ntriq-agentshop

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

With no annotations provided, the description carries full burden and adds valuable behavioral context: it discloses the cost ('$0.05 USDC per call') and blockchain details ('x402, Base mainnet'), which are critical for usage decisions. It also implies mutation/processing behavior through 'analyze' and specifies input formats (URL or base64). However, it doesn't mention rate limits, error conditions, or output format 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?

The description is extremely concise and front-loaded: the first clause states the core purpose, followed by key input constraints and cost details. Every sentence earns its place with no wasted words. The structure efficiently communicates essential information 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?

Given 4 parameters with full schema coverage but no annotations and no output schema, the description is moderately complete. It covers purpose, input formats, analysis types, and cost, but lacks output format details, error handling, and sibling differentiation. For a tool with significant functionality and cost implications, more behavioral context would be beneficial.

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 100%, so the schema already documents all parameters thoroughly. The description adds marginal value by mentioning 'image URL or base64' and listing analysis types, but doesn't provide additional syntax, format, or usage details beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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: 'Analyze document images — extract text, summarize, classify, or extract tables.' It specifies the verb ('analyze') and resource ('document images'), and lists the specific analysis types. However, it doesn't explicitly differentiate from sibling tools like 'invoice_extract' or 'screenshot_data' which might have overlapping functionality.

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 cost but doesn't specify scenarios where 'document_intelligence' is preferred over siblings like 'invoice_extract' (for invoices) or 'alt_text' (for accessibility). No prerequisites, exclusions, or comparative context is provided.

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