df_list_fact_tables

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

Annotations already declare the operation as read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds useful context that the result includes element counts, but it does not disclose behavior around pagination, caching, language, or response format. This is acceptable but not rich.

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 a single clear sentence with no wasted words and front-loads the core purpose. It is appropriately concise for a simple list operation, though the brevity contributes to missing parameter-level guidance.

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 pagination, language, and cache parameters, and the absence of an output schema, the description should provide more context about return structure, pagination behavior, and parameter effects. It only states that fact tables are listed with counts, which is incomplete for an agent trying to call the tool correctly with all optional parameters.

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 only 33%; only project_id and version_id have descriptions in the schema. The description adds no meaning for page, page_size, language, or use_cache, and it only restates the project/version scoping already implied by the required parameters. With low schema coverage, the description should compensate but does not.

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 states a specific action ('List'), a specific resource ('fact tables'), a scope ('of a project version'), and an output detail ('with element counts'). This distinguishes it from siblings like df_get_fact_table and df_write_fact_table without needing to open schemas.

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 gives a clear scope ('of a project version') that implies when to use it, but it never explicitly says when to choose this over a sibling like df_get_fact_table or df_list_data_marts. There is no exclusion or alternative guidance, leaving some usage inference to the agent.

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