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

With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions executing a sequence of API calls and generating a 'live trace', it doesn't disclose important behavioral aspects: whether this creates persistent data, what authentication is required, whether it's idempotent, what side effects occur, or what the output format looks like. The description provides some context about the multi-step nature but misses critical operational 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 appropriately concise with two sentences that each serve a distinct purpose: the first explains what the tool does, the second explains when to use it. There's no redundant information or unnecessary elaboration. The structure could be slightly improved by front-loading the core functionality more clearly, but overall it's 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?

Given this is a multi-step API execution tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool actually creates (despite the name 'create_demo_shop'), what the output looks like, what errors might occur, or important behavioral constraints. For a tool that presumably orchestrates multiple API calls with potential side effects, more comprehensive documentation 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 has 100% description coverage, with the single parameter 'api_url' clearly documented as 'Optional URL to simulate the Tunzaa environment for grounding.' The description doesn't add any meaningful parameter semantics beyond what the schema already provides - it doesn't explain when to use the api_url parameter, what values are valid, or how it affects the execution. Baseline 3 is appropriate when schema coverage is complete.

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 'executes a full sequence of Tunzaa API calls (Token -> Payment -> Installments)', which provides a clear high-level purpose. However, it doesn't specify what resource is being created (a 'demo shop' as implied by the name) or differentiate from sibling tools like 'initiate_payment' or 'get_token' that handle individual steps. The phrase 'ultimate grounding tool' is vague marketing language rather than functional specification.

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 states 'Use this to see a 'live trace' of the API, allowing you to generate perfect integration code', which provides clear context about when this tool should be used (for API exploration and code generation). However, it doesn't mention when NOT to use it or explicitly contrast with sibling tools that handle individual API steps, leaving some ambiguity about alternative approaches.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'complex object structure,' hinting at input complexity, but fails to disclose critical traits: whether this is a write operation (implied by 'create'), permission requirements, side effects (e.g., database changes), error handling, or response format. For a mutation tool with zero annotation coverage, this is a significant 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 appropriately sized with two sentences that are front-loaded: the first states the purpose, and the second adds context. There's no wasted text, but the second sentence could be more actionable (e.g., specifying key parameters). It's efficient but not perfectly structured for maximum clarity.

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

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

Given the complexity (9 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't address the mutation nature, potential side effects, error scenarios, or what happens after creation (e.g., returns a plan ID). For a tool with high parameter count and no structured safety hints, more context is needed to guide effective use.

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

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

Schema description coverage is 78% (high), so the baseline is 3 even with no parameter info in the description. The description adds minimal value beyond the schema by noting 'complex object structure,' but doesn't explain parameter interactions (e.g., 'custom_interval' depends on 'payment_frequency') or provide examples. It compensates slightly but not enough to raise the score.

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: 'Create a new installment plan.' It specifies the action (create) and resource (installment plan), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'edit_installment_plan' or 'initiate_payment,' which would require explicit comparison for a score of 5.

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

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

The description provides implied usage guidance: 'Use this to understand the complex object structure required for installment-based payments.' This suggests it's for creating plans with structured data, but it lacks explicit when-to-use rules, alternatives (e.g., vs. 'edit_installment_plan'), or exclusions. No misleading information is present, but guidance is minimal.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool performs a cancellation/deletion (implying a destructive mutation) and mentions verifying the response structure, but lacks critical behavioral details: it doesn't specify if the deletion is reversible, what permissions or authentication are required, any rate limits, side effects (e.g., impact on related payments), or error handling. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is concise with two sentences, front-loading the primary action ('Cancel/Delete an existing installment plan.') and following with a secondary purpose. There is no wasted text, but the second sentence about verifying response structure feels somewhat disconnected and could be integrated more smoothly. Overall, it's efficient but not perfectly structured.

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

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

Given the tool's complexity (a destructive mutation with 2 parameters, 50% schema coverage, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits, full parameter meanings, output expectations, and usage context. The mention of response structure verification is insufficient to cover these gaps, making it inadequate for safe and effective agent use.

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

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

Schema description coverage is 50% (only 'plan_id' has a description). The description adds no parameter-specific information beyond what the schema provides—it doesn't explain the 'address' parameter or provide additional context for 'plan_id'. With low schema coverage, the description fails to compensate for undocumented parameters, resulting in minimal added value. The baseline is adjusted downward due to the coverage gap, but the description doesn't worsen it.

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 with specific verbs ('Cancel/Delete') and identifies the resource ('an existing installment plan'). It distinguishes from siblings like 'edit_installment_plan' and 'get_installment_plan' by focusing on removal rather than modification or retrieval. However, it doesn't explicitly differentiate from all siblings (e.g., 'create_installment' is for creation, but this is implied).

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 minimal guidance: it states to use this tool for cancellation/deletion, but offers no context on when to use it versus alternatives (e.g., when not to delete, prerequisites like plan status). It mentions verifying the cancellation response structure, which hints at a testing use case, but this is vague and doesn't clarify operational scenarios. No explicit when/when-not or alternative tool references are included.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, error handling, or what the response entails. The mention of 'mutable via the Tunzaa API' adds some context but is insufficient for a mutation tool.

