gigaverse

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 is educational, not advice, and that output includes a disclaimer that must be shown. However, it omits other behavioral details like return format, error handling, or rate limits.

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 concise sentences: first states purpose, second provides a critical usage warning. Every word earns its place with no redundancy or fluff.

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 (2 params, no output schema), the description covers purpose and a usage constraint. However, lacking output schema, it should describe what the tool returns (e.g., eligibility status, phase-out amount). The description is adequate but not fully 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?

Schema description coverage is 50% (only magi has a description). The description adds 'MAGI (USD)' but repeats schema info. It does not explain the filing_status enum values or add meaning beyond the schema. For the undocumented filing_status parameter, the description 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 the tool's purpose: 'Educational Roth IRA MAGI phase-out check using 2026 IRS limits.' The verb 'check' and specific resource 'Roth IRA MAGI phase-out' differentiate it from sibling tools like get_practicle_info or register_partner.

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 includes a critical usage guideline: 'NOT tax or investment advice — always show the returned disclaimer to the user.' This tells the agent when to use the tool (educational) and a mandatory action (show disclaimer). It does not explicitly state when not to use it or mention alternatives, but the constraint 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?

With no annotations provided, the description carries full responsibility. It mentions 'Educational only,' signaling no actionable or state-changing side effects. It specifies what is returned, but does not explicitly declare the tool as read-only or non-destructive. The absence of parameters also implies a static fetch.

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 long, front-loading the core action ('Get information') and quickly specifying the target product and its target audience. Every clause adds value; there is no fluff or redundancy.

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

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

Given the tool has no parameters and no output schema, the description sufficiently explains what is returned (product description, pricing, launch status, links) and adds context (educational only). It could specify the exact data structure or mention common use cases, but remains complete enough for a simple info retrieval 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 tool has zero parameters, so the schema coverage is trivially 100%. Per the calibration rule for 0 parameters, the baseline score is 4. The description adds context beyond the schema by clarifying the product and the nature of the returned data, which is beneficial.

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

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

The description clearly states the tool retrieves information about a specific financial product ('Gigaverse PRActicle') and lists the content returned (product description, pricing, launch status, links). The use of 'Get' as a verb and the resource named clearly differentiate it from sibling tools like check_roth_eligibility or get_signup_status.

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 this tool is used to obtain product information, but does not explicitly state when to use it versus alternatives. It lacks a 'when to use' or 'when not to use' directive, nor does it reference sibling tools. The agent must infer usage from context rather than 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 provided, but description adds value by noting it returns no personal information and listing statuses, which aids agent understanding.

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

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

Two sentences, no fluff, front-loaded with purpose. Every sentence 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?

For a simple tool with one parameter and no output schema, the description fully covers purpose, parameters, and return characteristics.

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 pattern coverage but no description; description only mentions 'by signup_id' which is already clear from schema, adding minimal value.

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 checks the status of a signup by signup_id and lists the possible statuses, distinguishing it from sibling tools like start_signup.

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 implies use after initiating a signup, but lacks explicit when-not-to or alternative tool mentions. However, siblings provide context.

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

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

No annotations provided, but description thoroughly covers behavior: immediate return of partner_id (pending review), no API secrets pre-RIA, and activation upon RIA registration. Sandbox behavior is also detailed.

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 sentences, front-loaded with purpose and key action. Every sentence adds distinct value without redundancy.

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

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

Given no output schema, the description explains return value and status. Covers integration with start_signup, pre- and post-RIA behavior, and sandbox mode. Comprehensive for a 4-parameter 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 provides 100% coverage with descriptions for all 4 parameters. The description adds specific context about the sandbox parameter (test mode behavior) and implies the importance of email/company as required fields, but does not elaborate beyond schema for other 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?

Description clearly states the action (register a company as an integration partner), specifies eligible company types, and the immediate output (partner_id with pending status). This distinguishes it from sibling tools like start_signup.

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 instructs to pass the returned partner_id to start_signup for attribution. Mentions the prerequisite of RIA approval for revenue share, but does not directly state when not to use this tool or compare with 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 effectively discloses key behaviors: the tool does not open an account, returns a signup_url, requires human action, and is idempotent per email. Lacks details on error handling or rate limits but covers the most important aspects.

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 four sentences that front-load the purpose and key caveats before listing parameters. Every sentence adds value without any 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?

Given the tool's moderate complexity and lack of output schema, the description adequately covers the primary output (signup_url) and the human involvement requirement. However, it could be more complete by describing the return format or error conditions.

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 all parameters with 100% coverage. The description restates the parameters without adding new semantic meaning beyond the schema, so it meets the baseline but does not exceed 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: initiating a retirement-account signup. It distinguishes itself from sibling tools by specifying that it does NOT open an account and that the human must complete the process, which contrasts with eligibility checks or status lookups.

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 start a signup process) and includes a critical caution that the signup cannot be completed by an agent. However, it does not explicitly mention when not to use it or reference sibling tools as alternatives.

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