df_bulk_write_facts

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

Annotations already convey that this is a non-read-only, non-idempotent, non-destructive operation, and the description adds little beyond that. It does not disclose partial-failure behavior, atomicity, validation, or any side effects beyond the obvious write. The idempotency_key parameter in the schema covers replay behavior, but the description itself offers no additional behavioral context.

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 only two sentences and avoids extraneous detail, making it easy to scan. The opening 'WRITES TO DATAFORGE' is somewhat redundant given the tool name and the uppercase styling, but the second sentence economically states the core behavior.

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?

There is no output schema, so the description should compensate by explaining expected responses, error modes, or partial-failure semantics, but it does not. For a complex bulk mutation tool, this leaves the agent without enough context to handle results or failures 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?

Top-level schema coverage is 75%, and nested fact properties are individually described, so the schema carries most parameter semantics. The description adds only that multiple facts can be passed at once, which is already visible from the 'facts' array type and minItems. No extra meaning is added for project_id, version_id, or idempotency_key beyond what their descriptions already state.

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 states a clear action ('Create and/or update') on a specific resource ('facts') with an explicit scope ('many facts in one call'). This distinguishes it from the sibling df_write_fact (single fact) and other bulk operations on different entities like measures or dimensions.

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 phrase 'many facts in one call' implies the tool is for batch operations, but it never names alternatives such as df_write_fact for a single fact or explains when not to use it. There is no explicit when/when-not guidance or mention of related bulk-write siblings like df_bulk_write_measures.

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