional 'org' parameter is not explained, and the tool's output format is left entirely to the schema, which is acceptable but slightly incomplete.

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%, and the description only implies that 'text' contains grant requirements. The 'org' parameter is left undefined, and no format or usage details are provided. The description fails to compensate for the lack of parameter documentation.

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 and resource: build an application checklist from grant requirements. It distinguishes from sibling checklist tools like build_firegrant_checklist or generate_permit_checklist by specifying 'application checklist' and 'grant requirements'.

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 an explicit trigger: 'Use this when a user wants an application checklist from grant requirements.' It does not mention alternatives or when-not-to-use, but the condition is specific enough to guide selection.

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, covering the safety profile. The description adds no additional behavioral context beyond usage guidance, which is acceptable given the strong annotations, but there is no extra transparency value.

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 usage guidance. There is zero wasted 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?

This is a simple tool with one fully documented parameter, a strong annotation set, and an output schema. The description fully covers when to use it. Given the low complexity, no further context is needed.

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 covers 100% of the parameter (text: RFP or solicitation text). The description does not add any further parameter details, so it relies on the schema, which is sufficient.

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 identifies the tool's purpose: building an RFP requirement/compliance matrix. The verb is implied by the title, and the resource is specific. It doesn't explicitly distinguish from sibling tools like build_application_checklist, but the scope is clear enough.

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 starts with 'Use this when...' which provides explicit guidance on when to use the tool. It gives clear context (user wants an RFP compliance matrix) but doesn't mention exclusions or alternative 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds no behavioral context beyond the use case, such as what the checklist includes or any constraints. This does not contradict annotations, but also adds little value beyond 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 a single, front-loaded sentence that immediately conveys the use case. There is zero wasted verbiage, making it highly concise and 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 tool has an output schema and annotations that cover return structure and side-effect safety, so the description need not repeat those. However, it is minimal and leaves gaps around parameter meanings and how to phrase a request, which reduces completeness for an agent without further 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 0%, and the description does not explain the two parameters ('text' and 'org'). The required 'text' parameter's role is only inferable from the tool name and description. This is insufficient for an agent to know what input to provide, especially since 'org' is optional and undocumented.

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: to produce a fire-grant application preparation checklist. It uses a specific resource ('fire-grant application preparation checklist') and implies the 'build' action. However, it does not explicitly distinguish itself from sibling tools like build_application_checklist or build_fire_purchase_checklist, leaving some ambiguity.

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 an explicit 'Use this when...' condition, which clearly indicates the intended scenario. It does not mention when not to use it or offer alternatives, but the condition is specific enough for basic selection among siblings.

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 covers the safety profile. However, the description adds no behavioral context beyond the purpose—it does not describe what the tool produces, any input formatting requirements, or the nature of the output. With annotations present, the bar is lower, but the description still provides almost no extra transparency beyond what annotations already convey.

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 directly states the usage condition. It is front-loaded with the action and contains zero filler. Perfect conciseness for a straightforward 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?

While the tool is simple (one parameter, output schema present), the description fails to explain what the 'text' parameter should contain, making the tool incomplete from a usability standpoint. The output schema exists but is not referenced or summarized, and the description does not connect the input to the resulting checklist. Despite the annotations providing safety context, the lack of parameter semantics leaves a significant 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?

Schema description coverage is 0%, and the description does not mention the single 'text' parameter at all. The schema only specifies 'type: string', leaving the agent without any clue about what content should be passed in. This is a critical gap, especially since the tool has only one parameter and it is 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 clearly states the tool's function: to provide a purchasing checklist for fire/public-safety equipment. This distinguishes it from sibling checklist builders like build_application_checklist or build_firegrant_checklist, which target different domains. The verb 'build' is implied through context, making the purpose specific 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 explicitly frames usage with 'Use this when a user wants a purchasing checklist for fire/public-safety equipment,' giving a clear trigger condition. It does not mention when not to use it or name alternatives, but the focused scope makes the context sufficient. A brief exclusion note would push this to 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description adds no behavioral details about how the tool operates, what it returns, or any limitations. It only restates the usage intent, so it contributes little 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?

A single sentence, front-loaded with the usage scenario, no filler words. Extremely concise and to the point.

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 many sibling tools and zero parameter descriptions, the description provides only a minimal purpose statement. It lacks essential context about parameter roles and how this tool differs from similar question-generating tools, making it insufficient for reliable 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 0% and the description gives no hints about 'lane' or 'text'. With two ambiguous string parameters, the agent has no way to infer their meaning from the description, which fails to compensate for the missing schema details.

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 a specific purpose: generating questions to verify inspection requirements. It is clear about the resource and action, but it does not differentiate from sibling tools like generate_vendor_questions or build_compliance_matrix, which may also produce questions.

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?

Provides a clear usage context ('Use this when a user wants questions to verify inspection requirements'), but no explicit exclusions or alternative tool names. The context is clear enough, but lacks '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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety and mutation profile. The description adds only a usage directive, not additional behavioral context such as output structure or how the 'text' parameter is processed. This is acceptable given annotation coverage but provides no extra 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 a single sentence, front-loaded, and directly conveys the tool's use case without any filler. 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 a clear purpose, usage condition, and existing annotations/output schema, the core context is present. However, the unexplained 'text' parameter is a notable gap, preventing the description from being fully self-sufficient for an 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?

The input schema has a single optional 'text' string with no description, and schema description coverage is 0%. The description does not compensate by explaining what 'text' should contain or how it affects the checklist, leaving the parameter semantically empty.

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 builds an implementation checklist for AI/MCP integrations, using a specific verb ('wants' implies 'build') and distinct resource. It distinguishes from sibling tools like build_application_checklist and build_compliance_matrix by specifying the integration context.

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 says to use this tool when a user requests an implementation checklist for an AI/MCP integration, giving a clear when-to-use condition. However, it does not mention when not to use it or explicitly name alternative tools for other checklist types.

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. The description adds no behavioral details beyond the purpose itself, such as how the questions are generated or what constitutes a bid. With annotations present, the description fails to add any extra context, so a score of 2 reflects this lack of added value.

