aggregate_records

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

With no annotations, the description fully bears the burden. It discloses that exact Decimal arithmetic is used to avoid float drift, which is critical for currency values. No mention of auth or rate limits, but the arithmetic behavior is well covered.

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 sentences that efficiently cover purpose, operations, usage directive, and behavioral detail. No redundant information.

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?

No output schema and no mention of return format. While the operation is simple, the description could be more complete by indicating what the tool returns (e.g., a decimal number). Missing error or validation context.

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 baseline is 3. The description adds examples like 'InvoiceAmount' but does not significantly extend beyond the schema's parameter descriptions.

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?

Clearly states the verb 'Compute' and the resource 'aggregate' with all supported operations. Explicitly distinguishes from other arithmetic tools by saying 'Use this for ANY arithmetic on Oracle Fusion data — do NOT compute sums, averages, or counts yourself.'

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 strong directive to use this tool for all arithmetic, and warns against manual computation. However, it does not differentiate from sibling tools like sumif_records or group_by_aggregate, which could have distinct use cases.

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