Qualityiris

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

No annotations exist. The description says it returns a plain-language overview but does not elaborate on behavior beyond that (e.g., no side effects, performance). It is adequate but minimal.

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

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

Single sentence with no redundancy. Every word adds value; no wasted text.

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

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

Given no parameters, no output schema, and no annotations, the description sufficiently conveys the tool's return. It does not detail format or contents, but for a simple overview this is acceptable.

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?

Zero parameters with 100% schema coverage. Description adds meaning by specifying 'plain-language product overview', clarifying the output's tone and scope, meeting the baseline of 4.

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

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

Description clearly states verb ('Returns'), resource ('product overview of Qualityiris'), and context ('AI-powered QA platform for apparel manufacturing'). It distinguishes from sibling tools (get_faq, list_features, list_pricing_plans) which cover 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 implies use for a general overview but does not explicitly state when to use this tool versus alternatives. No exclusions or recommendations are provided.

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 burden. It accurately describes a read-only retrieval of Q&A data. For a parameterless read operation, this is sufficient, though it could mention idempotency or static nature.

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 containing all necessary information with no wasted words. The purpose is front-loaded, achieving clarity in minimal space.

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 is complete for its simplicity, but lacks output schema. It tells what is returned (questions and answers), but no structure details. Given sibling tools, the context is sufficient.

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 zero parameters, so the description adds no parameter info. Baseline for 0 parameters is 4, and the description is adequate given no parameters exist.

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 returns 'common evaluation questions and answers about Qualityiris', specifying the verb, resource, and context. This distinguishes it from siblings like about_qualityiris, list_features, and list_pricing_plans.

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 retrieving FAQ content but provides no explicit guidance on when to use this tool versus alternatives. No when-not or preferred scenarios are mentioned, leaving the agent to infer based on tool names.

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, so description bears full burden. It does not disclose any behavioral traits beyond the obvious read operation. For a simple list tool with no parameters, the description is adequate but could mention that it returns a list of feature module names or 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?

A single, clear sentence with no fluff. Every word contributes to understanding the tool's function.

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

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

Given no parameters and no output schema, the description is minimal. It states what the tool lists, but doesn't clarify the format (e.g., names only, with descriptions) or whether it's a full list. Adequate but slightly vague.

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

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

No parameters exist, so schema coverage is trivially 100%. The description adds nothing beyond the schema, but baseline for zero parameters is 4.

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

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

The description 'Lists the core Qualityiris feature modules' uses a specific verb ('Lists') and clearly identifies the resource ('core Qualityiris feature modules'). It distinguishes from sibling tools (about_qualityiris, get_faq, list_pricing_plans) which cover different topics.

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

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

No explicit guidance on when to use this tool vs alternatives, but the tool's purpose is self-explanatory and siblings cover distinct topics, so usage is implied. Lacks any when-not advice.

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, so description carries full burden. It states returns pricing but doesn't mention read-only nature, auth needs, or other behavioral traits; adequate but minimal.

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

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

Single sentence with specific, relevant details—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?

Fully describes the tool's return value with no output schema; no missing information for a parameterless list 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?

No parameters in schema; schema coverage is 100%. Baseline of 4 applies as description adds no parameter info.

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?

Clearly states it returns Qualityiris pricing with specific amounts, distinguishing it from sibling tools about general info, FAQs, and features.

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 tells when to use (for pricing info), and with sibling context, it's clear this is the pricing tool, but no explicit when-not-to-use or alternatives.

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