zero-core-budget

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 the main behavioral traits: verifying limits, estimating ROI from historical data, and suggesting cheaper alternatives. There is no misleading information, though it could add details about what happens when limits are exceeded.

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?

Two sentences with the key information front-loaded: the tool's purpose and when to call it. Every sentence earns its place, with no redundant or filler content.

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 explains what the tool does and when to use it, but there is no output schema and the description does not mention what the return value looks like. For a check tool, understanding whether it returns approval status or a detailed report is essential; the description leaves this 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 provides 100% parameter coverage with clear descriptions for each field, so the description does not need to add much. It adds the contextual cue that this is a pre-spend check, but does not elaborate on individual parameters beyond what the schema already states.

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 specific verbs ('verifies', 'estimates', 'suggests') and clearly identifies the resource as a pre-spend budget approval check. It distinguishes itself from sibling tools like get_spending_report and report_spend by emphasizing it is the pre-payment validation step.

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 instruction 'Call this BEFORE paying for any service' provides explicit when-to-use guidance. It does not explicitly name alternative tools, but the context of 'pre-spend' versus sibling reporting tools makes the usage scenario clear 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 are empty, so the description carries the full burden. It describes what the tool returns in detail (total spent, category breakdown, top services with ROI, optimization recommendations), making its behavior transparent. It doesn't mention side effects or limitations, but given the read-only nature of a report, this is adequate.

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, front-loaded with the core purpose ('Detailed spending analytics report'), and every word adds value. 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?

With only 2 parameters and no output schema, the description covers the essential context: what the tool does, what it returns, and when to use it. It doesn't specify return format (e.g., JSON vs table), but that is not explicitly required given the tool's simplicity and the presence of a detailed description of contents.

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 already describes both parameters (agent_id, period) with 100% coverage. The description adds no additional parameter semantics beyond what the schema provides, 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 purpose: 'Detailed spending analytics report' and lists specific outputs (total spent, category breakdown, top services with ROI, optimization recommendations). This distinguishes it from siblings like check_spend, which likely provides a quicker/simpler spend check, and report_spend, which likely refers to submitting spend data.

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 use case: 'Use to understand spending patterns and find inefficiencies.' This gives context for when to use the tool, though it doesn't explicitly mention when not to use it or name alternatives among siblings. The guidance is sufficient for basic 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?

With no annotations, the description carries the burden of behavioral disclosure. It explicitly lists what the tool checks (status, uptime, payment network config) and uses 'Check' implying a read-only operation. However, it does not explicitly state side effects or return format, but this is acceptable for a simple health check.

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 redundant words. It communicates the essential purpose clearly and 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?

Given the tool's simplicity (no parameters, no output schema), the description is complete enough to convey what the tool does. It mentions the key aspects (status, uptime, configuration). It could potentially specify the output format, but that is not critical for a health check.

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

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

The tool has zero parameters, so the input schema fully covers parameter semantics. Per the guidelines, a baseline of 4 is appropriate when there are no parameters.

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

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

The description clearly states the tool's function with a specific verb ('Check') and resource ('Harvey Budget server status, uptime, and payment network configuration'). This distinguishes it from sibling tools like check_spend or get_spending_report, which focus on spending data.

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 clear context for when to use the tool (to check server health and payment network configuration), but does not explicitly mention when not to use it or name alternatives. Since the tool has a unique purpose among siblings, this is adequate.

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 full responsibility. It states what the tool lists, but does not explicitly declare it as read-only or describe the return format. The verb 'list' implies a safe, non-mutating operation, but more explicit disclosure would be beneficial.

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 no fluff, front-loading the action and purpose. Every word contributes to understanding.

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 (no parameters, no annotations, no output schema), the description adequately covers purpose, content (pricing and input requirements), and context (discovery). It could mention return format explicitly, but it's largely 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 tool has zero parameters, so schema coverage is trivially complete. The description correctly avoids parameter details and focuses on output content. This aligns with the baseline for 0-parameter tools.

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 lists all available Harvey Budget tools with pricing and input requirements, using the specific verb 'List'. It also distinguishes itself from sibling operational tools by positioning itself for discovery.

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 for discovery', giving a clear usage context. It does not name alternatives, but siblings are action-oriented, making it evident that this tool is for discovering available tools rather than performing budget operations.

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, the description carries the full burden and discloses key behaviors: free tool, upsert semantics, and a prerequisite relationship. It does not mention error handling or permissions, but for a registration tool, this is reasonably 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?

Three short sentences, each providing distinct value: purpose, usage prerequisite, and upsert behavior. No redundancy or filler, perfectly front-loaded.

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 output schema, the description covers the essential context: what it does, when to call it, and idempotency. It does not describe the response format, but that is not critical for a simple registration tool with 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%, and the schema already provides detailed parameter descriptions. The description adds no new parameter semantics beyond mapping to daily/weekly limits, so 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 registers an agent with budget limits, using a specific verb ('Register') and resource ('agent'). It also distinguishes from siblings by noting it should be called before check_spend or report_spend, and mentions upsert behavior, making its purpose 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?

Explicitly states when to use: 'call this before using check_spend or report_spend'. Also indicates it's free, providing a cost-relevant condition. This gives clear usage context and differentiates from 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, the description carries the full burden. It adds useful context about the post-payment timing and persistent ROI history, but it does not disclose details about idempotency, validation failures, or permissions. The behavior is clear enough for a simple recording tool, 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 two sentences, front-loaded with the primary action ('Record a completed spend') and includes only essential usage guidance. 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?

For a six-parameter tool with full schema coverage and no output schema, the description provides essential context: it is for completed spends, tracks outcomes, and builds ROI history. It is nearly complete, though it could mention duplicate handling or confirmation, but that is a minor 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 coverage is 100%, so all parameters are already described. The description adds the concept of 'optional outcome tracking', which hints at value_received and outcome_success, but it does not provide additional syntax or format details beyond the 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 uses a specific verb and resource: 'Record a completed spend' with optional outcome tracking. It clearly distinguishes from siblings like check_spend and get_spending_report by being the action of recording rather than checking or retrieving.

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: 'Call this AFTER paying for a service to track spending and build ROI history.' This provides clear timing and purpose, though it does not explicitly name alternative tools or exclusion cases.

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