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. Every word is necessary and it directly states the purpose, 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?

With only a one-sentence description and no parameter explanations, the tool is not adequately specified for correct invocation, especially given the 0% schema coverage. Although an output schema exists, the lack of input semantics leaves a significant knowledge gap. The tool is simple (2 params) but the description does not cover essential 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 schema has 0% description coverage, and the tool description does not explain the meaning of the required 'text' parameter or the optional 'vendor' parameter. The agent is left without any guidance on what content to provide, making this a severe gap.

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 builds 'vendor clarification questions from a bid', which is a specific verb and resource. It distinguishes from most siblings by scope, but there is a similar sibling 'generate_vendor_questions' with no explicit differentiation, so it loses the fifth point.

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 begins with 'Use this when', providing a clear context for when to invoke the tool. It does not mention alternatives or exclusions, but the situation 'user wants vendor clarification questions from a bid' is well-specified.

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 destructiveHint=false, covering the safety profile. The description adds context about the comparison scope and presentation, but does not detail output structure or input requirements. This is adequate given annotations, but not rich.

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. It is front-loaded and easy to parse, covering the core action and scope 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?

Annotations and output schema cover safety and return values, but the lack of parameter explanations and the absence of alternative guidance leave some gaps. However, for a simple comparison tool, the core purpose is adequately clear.

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 compensate. It does not explain the format of quote_a, quote_b, or quote_c, nor what values they take. The parameter names are somewhat self-explanatory, but no additional semantics are provided.

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 'compare' with a clear resource 'contractor quotes' and specifies the scope as 'two or three side by side'. This clearly distinguishes it from sibling tools like audit_quote and extract_quote_amounts, which have different actions.

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 an explicit trigger condition ('when a user wants to compare two or three contractor quotes side by side'), which is clear usage context. However, it does not mention exclusions or alternatives, so it falls short of a full 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety. The description adds minimal behavioral context about the output (amounts and flags), but does not disclose any edge cases or limitations. With strong annotations, this is adequate but not enriched.

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, front-loaded sentence with no wasted words. It immediately states the trigger condition and the expected result, making it highly efficient.

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 an output schema and annotations, the description fails to clarify the input parameter or any preconditions, leaving the tool under-specified for an agent. The description is too sparse given the ambiguity of 'text'.

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 single parameter 'text' has no schema description (0% coverage) and the description does not explain its purpose or format. Since coverage is low and there is no compensation, the parameter semantics are 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 the tool provides public-safety RFQ quote amounts and comparison flags, distinguishing it from the broader sibling compare_quotes. However, it lacks a direct action verb (e.g., 'retrieve' or 'compare'), making the purpose slightly implicit.

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?

Explicitly begins with 'Use this when a user wants...', providing clear usage context. It does not mention alternatives or exclusions, but the 'when' framing is sufficiently directive for an AI agent.

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 declare readOnlyHint, idempotentHint, and destructiveHint false, which cover safety. The description adds no additional behavioral context, but does not contradict 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?

Single sentence, front-loaded with usage guidance. 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?

The description covers purpose and usage context but lacks parameter guidance. Output schema exists, so return values are covered. The missing parameter semantics are the main 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?

Schema has no descriptions and coverage is 0%. The description does not explain the 'request' or 'supplier' parameters, leaving ambiguity about what to pass.

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: generating a checklist for listing inventory. It uses a specific verb ('use') and resource ('listing inventory'), distinguishing it from sibling checklist tools like build_application_checklist.

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 clear 'when to use' condition ('when a user wants a checklist of information required before listing inventory'), but it doesn't mention alternatives or exclusions, 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds one behavioral clue: the plan is derived from permit dependencies, which indicates the source of the output. However, it doesn't describe what the plan includes, how dependencies are processed, or any limitations.

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 words. It efficiently states the purpose, though it sacrifices informativeness for brevity.

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 two obscure parameters and a vague description, the tool lacks enough context for an agent to invoke it correctly. The output schema exists, but the input semantics are unresolved. Sibling tools are numerous, and without further detail, an agent might confuse this with other plan generators.

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 lists 'lane' and 'text' with no descriptions, and schema coverage is 0%. The description only hints that permit dependencies are involved, possibly referring to the 'text' parameter, but 'lane' remains entirely unexplained. This is insufficient for an agent to map user input to 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 that the tool is used when a user wants a project-opening plan, and it specifies the input source ('permit dependencies'), which differentiates it from other plan-generating tools. However, it relies on an implicit verb rather than explicitly saying 'creates' or 'generates', and it doesn't name alternative tools.

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 explicitly frames when to use the tool ('Use this when...'), providing clear context. It doesn't mention alternatives or exclusions, but the qualifier 'from permit dependencies' narrows the use case sufficiently.

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 safety profile is covered. The description adds that it works 'from a compliance calendar' but doesn't disclose additional behavioral traits like prerequisites or generation mechanics, which is acceptable given the 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?

A single, clear sentence with no superfluous content. It is front-loaded with the action and resource, making it 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?

For a simple one-parameter tool with rich annotations and an output schema, the description covers the core use case. It could be slightly more explicit about what a 'reminder-plan outline' entails, but the output schema likely fills that 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 schema fully describes the single parameter 'vertical' as a 'Compliance calendar vertical identifier' (100% coverage). The description's phrase 'from a compliance calendar' echoes this without adding new semantic detail, 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 the tool generates a 'reminder-plan outline' from a compliance calendar, giving a specific verb and resource. It distinguishes this from sibling tools by mentioning the compliance-calendar source, though it doesn't explicitly name an alternative.

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?

Provides an explicit trigger: 'Use this when a user wants a reminder-plan outline from a compliance calendar.' This gives clear direction on when to select this tool, even though it doesn't state when not to use it or list 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?

Annotations (readOnlyHint: true, idempotentHint: true) already disclose that the tool is safe and non-destructive. The description adds minimal behavioral context by framing the output as 'proposed' and scoping it to 'a workflow,' but it does not elaborate on return format, limitations, or side effects beyond what annotations provide.

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 consists of a single, concise sentence that directly conveys the intended use case. There is no redundant or extraneous information, making it well-structured and appropriately sized.