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

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

The description is concise with two sentences, front-loading the core purpose. However, the second sentence about 'mutable via the Tunzaa API' could be more integrated or omitted if it doesn't add actionable guidance, slightly reducing efficiency.

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

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

Given the complexity of a mutation tool with 3 parameters, no annotations, no output schema, and incomplete parameter coverage, the description is inadequate. It fails to provide necessary context on behavior, usage, or output, leaving significant gaps for an AI agent to operate effectively.

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

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

Schema description coverage is 67% (2 out of 3 parameters have descriptions). The description adds minimal value beyond the schema, as it doesn't explain parameter meanings, constraints, or examples beyond the schema's details for 'plan_id' and 'updates'. The 'address' parameter lacks documentation in both schema and description, but the baseline is 3 due to moderate 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 action ('Update') and resource ('an existing installment plan'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'create_installment' or 'delete_installment_plan', which would require more specific context about when to use each.

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 minimal guidance, mentioning only that it's for updating plans and referencing the Tunzaa API for mutable fields. It lacks explicit when-to-use instructions, alternatives (e.g., vs. create_installment), prerequisites, or exclusions, leaving usage context unclear.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns details like 'status, schedules, etc.,' but does not disclose critical behavioral traits such as whether it's a read-only operation, authentication requirements, error handling, or rate limits. This leaves significant gaps for an AI agent to understand how to use it safely and effectively.

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

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

The description is concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose and usage. Every sentence adds value without redundancy, making it easy to parse and understand quickly.

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

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does but lacks details on behavioral aspects, parameter usage, and output format. Without annotations or an output schema, more context would be helpful for the AI agent to use 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 has 50% description coverage (only 'plan_id' is described). The description does not add any parameter-specific information beyond what the schema provides. It implies the tool retrieves details for a 'specific installment plan,' which aligns with the 'plan_id' parameter, but does not explain the purpose of the 'address' parameter or provide additional context. With moderate schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Get details of a specific installment plan.' It specifies the verb ('Get') and resource ('installment plan'), and mentions the type of details returned ('status, schedules, etc.'). However, it does not explicitly differentiate from sibling tools like 'list_installments' or 'get_payment_status,' which slightly reduces 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 provides implied usage guidance: 'Use this to see the precise fields returned for a plan.' This suggests it's for retrieving detailed information about a specific plan, but it does not explicitly state when to use this tool versus alternatives like 'list_installments' or 'get_payment_status,' nor does it mention prerequisites or 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool checks status and lists possible states (COMPLETED, PENDING, FAILED), which gives some context about expected behavior. However, it lacks details on permissions, rate limits, error handling, or whether it's idempotent, which are important for a payment-related tool. The description does not contradict annotations, but it's insufficient for full 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 concise with two sentences that efficiently convey the tool's purpose and utility. It is front-loaded with the main action ('Check the status...') and avoids unnecessary details. However, it could be slightly more structured by explicitly separating usage guidance from purpose, but overall it's well-sized with minimal waste.

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

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

Given no annotations, no output schema, and moderate schema coverage, the description provides basic purpose and status context but lacks completeness. It does not explain return values, error cases, or dependencies (e.g., requiring a valid 'transactionID' from 'initiate_payment'), which are crucial for effective tool use. The description is adequate as a starting point but has clear gaps for a payment status 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 description coverage is 50% (only 'transactionID' has a description). The description does not add meaning beyond the schema, as it does not explain parameters like 'address' or provide additional context for 'transactionID'. Since schema coverage is moderate, the baseline is 3, but the description fails to compensate for the undocumented 'address' parameter, leaving gaps in understanding.

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 with a specific verb ('Check') and resource ('status of a payment transaction'), distinguishing it from siblings like 'initiate_payment' (which creates payments) and 'get_installment_plan' (which retrieves plan details). It explicitly mentions the tool helps understand status states, which adds clarity about its informational 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 implies usage by stating it's 'helpful for understanding the various status states... for your application logic,' suggesting it should be used to monitor payment outcomes. However, it does not explicitly state when to use this tool versus alternatives (e.g., vs. 'handle_callback' for real-time updates) or provide exclusions, leaving some ambiguity in context.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: the tool retrieves an access token, automatically refreshes internal tokens, and serves for credential verification and token structure inspection. It doesn't mention side effects, error conditions, or performance characteristics, but covers the core operational behavior adequately for a simple retrieval tool.

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

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

The description is extremely concise (three sentences) with zero wasted words. Each sentence adds distinct value: the core function, an important behavioral detail (automatic refresh), and usage context. It's front-loaded with the primary purpose and efficiently 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 low complexity (one optional parameter, no output schema, no annotations), the description is reasonably complete. It explains what the tool does, key behavior (automatic refresh), and primary use cases. For a simple token retrieval tool, this provides sufficient context, though it could benefit from mentioning response format or error handling.

