Validate records against schema

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, indicating safe, non-destructive operation. The description complements this by specifying the exact return format ({'valid', 'total', 'valid_count', 'errors'}), which adds valuable behavioral context beyond annotations. No contradiction.

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 concise with two short paragraphs and a structured 'Args' section. Every sentence adds value: purpose, usage guidance, return type, and parameter summaries. No redundant or filler 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?

Despite having no output schema, the description explicitly provides the return format, making it complete. It also references sibling tools (get_input_schema, get_required_fields) for further context. Given the tool's simplicity (2 required parameters), this is fully sufficient for an AI agent to understand and invoke correctly.

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 both parameters in detail. The description provides a brief summary of each parameter (e.g., 'A supported ISO 20022 acmt message type') but adds little beyond what the schema includes. It mentions links to related tools, which is helpful, but not enough to elevate above the baseline of 3.

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 ('Validate') and resource ('flat account records against a message type's input JSON Schema'). It clearly distinguishes the tool from siblings like validate_identifier and generate_message by stating what it checks (JSON-Schema shape) and its intended use before generate_message.

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 explicitly states when to use the tool ('before generate_message') and when not to ('to validate a single financial identifier... use validate_identifier'). It also clarifies that it only checks JSON-Schema shape, setting proper expectations.

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