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 an output schema and annotations, the description is too sparse to fully support correct invocation. It lacks parameter semantics, fails to differentiate from similar sibling tools, and does not clarify what constitutes a 'proposed AI/MCP tool catalog' or how the input text should be used. The overall simplicity of the tool is not enough to compensate for these omissions.

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 one parameter, 'text', with no description and 0% schema description coverage. The tool description does not explain what 'text' should contain (e.g., the workflow description, user request, or tool list). This is a significant gap because the agent is left without any guidance on how to populate 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?

The description states 'Use this when a user wants a proposed AI/MCP tool catalog for a workflow,' which implies the tool produces a catalog but lacks an explicit action verb like 'creates' or 'generates.' It does not distinguish from sibling tools such as generate_mcp_package_plan or audit_workflow_for_ai, making the purpose somewhat vague.

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 explicitly provides a use case: 'when a user wants a proposed AI/MCP tool catalog for a workflow.' This gives clear context for when to invoke the tool, but it does not mention when not to use it or suggest alternative tools, so it stops 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds minimal behavioral context beyond noting the input is RFP requirements. It does not contradict 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, front-loaded sentence with no filler. It directly states the trigger condition and output, 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?

For a simple tool with one parameter, full schema coverage, rich annotations, and an output schema, the description is adequate. It explains when to use and what input is expected. It does not explain the return format, but the output schema presumably covers that. Minor gap: no mention of what the outline structure looks like.

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 fully describes the single 'text' parameter as 'RFP or solicitation text' (100% coverage). The description's 'RFP requirements' aligns with this but adds no new meaning. 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 indicates the tool produces a response outline derived from RFP requirements, which distinguishes it from sibling tools that generate questions, checklists, or compliance matrices. However, the verb is implicit ('wants a response outline') rather than explicitly stating 'draft' or 'generate', so it is clear but not maximally specific.

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 context for when to use the tool: when a user needs a response outline from RFP requirements. It does not mention alternatives or exclusions, but the context is clear enough to guide selection among the many sibling 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the dispatch context but discloses no additional behavioral traits (e.g., output format, dependencies, or side effects). This is acceptable given strong annotations, but the description contributes minimal behavioral insight.

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 with no redundancy. It front-loads the usage scenario and stays appropriately minimal 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 simplicity, strong annotations, and presence of an output schema, the description is minimally adequate. However, the unexplained 'text' parameter is a significant gap, and the description does not clarify what inputs drive the generated questions. The tool is usable in context but incomplete without parameter semantics.

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 a single required parameter 'text' with no description, and schema description coverage is 0%. The description does not explain what 'text' should contain (e.g., maintenance issue, tenant information, or user request). This leaves the agent guessing how to populate the parameter, making the tool difficult to invoke correctly.

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: generating questions to ask a tenant before maintenance dispatch. It distinguishes this tool from sibling tools like generate_vendor_questions or generate_contractor_questions by specifying the tenant context. Although it doesn't use an explicit verb like 'draft' or 'generate', the intent 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 explicitly provides a usage condition: 'Use this when a user wants questions to ask a tenant before maintenance dispatch.' This gives clear contextual guidance and implies it is for tenant-related inquiries, differentiating it from vendor or contractor question tools. It does not mention alternatives or exclusions, but the context is specific enough.

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 the safety profile. The description adds no new behavioral traits such as rate limits, authorization requirements, or expected output format. It essentially restates the purpose without going beyond what annotations already establish.

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, front-loaded with the usage trigger. It is not verbose and contains no filler, but it is so brief that it sacrifices necessary detail. Concise yet overly minimal.

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 a simple schema and annotations, plus an output schema (not shown), the description only covers when to use it. It doesn't explain what the tool actually returns, how the request and supplier inputs relate, or what kind of output the user should expect. Given the domain shown by sibling tools, this seems under-specified.

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% description coverage: neither 'request' nor 'supplier' is explained in the schema. The description does not mention or define these parameters, leaving their meaning entirely ambiguous. Since the description fails to compensate for the missing schema documentation, this is a critical gap.

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 indicates the tool is about obtaining the inputs required for assessing listing margin, which is a specific function. However, it is phrased as a usage condition ('Use this when...') rather than a direct statement of what the tool does, and it doesn't explicitly mention the action 'estimate' from the title, so it lacks full precision in distinguishing its exact role.

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 explicitly tells when to use the tool: when a user wants the inputs required for margin assessment. This provides clear context, but it doesn't mention any alternative sibling tools or when not to use this tool, so it falls short of a full usage guideline.

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, covering the safety profile. The description adds that the output is a checklist of 'likely needed' documents, implying a heuristic or informative result rather than a definitive legal listing, which is useful 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?

A single sentence, front-loaded with the usage condition, with no wasted words. It efficiently conveys purpose and context.

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 optional parameter, a rich output schema, and strong annotations, the description is sufficient. It conveys the primary use case and output type; the schema and annotations cover the remaining details. The only minor gap is not explaining how the optional 'vertical' parameter alters the checklist, but the schema's parameter description largely covers that.

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 single parameter 'vertical' is already fully described in the schema as a 'Compliance calendar vertical identifier.' The description doesn't reference this parameter, but with 100% schema coverage, the schema carries the burden. The description's phrase 'compliance lane' vaguely connects to 'vertical' but adds no additional semantic detail.

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 when to use the tool ('when a user wants a checklist of documents likely needed for a compliance lane'), aligning with the tool's name. It identifies the resource (required documents) and the context (compliance lane), but it doesn't explicitly contrast with sibling checklist-building tools such as build_application_checklist or generate_evidence_list.

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 an explicit usage condition ('Use this when...'), giving clear context for when to invoke it. It doesn't mention alternative tools or exclusion criteria, but for this single-purpose tool that's sufficient.

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 adds no behavioral information beyond what annotations already indicate (readOnly, idempotent, non-destructive). It does not disclose processing details, limitations, or any side effects. With annotations present, the bar is lower, but the description contributes zero additional context, so it fails to add value.

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 usage directive, and contains no unnecessary words. It is appropriately sized for a simple tool and each 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?

