tools

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

No annotations are provided, so the description bears the full burden. It discloses the cost ($0.01 per call via x402), which is valuable behavioral context, but it omits details about authentication, rate limits, error behavior, or what happens if the schema parameter is omitted.

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 short sentences, front-loaded with the action and object. The second sentence adds essential cost information without any filler.

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 tool is relatively simple with only two parameters and no output schema, but the description leaves a meaningful gap: it does not explain the expected format of the schema parameter or behavior when schema is absent. It is adequate for basic selection 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?

The input schema has no descriptions (0% coverage), so the description must compensate. It provides minimal semantic hints: text is 'unstructured text' and schema is 'your schema description.' However, it does not clarify whether schema should be a JSON Schema, a natural-language description, or its optionality.

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: 'Extract structured JSON from unstructured text.' It clearly distinguishes this tool from siblings like summarize and web_research by focusing on extraction to a structured JSON format.

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 clearly implies when to use the tool: when you need structured JSON from unstructured text. It does not explicitly mention alternatives or exclusions, but the context is clear enough 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 but only discloses char limit and cost. It does not mention output format, error handling, or behavior on exceeding the limit. The disclosed constraints are useful but incomplete.

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 short sentences, front-loaded with the main action and followed by constraints. Every word earns its place, no 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 no output schema and no annotations, the description covers the primary purpose, a key constraint (char limit), and cost, but omits the return value format and what 'focus' accepts. This is a simple tool, so it is partially complete but leaves important gaps.

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 0%, so the description must compensate. It adds a char limit for 'text' and says 'focus' is optional, but 'optional' is already evident from the schema's required field. No meaning is given for what 'focus' actually does, leaving the parameter semantics largely unexplained.

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 'Summarize' and the resource 'any text' with a specific scope (up to ~24k chars). It distinguishes the tool from siblings by focusing on summarization rather than extraction or research.

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?

Provides clear context for when to use: summarizing text with an optional focus. It does not explicitly exclude alternatives or name when not to use, but the purpose is distinct enough that context 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 the full burden of behavioral disclosure. It adds valuable context by revealing that results are LLM-synthesized on independent hardware, that the service costs $0.02 per call, and the payment method (x402) with where to include payment. This goes beyond basic read/write semantics, though it does not cover edge cases like failure 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?

The description is exceptionally concise, using three short sentences that front-load the purpose and follow with essential behavioral and cost details. Every sentence earns its place, and there is no repetitive or irrelevant 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?

For a simple tool with one parameter and no output schema or annotations, the description is quite complete. It explains what the tool does, the nature of the output (concise cited brief), and the payment requirement. It could be slightly more explicit about return format or any prerequisites, but given the tool's simplicity, it covers the essential context well.

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 only defines 'query' as a string with no description. The tool description implies that 'query' is the question or topic to research ('answering your query'), adding a bit of meaning beyond the bare schema. However, it does not elaborate on query format, language, or length, so the compensation is minimal.

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 'searches the web and returns a concise cited brief answering your query.' It specifies the action (searching the web) and the deliverable (a concise cited brief), which distinguishes it from sibling tools like extract_structured and summarize.

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 gives no explicit guidance on when to use this tool versus alternatives. It implies general web research but does not mention sibling tools or provide any exclusions, leaving the agent to infer usage based on the tool name alone.

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