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

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

The input schema has 100% description coverage, with one optional parameter ('address') fully documented in the schema. The description adds no parameter-specific information beyond what the schema provides. According to the rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 with specific verbs ('retrieve', 'refreshes') and identifies the resource ('Tunzaa access token'). It distinguishes from siblings by focusing on authentication tokens rather than payment/installment operations. However, it doesn't explicitly contrast with other authentication-related tools since none are listed among 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 description provides implied usage context ('verify your API credentials', 'see the internal token structure'), suggesting this is for authentication validation and debugging. However, it lacks explicit guidance on when to use this versus alternatives (e.g., whether to call this before other operations) or any exclusion criteria. The mention of 'refreshes internal token automatically' hints at a maintenance use case but isn't framed as explicit 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?

No annotations are provided, so the description carries the full burden. It mentions 'simulate or handle' which suggests both testing and production use, but doesn't clarify whether this is a read-only operation, if it modifies data, what permissions are needed, or what the response looks like. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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

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

The description is two concise sentences that efficiently convey the tool's purpose and value. The first sentence states what it does, the second explains why it's useful. There's no wasted verbiage or redundant information.

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

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

Given no annotations and no output schema, the description provides adequate basic purpose but lacks important behavioral context for a tool that appears to handle webhook payloads. It doesn't explain what happens after simulation/handling, whether there are side effects, or what the agent should expect as a result. For a 6-parameter tool in a payment system context, more completeness would be helpful.

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

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

Schema description coverage is 100%, so the schema fully documents all 6 parameters. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain format details or provide examples). With complete schema coverage, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Simulate or handle the callback payload sent by Tunzaa to your webhook.' It specifies the verb ('simulate or handle') and resource ('callback payload'), but doesn't explicitly differentiate from sibling tools like 'get_payment_status' or 'initiate_payment' which handle different aspects of the payment flow.

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 some usage context: 'Essential for grounding your webhook integration code with real payload examples.' This implies it's used for testing or development with webhooks, but doesn't explicitly state when to use it versus alternatives like 'get_payment_status' for checking status directly, or provide clear 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?

No annotations are provided, so the description carries the full burden. It mentions the tool is for initiating payments and inspecting response structures, but it doesn't disclose critical behavioral traits like whether this is a live transaction or demo, authentication requirements, rate limits, error handling, or what happens after initiation (e.g., callback triggering). For a payment tool with zero annotation coverage, this is a significant 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 appropriately sized with two sentences. The first sentence states the purpose clearly, and the second provides usage context. There's no wasted text, and it's front-loaded with the core function. However, the second sentence could be more direct about tool usage rather than focusing on code implementation.

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

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

Given the complexity of a payment initiation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., transaction effects, security), doesn't explain the response structure mentioned, and provides minimal guidance on usage. For a tool that likely involves financial transactions, this is inadequate despite the good schema coverage.

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

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

Schema description coverage is 100%, so the schema already documents all 4 parameters thoroughly. The description doesn't add any parameter-specific semantics beyond what's in the schema (e.g., it doesn't explain format details for 'customer_msisdn' or 'reference' beyond the schema's descriptions). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate with extra insights.

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: 'Initiate a payment request (M-Pesa, etc.) via Tunzaa.' It specifies the action (initiate) and resource (payment request) with platform context (Tunzaa). However, it doesn't explicitly differentiate from sibling tools like 'get_payment_status' or 'handle_callback' beyond the 'initiate' verb.

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 implied usage guidance: 'Call this to inspect the response structure needed to implement mobile money flows in your local code.' This suggests it's for development/testing purposes, but it doesn't explicitly state when to use this vs. alternatives like 'get_payment_status' or provide clear exclusions. The context is somewhat clear but lacks explicit 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?

With no annotations provided, the description carries the full burden. It discloses that the tool returns paginated results and plan summaries, which is useful behavioral context. However, it doesn't cover other aspects like rate limits, authentication needs, or error handling, leaving gaps for a read operation.

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

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

The description is two sentences with zero waste, front-loading the core purpose and efficiently adding usage context. Every word earns its place, making it highly concise and well-structured.

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

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

For a read tool with 3 parameters, 67% schema coverage, and no output schema, the description provides basic purpose and behavioral hints but lacks details on return format, error cases, or the 'address' parameter. It's minimally adequate but has clear gaps given the complexity.

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 67% (2 out of 3 parameters have descriptions). The description adds no parameter-specific information beyond what the schema provides, such as explaining the 'address' parameter. Baseline is 3 since the schema does moderate lifting, but the description doesn't compensate for the undocumented 'address' 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 verb ('List') and resource ('existing installment plans'), making the purpose unambiguous. It distinguishes from siblings like 'get_installment_plan' by indicating it returns multiple plans rather than a single one, though it doesn't explicitly name alternatives.

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

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

The description implies usage for viewing pagination and plan summaries, suggesting it's for browsing multiple plans. However, it doesn't explicitly state when to use this vs. alternatives like 'get_installment_plan' for single plans or provide exclusions, leaving some ambiguity.

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