While the output schema and annotations provide some structure, the description omits crucial parameter explanations and lacks sufficient differentiation context. For a tool with only two parameters and no schema descriptions, the description should provide more guidance on what inputs mean and how they are used.

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%, and the description does not explain what 'text' or 'vendor' represent. Since the description fails to compensate for the lack of schema descriptions, there is no useful semantic guidance for the 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 extracts public-safety bid requirements, using the verb 'extract' and specifying the resource ('public-safety bid requirements'). This distinguishes it from sibling tools like extract_grant_requirements and extract_requirements, which target different resources.

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 clear usage condition: 'Use this when a user wants public-safety bid requirements extracted.' It implies that other types of requirements (e.g., grants) have different tools, but it does not explicitly name alternatives or exclusions. This meets the bar for clear context without explicit 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?

The description adds no behavioral context beyond what the annotations already state. It does not mention that the tool processes the required 'text' parameter, what the output looks like, or any edge cases. With readOnlyHint and idempotentHint already declared, the description contributes zero additional insight into 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 one sentence, so it is concise, but it is under-specified to the point of being tautological. It does not earn its few words because it adds no substantive information beyond the title. A description that merely restates the tool name is not appropriately sized; it is empty.

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 the tool has 2 parameters, a required text input, and many sibling tools, the description is far too sparse. It does not mention that input text is expected or what the extraction returns. Even though an output schema exists, the description fails to reference it or give any clue about the workflow, making the overall context incomplete.

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%, but the description does not compensate. It never explains the purpose of 'text' (the required parameter) or 'org' (the optional parameter). There is no mention of input format, intended content, or how the parameters affect output. For a 2-parameter tool at 0% schema coverage, this is a complete failure to add parameter 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?

The description 'Use this when a user wants fire-grant requirements extracted' essentially restates the tool's name and title. It lacks any explanation of what constitutes fire-grant requirements or how extraction is performed, and it does not distinguish this tool from siblings like extract_grant_requirements or extract_bid_requirements.

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 'Use this when...' is the only usage cue, but it merely mirrors the tool's function. No alternatives, exclusions, or contextual triggers are provided to help an agent choose between this and the many similarly named extraction/checklist tools in the 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?

Annotations already indicate readOnly, idempotent, and non-destructive behavior, so the description is not required to repeat those. The description adds only that it processes source text, without detailing the extraction process or any edge cases. It doesn't contradict the annotations, but provides minimal 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, well-structured sentence with no redundancy. It is easily readable but borders on under-specification, though that issue is more relevant to completeness than 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 existence of multiple extraction siblings and the optional 'org' parameter, the description is underspecified. It doesn't clarify when to choose this tool over firegrant or bid extraction, and doesn't mention the purpose of 'org'. The presence of an output schema and annotations mitigates some gaps, but the overall context is insufficient.

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% and the description provides no explanation for the 'text' or 'org' parameters. The parameter names are only partially self-explanatory; 'org' especially is ambiguous. The description fails to compensate for the lack of schema documentation.

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 extracts grant requirements from source text, using a specific verb and resource. However, it does not explicitly differentiate from sibling tools like extract_firegrant_requirements or extract_bid_requirements, though the name provides some 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 explicit usage context ('Use this when a user wants grant requirements extracted'), making the primary scenario clear. It lacks exclusions or alternative recommendations, so it stops short of full differentiation among extraction siblings.

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 readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds no additional behavioral context such as output granularity or edge cases; it simply restates the purpose, so it meets the baseline but doesn't go further.

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, grammatically functional, front-loaded with 'Use this when.' No filler 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?

With one parameter, full schema coverage, and an output schema present, the description is minimally sufficient. It could hint at return format or mention that it handles various quote formats, but for this simplicity, it's 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 covers the lone 'text' parameter fully with description 'Contractor quote or estimate text.' Description doesn't add new parameter semantics beyond what schema provides, so baseline 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 explicitly states the tool detects amounts from a contractor quote, with a clear 'Use this when' trigger and resource scope. It distinguishes from sibling extraction tools like extract_requirements by specifying 'quote amounts'.

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?

Provides a clear use case ('when a user wants amounts detected from a contractor quote') but does not mention alternatives or exclusions. It's clear enough for the agent to select among many extract tools, but lacks explicit 'use X instead' 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, establishing that this is a safe, non-mutating operation. The description adds no additional behavioral context, such as output format or edge cases; the presence of an output schema mitigates this gap.

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 efficiently conveys the tool's purpose. Every word earns its place, with no redundancy or unnecessary detail.

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 this simple—one parameter, strong annotations, and an output schema—the description provides sufficient context for an agent to select and invoke it correctly. There are no missing critical details that would hinder 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 schema fully documents the single 'text' parameter with 100% coverage. The description merely echoes the schema's 'RFP or solicitation text' without adding any new semantic detail, so it provides no extra value beyond the structured fields.

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 that the tool extracts requirements from an RFP or solicitation, using a specific verb and resource. It does not explicitly differentiate from sibling tools like extract_bid_requirements or extract_grant_requirements, but the mention of 'RFP or solicitation' provides some scope 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 phrase 'Use this when...' provides an explicit usage trigger, telling the agent the context in which to invoke the tool. However, it does not mention when-not-to-use or alternative tools, so it lacks the full exclusionary guidance for 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the description doesn't need to restate these. It adds context about targeting 'missing or unclear' sections, but does not elaborate on how sections are determined or what the output structure looks like. This is acceptable given the annotation coverage, but not deeply transparent.

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 immediately states the use case. There is no fluff or redundancy; every word contributes to the meaning.

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 string parameter, an output schema, and rich annotations, the description is sufficient for an agent to decide when to use it. It doesn't detail what constitutes a 'missing or unclear' section, but that level of nuance is not critical for selection given the schema and output 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 input schema provides 100% coverage for the only parameter ('text'), describing it as 'Contractor quote or estimate text.' The description adds no additional parameter-level meaning, 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 states a specific purpose: identifying missing or unclear quote sections, using an actionable conditional ('Use this when...'). It is clear about the resource (quote sections) and the action (identify/flag), distinguishing it from siblings like extract_quote_amounts or compare_quotes, though it doesn't explicitly contrast with them.

