scan_table

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

The annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior; the description enhances this by warning that scans consume read capacity proportional to table size regardless of filters and that filters are applied after reads. It also documents the response includes count, scanned_count, and pagination key, adding operational context beyond the safe-read annotation.

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 well-structured with clear sections for usage, non-usage, and return values. Every sentence serves a purpose, and the total length is appropriate for the tool's complexity.

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 (DynamoDB scan, filtering, pagination) and the strong annotations and schema, the description covers all critical aspects: performance implications, when to use alternatives, and response contents. It also aligns with the output schema's mention of format, making it a complete guide.

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 0%, so the description must compensate. It does mention the 'format' parameter and its values (json or markdown), and notes that filter_expression does not reduce read capacity, but it does not explain other parameters like table_name, limit, index_name, exclusive_start_key, or expression attribute placeholders. Since the schema itself provides detailed descriptions for all parameters, the description adds marginal value but not enough to fully cover the low coverage gap, warranting a mid score.

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 defines the tool's function with 'Scan a DynamoDB table to read all items' and distinguishes it from the sibling tool by explicitly referencing query_table as a more efficient alternative. This makes its purpose specific and non-overlapping.

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 explicit 'When to use' and 'When NOT to use' sections, including concrete scenarios such as browsing all items or not knowing the partition key. It also names the alternative tool (query_table) and warns against scanning large tables without filters, giving clear decision criteria.

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