ntriq-agentshop

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 value by stating the cost ('$0.02 USDC per call'), which is a key behavioral trait not covered by the schema. However, it lacks details on other aspects such as rate limits, error handling, or output format, leaving gaps in transparency for a tool that performs data extraction.

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 highly concise and front-loaded, consisting of two sentences that efficiently convey the tool's purpose and cost. Every sentence earns its place by providing essential information without redundancy or fluff, making it easy for an agent to parse quickly.

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 complexity (data extraction from images) and the absence of both annotations and an output schema, the description is partially complete. It covers the purpose and cost but lacks details on behavioral traits, output format, and usage guidelines. This leaves significant gaps for an agent to understand how to invoke and interpret results effectively.

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 100%, so the schema already documents all three parameters thoroughly. The description does not add any semantic details beyond what the schema provides, such as examples or constraints for 'extraction_hint'. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description neither compensates nor detracts.

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: 'Extract structured data from screenshots of dashboards, tables, forms, or UIs.' It specifies the verb ('extract') and resource ('structured data'), and identifies the source material ('screenshots'). However, it does not explicitly differentiate from sibling tools like 'document_intelligence' or 'invoice_extract', which may also extract data from documents, leaving some ambiguity about when to choose this tool over others.

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 no guidance on when to use this tool versus alternatives. It mentions the cost per call, which is a usage consideration, but does not specify contexts, prerequisites, or exclusions. Without explicit when-to-use or when-not-to-use instructions, the agent lacks clear direction for selection among sibling tools like 'alt_text' or 'sentiment_analysis'.

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