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 'Use this when a user wants missing or unclear quote sections identified' provides explicit context for when to invoke the tool. It lacks exclusions or named alternatives, keeping it one step below a perfect score, but the guidance is clear and actionable.

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 safety profile is covered. The description adds the type of analysis (flagging gaps) but does not describe the process, output format, or any side effects beyond what annotations imply.

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, front-loaded sentence that conveys the purpose directly. No filler or redundancy; 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?

Given the tool's simplicity (one param, rich annotations, output schema present), the description covers the essential trigger. However, the lack of parameter guidance leaves a minor gap, preventing a perfect score.

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?

With 0% schema description coverage, the description had to compensate for the single 'text' parameter. It only hints that the text likely contains the procurement document or quotes, but never explicitly states what content should be passed, what format is expected, or how it is processed.

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: flag missing procurement assumptions and quote-comparison gaps. The verb 'flag' plus specific resources ('procurement assumptions', 'quote-comparison gaps') distinguishes it from generic tools, though it doesn't explicitly differentiate from the similar sibling flag_missing_quote_sections.

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?

Begins with 'Use this when...', providing clear usage context. It does not mention alternatives or exclusions, but the context is specific enough to guide selection among the many sibling 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?

Annotations cover read-only/idempotent safety, so the description adds value by characterizing the output as a 'starter' (not exhaustive) and limiting to 'supported' verticals. This is contextual behavior beyond the structured 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?

A single, front-loaded sentence with no fluff. It immediately states when to use the tool and what it produces.

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 one-parameter tool with an output schema and comprehensive annotations, the description is sufficient for selection and invocation. It could list example verticals, but the output schema likely covers return structure, so no major gap exists.

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 a basic description for 'vertical'. The description adds the 'supported' constraint, implying validation/selection from a finite set, which is meaningful beyond the schema. No enums are provided, but the added constraint compensates.

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 provides a starter compliance calendar for a supported vertical, matching the name and distinguishing it from sibling checklist/matrix tools. It lacks an explicit alternative tool name but is otherwise specific about the resource and 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?

Explicitly provides a usage condition ('when a user wants a starter compliance calendar') and implies a supported vertical. It does not mention when not to use it or name alternative tools, but the context is clear enough for selection.

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 agent knows it is a safe, non-mutating operation. The description adds no additional behavioral context such as output format, limitations, or edge cases, but with annotations present, the baseline is acceptable.

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 front-loads the usage condition. 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?

The tool is simple with one parameter and an output schema, so the description does not need to explain return values. It effectively covers when to use the tool, and given the low complexity, it is sufficiently 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 has 100% coverage with the parameter 'text' described as 'Contractor quote or estimate text.' The tool description adds no further parameter semantics, but schema coverage is high, 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 the tool generates questions for a contractor based on a quote, specifying the resource (contractor) and input (quote). However, it does not distinguish it from sibling tools like build_vendor_questions or generate_vendor_questions, all of which create question sets.

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 clear usage context: 'Use this when a user wants questions to ask a contractor based on a quote.' It does not mention exclusions or alternatives, but the condition is specific enough to guide selection.

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 destructiveHint=false, so the safety profile is covered. The description adds that the tool produces a list of evidence to gather, which is mild behavioral context but doesn't go beyond what annotations imply.

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 usage condition with no filler or redundant details. 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?

Although an output schema exists, the description is too brief for a 2-parameter tool with 0% schema coverage. It lacks guidance on what to include in 'text' or how 'org' affects the output, making the tool under-specified for an 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 0%, and the description does not explain the roles of 'text' or 'org'. It only implies the grant context, leaving the agent to guess parameter meaning from names alone.

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 ('generate a list of supporting evidence/documents to gather for a grant') and the resource (grant evidence), making it easy to distinguish from sibling tools like explain_required_documents or build_application_checklist.

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 explicitly says 'Use this when a user wants a list of supporting evidence/documents to gather for a grant,' providing a clear trigger condition. It doesn't mention alternatives or exclusions, but the context is specific enough for most 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds no behavioral context about what the plan generation entails, how the input is processed, or any side effects. With no added context beyond the annotations, this is a notable gap.

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 unnecessary words, earning high marks for conciseness. It is appropriately front-loaded with the usage trigger, though the brevity contributes to under-specification that is penalized elsewhere.

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?

Even for a simple tool with one optional parameter and an output schema, the description is too sparse. It omits what the plan contains, what the text input is for, and any intended use context beyond the trigger phrase. The output schema may help, but the description alone is insufficient.

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 'text' with no description and schema coverage is 0%. The tool description does not explain what 'text' should contain or how it is used. This leaves the agent completely unguided on how to populate the input.

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 tool is for a scoped MCP/AI implementation package plan, which distinguishes it from sibling tools. However, it does not clearly specify what the plan contains or explicitly state the generation action beyond the name, making it somewhat vague.

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 'Use this when a user wants a scoped MCP/AI implementation package plan' provides clear, explicit context for when to invoke the tool. However, it lacks any mention of when not to use it or alternatives among the sibling tools, so it stops 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, covering safety and repeatability. The description adds no extra behavioral context (e.g., input format expectations), but it does not contradict 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 with no fluff, front-loading the usage condition. It is appropriately short 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?

With two parameters and zero schema descriptions, the description should clarify what inputs are expected. It does not, making the tool ambiguous for correct invocation. The output schema exists but return values are still not prose-described.

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%, and the description never mentions the 'text' or 'vendor' parameters. It entirely fails to compensate for the lack of schema descriptions, leaving parameter roles ambiguous.

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 produces 'likely reasons a solicitation may be a weak fit or no-bid,' which is a specific output. It is distinct from sibling scoring tools like score_bid_fit, but relies on the title for the action verb (generate).

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 trigger condition ('when a user wants likely reasons...') but does not explicitly mention when not to use it or name alternatives. This is clear context without 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 already declare readOnly=true, idempotentHint=true, and destructiveHint=false. The description adds useful context that the checklist is a 'starter' (not final) and only for a 'supported lane', but does not explain behavior beyond that. No contradiction 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?

