AskAIs AI Receipt Generator

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

With no annotations provided, the description adequately discloses key behaviors: it returns one-time login credentials and API key with introductory credit, and requires terms acceptance. However, it omits potential side effects (e.g., irreversibility) 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?

Three sentences, front-loaded with purpose, no redundant wording. Every sentence adds value.

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 4 parameters, no output schema, and no annotations, the description covers core functionality and return values but does not explain all parameters or long-term consequences. Adequate but 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 50% (only client_name and accept_terms have descriptions). The description does not add meaning for the parameters; it only reinforces accept_terms. Missing explanations for client_version and preferred_language.

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 verb 'Create' and resource 'AskAIs account', clearly distinguishing it from sibling tools like generate_receipt or get_balance.

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 context for when to use ('without opening a browser') and a prerequisite ('user must explicitly accept terms'), but does not explicitly state when not to use or provide 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?

No annotations are provided, so the description carries the full burden. It discloses the cost ($0.10 on success) but fails to mention other important behaviors such as prerequisites (e.g., need for api_key from create_free_account), side effects, failure modes, or whether authentication is required. This is insufficient for a tool with 19 parameters and no 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 very concise with two sentences, but it sacrifices necessary detail. It is appropriately front-loaded but omits critical information about parameters, returns, and usage 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?

Given the high complexity (19 parameters, no output schema, no annotations), the description is far from complete. It does not explain the return value (PDF), provide parameter guidance, or include any usage examples. The tool demands a more thorough description to be usable by an AI 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 schema description coverage is only 21%, yet the description provides no additional meaning for the 19 parameters. It does not mention any parameter names, types, or how they relate to the output. The agent must rely solely on the sparse schema descriptions, making parameter understanding very difficult.

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 downloadable receipt PDF for legitimate transactions, with a specific verb 'Generate' and resource 'receipt PDF', effectively differentiating it from sibling tools like create_free_account, get_balance, and get_usage_rules.

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 legitimate transactions and mentions a cost, but does not explicitly state when to use versus alternatives or when not to use. The required boolean parameter's schema description provides some guidance, but the description itself lacks explicit usage 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, the description carries full burden. It only states the basic purpose but does not disclose side effects, authentication requirements, rate limits, or error handling. For a simple read operation, more detail could be helpful.

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 unnecessary words. It efficiently conveys the purpose.

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 low complexity (one optional parameter, no output schema), the description is mostly adequate. It could be improved by specifying the return type (e.g., 'returns a number') but is sufficient for basic understanding.

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% for the single parameter (api_key). The description does not add any parameter semantics beyond what the schema provides. The baseline is 3, and no adjustment is needed.

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 ('return') and the resource ('remaining prepaid AskAIs API credit'), with scope ('for the connected account'). It is distinct from sibling tools like create_free_account, generate_receipt, and get_usage_rules.

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 vs alternatives. Usage is implied by the function (checking balance), but no exclusions or conditions are provided. The description only states what the tool does.

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 indicates a read operation with no side effects. Could explicitly state 'no changes will be made' but current wording 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?

Single sentence, front-loaded with 'Read'. Every word adds value, no 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?

Tool is simple (no params, no output schema). Description fully covers purpose, usage context, and behavior for its 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?

Tool has zero parameters, so description need not add details. Baseline is 4 for zero parameters with 100% 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 uses a specific verb 'Read' and resource 'rules', listing four categories: pricing, free-credit, privacy, acceptable-use. It clearly distinguishes from sibling tools: create_free_account, generate_receipt, get_balance.

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: 'before creating an account or receipt.' This gives clear context and implies avoidance when not in that scenario.

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