df_get_facts

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, which cover the safety profile. The description adds no behavioral context beyond that—no mention of caching behavior, language handling, or return format. It contributes nothing beyond the structured annotations.

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 concise sentence with no filler or redundancy. It is appropriately front-loaded and efficient, though it is arguably too terse to be maximally useful. Still, it earns credit for brevity and clarity.

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 a 4-parameter tool, a 50% schema coverage gap, and no output schema, the description is far from complete. It does not explain what 'facts' entails, how the optional parameters behave, or what the response looks like. An agent would need to inspect the schema or guess to call it 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?

Schema coverage is 50%: project_id and version_id have descriptions, but language and use_cache do not. The description mentions no parameters at all, so it fails to compensate for the uncovered ones. The agent is left guessing about the meaning and impact of language and use_cache.

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 verb ('Get') and resource ('all facts of a project version'), making the core purpose unambiguous. However, it does not differentiate from sibling get-style tools (e.g., df_get_fact_table, df_get_dimensions), so an agent must rely on naming alone to distinguish them.

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?

There is no guidance on when to use this tool versus alternatives, no mention of prerequisites or context, and no exclusions. The description is a bare statement of function with no direction for the agent.

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