The description is a single, front-loaded sentence with no filler or redundant information. Every word adds value, though it is short due to under-specification rather than being concise and complete.

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 an output schema and annotations, the description is too sparse for reliable tool selection. It lacks parameter semantics, clear sibling differentiation, and any details about supported lanes or how the checklist is generated. There are many analogous checklist tools, so more context is necessary.

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%, and the description provides minimal parameter guidance. 'lane' is mentioned as a supported category but not defined, and 'text' is entirely unexplained. The description fails to compensate for the lack of schema documentation.

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 produces a starter permit/opening checklist for a supported lane, which distinguishes it from sibling checklist tools like build_application_checklist or build_firegrant_checklist. However, the term 'lane' is ambiguous and not defined, slightly reducing clarity.

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 specific trigger condition ('when a user wants a starter permit/opening checklist') but provides no guidance on when not to use it or how it compares to the many similar sibling checklist tools. No exclusions or alternative recommendations are given.

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 all annotations false, the description must carry the behavioral disclosure burden. It only mentions that the report is 'saved', implying a side effect, but does not explain whether it overwrites existing reports, requires specific permissions, or has other side effects. No additional behavioral context is provided.

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 front-loads the usage context. Every word contributes meaning without 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?

For a tool with one well-documented parameter and an output schema present, the description provides sufficient context for an agent to select and invoke it. The main gap is the lack of behavioral detail around what 'saved' entails, but the simplicity of the tool reduces the need for extensive explanation.

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 'text' parameter as 'Contractor quote or estimate text' (100% coverage). The description adds minimal semantic value by echoing 'quote text', which is redundant. Baseline of 3 is appropriate since the schema handles parameter documentation.

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 indicates the tool generates a saved Contractor Quote Check report from quote text. It distinguishes from sibling tools like generate_contractor_questions by focusing on report generation, but it phrases the purpose indirectly as 'Use this when...' rather than stating 'This tool generates...'.

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 when-to-use guideline: 'Use this when a user explicitly wants a saved Contractor Quote Check report generated from quote text.' It does not mention alternatives or explicit when-not-to-use scenarios, but the 'explicitly wants' qualifier provides useful context for tool selection.

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, covering safety and side effects. The description adds no behavioral details beyond purpose, but given the strong annotation coverage, it does not need to. No contradiction exists.

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 12 words, front-loaded with the usage condition. Every word contributes to understanding the tool's purpose and when to use it. 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 full schema coverage, an output schema, and strong annotations, the description is largely sufficient. It could explicitly mention that output is a list of questions, but the output schema covers that. The main gap is lack of differentiation from similar siblings, but the RFP-specific wording mitigates this.

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%: the 'text' parameter is documented as 'RFP or solicitation text.' The description's 'derived from an RFP' reinforces this but adds no additional format, length, or example details. With high schema coverage, a 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: 'clarification questions derived from an RFP.' This uses a specific verb+resource pattern and distinguishes it from sibling tools like generate_vendor_questions or build_inspection_questions by explicitly mentioning RFP context.

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 'Use this when a user wants clarification questions derived from an RFP' provides clear usage context. It does not explicitly name alternatives or exclusions, but the RFP-specific framing implicitly guides selection among siblings.

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 safety profile is clear. The description adds no further behavioral details beyond the purpose, such as side effects or return behavior; it only adds domain scoping. This is adequate but not enriched.

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 use case. Every word earns its place, and 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?

The tool is simple, with few parameters, strong annotations, and an output schema. The description gives the trigger condition and scope, while the annotations and output schema cover safety and return structure. The main gap is parameter explanation, but that is accounted for separately.

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%, and the description does not explain the 'request' or 'supplier' parameters. With no parameter descriptions in the schema or the tool description, an agent cannot infer what values to pass or what semantics the parameters carry. This fails to compensate for low 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 tool generates a 'supplier intake checklist' and scopes it to 'inventory or travel/resort offers,' which distinguishes it from sibling checklist tools like build_firegrant_checklist or generate_rfp_questions. This is a specific verb-resource pairing with a defined domain.

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 begins with 'Use this when a user wants a supplier intake checklist,' giving a clear trigger condition. It does not explicitly mention alternatives or exclusions, but the specificity of the scenario provides sufficient usage context relative to siblings.

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, idempotentHint, and destructiveHint, covering the safety profile. The description adds that the packet is 'drafted from a maintenance issue,' which clarifies the input source, but provides no further behavioral context (e.g., output format, side effects) beyond the annotations and 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 sentence of about 20 words, front-loaded with the usage trigger. No redundant information or filler, 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 simplicity (1 parameter, output schema present, robust annotations), the description is adequate. It explains the core use case and source. It could be more complete by elaborating on what the packet includes or potential variations, but this is not critical for a straightforward generation 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 one undocumented parameter 'text' (0% coverage). The description compensates by implying that 'text' should contain the maintenance issue description, giving essential meaning to the parameter. However, it does not explicitly state 'text' is the maintenance issue, leaving some ambiguity.

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 generates a vendor-dispatch information packet from a maintenance issue, using a specific verb and resource. This distinguishes it from sibling tools like generate_vendor_questions or triage_maintenance_issue, which focus on different aspects.

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 explicitly says 'Use this when a user wants a vendor-dispatch information packet drafted from a maintenance issue,' providing clear context for when to use the tool. However, it does not mention when not to use it or name alternative tools, so it lacks 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds the timing detail 'before comparing quotes' but does not disclose further behavioral traits such as output format, length, or how the text input is used.

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 uses no filler. Every word contributes to the intended usage context, 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?

While the tool is simple, has output schema, and is well annotated, the complete absence of parameter semantics leaves a significant gap. The description covers purpose and timing but not what input is expected, which is essential 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 schema has one required parameter, 'text', with no description and 0% schema description coverage. The tool description never explains what 'text' should contain, leaving the agent to guess whether it is a vendor description, a request summary, or something else.

