Read a transaction's business data

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

Annotations already mark the tool as read-only and idempotent, so the description adds high-value behavior: large values are listed under 'omitted' rather than returned, and users can request them by name. It also clarifies that values are as saved by the mock config, which is non-obvious and useful.

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 three focused sentences: what the data is, when to read it, and how omitted values behave. Every sentence adds unique value with no filler or repetition.

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 presence of an output schema and comprehensive annotations, the description provides the essential behavioral context: it explains the data source, the likely use case, and a notable limitation (omitted large values). This is sufficient for an agent to select and invoke the tool 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?

The input schema covers all parameters with descriptions, so the baseline is 3. The description adds meaningful semantics by explaining that large values are omitted and can be retrieved by using the 'keys' parameter ('ask for one by name'), and by giving examples of value types. This goes beyond the schema but does not fully carry parameter documentation.

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 identifies the tool as reading a transaction's accumulated business data, with concrete examples (provider IDs, order IDs, form submission IDs). It also distinguishes this from related tools like record_get_payload by noting this data is what the next step's payload is generated from.

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 this tool: 'read it when a step reports missing requirements.' It also explains the relationship to payload generation, providing useful context. It does not explicitly name alternatives or state when not to use it, but the guidance is clear enough.

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