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 a specific use case: generating questions to send vendors before comparing quotes. It conveys the verb and resource clearly, but does not distinguish this tool from the sibling tool build_vendor_questions, which appears to serve a very similar 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 explicitly frames the tool with 'Use this when a user wants questions to send vendors before comparing quotes,' giving a clear triggering context. However, it does not mention exclusions or direct users to the sibling build_vendor_questions, so it stops short of full alternative 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?

The annotations already indicate that the tool is read-only, idempotent, and non-destructive. The description does not add any behavioral traits beyond these, such as how inputs are processed, what the response includes, or any limitations. It provides no extra context that would help an agent understand side effects or requirements.

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 a clear usage instruction and no redundant content. It is appropriately concise for the information it conveys, though it is also minimal. The structure is clean 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 two parameters with no semantic explanations, and the description only provides the high-level purpose. It lacks essential information about what 'lane' and 'text' mean, how to supply them, or what kind of output to expect. Even with an output schema present, the description is not complete enough for an agent 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?

The input schema defines two string parameters ('lane' and 'text') with zero descriptions, and the description does not explain either parameter. With schema description coverage at 0%, the description was expected to compensate by explaining parameter meaning, but it does not. This leaves an agent without any guidance on how to set these fields.

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: to identify likely forms or approvals for a project. The verb 'identify' and resource 'likely forms or approvals' make the core function clear, though it does not explicitly differentiate from sibling tools that deal with documents or checklists.

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 condition: 'Use this when a user wants likely forms or approvals identified for a project.' This provides direct guidance on when to invoke the tool, but it does not mention when not to use it or list alternatives, so it lacks 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that the items are 'likely', implying a heuristic nature, which is useful but not extensive. It lacks details about return format, but that is covered by the 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 sentence that is front-loaded with the usage trigger. There is no wasted wording, and it is 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 simplicity (one optional parameter, output schema present, safe annotations), the description is mostly complete. It covers when to use the tool and the nature of the items, leaving out only details that are already in the schema or are implied by the tool's name.

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 for the only parameter 'vertical' is 100%, with the schema describing it as 'Compliance calendar vertical identifier.' The description's 'compliance lane' aligns with this, but adds no further meaning beyond the schema, 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 indicates that the tool lists likely renewal/checklist items from a compliance lane. It uses a specific verb and resource, distinguishing it from generic list tools, though it does not explicitly compare to sibling tools.

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 states when to use the tool ('when a user wants likely renewal/checklist items'), providing clear context. It does not mention alternatives or exclusions, but for a simple tool this is sufficient.

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 destructiveHint=false, so the agent knows this is a safe operation. The description adds that it produces a 'consistent listing structure,' which is useful context, but doesn't discuss auth, rate limits, or other behavioral details.

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 wasted words. It efficiently communicates the primary use case.

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?

Although annotations and output schema exist, the description fails to explain the input parameters or the exact behavior of normalization. With only 2 params and no param documentation, the tool is under-specified 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?

The schema has 2 parameters (request and supplier) with 0% description coverage, and the tool description provides no information about these parameters. The agent is left with no guidance on what 'request' or 'supplier' should contain, which is a major gap.

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 normalizes inventory fields into a consistent listing structure, with a specific verb and resource. It distinguishes itself from siblings by its unique focus on normalization, 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 explicitly starts with 'Use this when a user wants...' which gives a clear condition for use. It doesn't mention alternative tools, but the context is specific enough to guide selection.

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, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds that it categorizes urgency from text, but does not disclose additional behavioral details such as the urgency scale, error conditions, or any side effects. With annotations providing the core safety information, the description adds some context but not rich behavioral detail.

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 with the directive 'Use this when...' and contains no redundant information. Every word contributes to the instruction, 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?

For a simple tool with one parameter, the description is adequate given the presence of a comprehensive output schema and safety annotations. It clearly states when to use the tool and what input to provide. It could be more complete by mentioning the urgency categories or distinguishing from sibling tools, but these are not essential given the output 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 0%, leaving the 'text' parameter undefined. The description compensates by indicating that the input is the issue text ('from issue text'), giving semantic meaning to the parameter. While it does not provide examples or format specifications, the clarification is sufficient for a single string 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?

The description clearly states the tool's function: categorizing maintenance urgency from issue text. It uses a specific action ('categorized') and resource ('maintenance urgency'), making the purpose clear. However, it does not explicitly distinguish itself from similar sibling tools like triage_maintenance_issue, so it lacks sibling differentiation.

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 clear usage context: 'when a user wants maintenance urgency categorized from issue text.' This tells the agent exactly when to invoke the tool. It does not mention alternatives or when not to use it, but the context is specific enough to guide selection.

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 readOnlyHint=false, idempotentHint=false, and destructiveHint=false, so the write nature is known. The description adds only the action itself ('record checkout interest') without additional behavioral context such as permission requirements, duplicate handling, or side effects beyond what annotations already imply.

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, front-loading the core instruction. Every word contributes to the intent.

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 a simple purpose, but the description omits clarification for product_id and email semantics, making it insufficient for an agent to correctly populate all parameters in all cases. It is minimally adequate but leaves 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 has 0% description coverage, and the description only mentions 'price point.' It does not explain the meaning or purpose of product_id or email, leaving the required product_id ambiguous and the optional email's role undefined.

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 records checkout interest at a stated price point, using a specific verb ('record') and resource ('checkout interest'). It distinguishes itself from siblings like save_lead by focusing on checkout interest and a price point.

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 explicitly says 'Use this only when a user explicitly asks to record checkout interest at a stated price point,' providing clear when-to-use guidance and implying it should not be used otherwise. It does not name alternatives but sets a clear boundary.

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 all false, providing no read-only or destructive hints. The description adds a consent requirement and product scoping, which is useful. However, it does not disclose idempotency, duplicate handling, or update behavior, though the output schema exists to clarify return 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?

A single, front-loaded sentence with zero waste. Every word earns its place, and the key usage condition is stated immediately.

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 an output schema, the description covers only the usage condition. It leaves parameter semantics unexplained and does not address edge cases like duplicate saves or updates, making it incompletely specified for a write 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 descriptions cover 0% of the 4 parameters, and the description fails to explain them. 'Contact details' loosely implies name/email, but note and product_id are left ambiguous. The description does not compensate for the missing schema metadata.

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 saves user interest or contact details for a product, using a specific verb and resource. It does not explicitly distinguish from the similar sibling save_checkout_interest, so it misses full sibling differentiation.

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 condition for use: 'only when a user explicitly asks'. This implies when-not to use (absent explicit request), but no alternative tools are named, so it lacks explicit exclusions for related actions.

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, idempotentHint, and non-destructive behavior. The description adds 'checklist-style' which hints at the output format, but does not clarify scoring methodology or side effects (though none are expected). This modest addition merits a 3.

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 that immediately states when to use the tool. 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?

With an output schema and rich annotations, the description is acceptable but minimal. It lacks parameter guidance and a clear definition of 'fit', which could be important for correct invocation. The 'checklist-style' hint is helpful, but overall it leaves gaps about expected inputs and scoring basis.

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% and the description does not explain the 'text' or 'vendor' parameters. It only appears to relate 'text' to the bid, but 'vendor' is left entirely unexplained, offering little help to the agent beyond 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 clearly states the tool's function: producing a checklist-style fit score for a public-safety bid. The verb 'score' and resource 'bid fit' are specific, and the mention of 'public-safety bid' differentiates it from grant or procurement scoring siblings.

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 'Use this when a user wants...' provides an explicit trigger condition. However, it does not mention when not to use it or point to alternatives such as score_bid_readiness or build_application_checklist, so it lacks exclusion criteria.

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 provide read-only, non-destructive, idempotent hints. The description adds only that the output is checklist-style, which is a modest behavioral detail. No contradictions 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?

The description is a single, front-loaded sentence that conveys the essential information without wasting words. Structure is ideal for quick scanning.

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 robust annotations and an output schema, the description is sufficient. It covers when to use it and what it produces, though it might benefit from a brief mention of what it does not do.

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 a clear description for the single 'text' parameter. The description adds no additional parameter semantics 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 tool's purpose: providing a checklist-style bid-readiness assessment from RFP text. It identifies the input (RFP text) and output style, though it doesn't explicitly differentiate from sibling tools like score_bid_fit or extract_bid_requirements.

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 opens with 'Use this when a user wants...' giving a clear usage condition. It does not mention when to avoid this tool or suggest alternatives, but the context is unambiguous.

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 safety profile is covered. The description adds that it is 'checklist-style readiness assessment', implying a read-only analysis of the provided text. It does not disclose deeper behavioral details like auth requirements, rate limits, or how results are delivered, but the annotations lower the bar for safety-related 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 sentence that is front-loaded with the usage context ('Use this when...') and packs the key information: audience (fire department), output style (checklist-style), and input (grant text). There is no redundant or filler content, making it appropriately concise.

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, the description doesn't need to explain return values. The tool is simple (2 params, read-only), and the description gives enough context to select it appropriately. However, it could be more complete by explicitly naming the parameters or noting the org field as the department name, but the presence of the output schema and annotations mitigates the need.

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 compensate by explaining parameters. It only mentions 'grant text', which likely maps to the required 'text' parameter, but does not explain the optional 'org' parameter or how it relates to the fire department. The description is too thin to fully compensate for the lack of schema descriptions, leaving the agent to guess about 'org'.

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 identifies the tool's purpose: a checklist-style readiness assessment for grant text, specifically for fire departments. It distinguishes from siblings like score_grant_readiness and score_bid_readiness by specifying the fire department context and 'grant text' input. The verb is somewhat implied ('wants a checklist-style readiness assessment') rather than explicitly stated as 'score' or 'assess', but the title reinforces the action.

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 clear usage trigger: 'Use this when a fire department wants a checklist-style readiness assessment for grant text.' This gives the agent context about when to select this tool over alternatives, such as bid readiness tools. It does not explicitly name alternatives or exclusions, but the fire department + grant text combination effectively scopes 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?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds that the tool consumes grant text and org context to produce a checklist, but doesn't disclose output format or edge cases. This is acceptable given the annotation coverage, but not rich.

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, front-loaded sentence with no filler. Every word adds 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?

With an output schema and clear annotations, the description is largely sufficient. The one-line usage guidance covers inputs and purpose, though it leaves the exact nature of the checklist implicit.

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 no descriptions, but the description maps 'text' to grant text and 'org' to organization context, giving some meaning. However, it doesn't clarify optionality or detailed semantics, so compensation is partial.

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 produces a grant-readiness checklist from grant text and organization context. The verb and resource are specific, though it doesn't explicitly distinguish from closely named siblings like score_firegrant_readiness.

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 an explicit usage condition ('Use this when a user wants...') and specifies the inputs. It doesn't mention when not to use it or name alternative tools, so it doesn't reach a 5, but the context is clear.

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 destructiveHint=false, so the description doesn't need to restate that this is a safe read-only operation. The phrase 'for human review' adds a small behavioral clue that it doesn't take direct action, but it doesn't detail the categorization process or any additional side effects. No contradiction with annotations is present.

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 17 words, front-loaded with the usage condition. It contains no redundant or filler words, and every part contributes to the overall meaning. Excellent 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?

The tool is simple: one required parameter, annotations for safety, and an output schema (though details not shown). The description gives the core purpose and usage condition, and the output schema can define return values. It is complete for the apparent complexity, though parameter semantics are weak (already scored separately).

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 one required 'text' string with no description, and schema coverage is 0%. The description implies the text is the maintenance issue but doesn't state this explicitly or provide any format, examples, or required content. This fails to compensate for the missing schema information, leaving the agent uncertain about what to pass in.

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 that the tool categorizes a maintenance issue by urgency for human review, giving a specific verb and resource. It is not a tautology and conveys the core function well. However, it doesn't explicitly distinguish itself from the sibling 'rank_urgency', which appears to serve a similar 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 starts with 'Use this when', providing an explicit condition for when the tool should be invoked. It clearly indicates the scenario: a user wants a maintenance issue categorized by urgency for human review. However, it doesn't mention when not to use it or suggest any alternatives among the sibling tools, 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.