find_code_assets_using_table

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

Annotations already cover the read-only/idempotent/non-destructive safety profile, but the description adds genuinely non-obvious behavior: it opens every candidate asset and consumes Dataform read quota, and its output is a bounded sample rather than proof of completeness. The only missing piece is any note about result shape beyond the coverage caveat, so a 4 rather than 5.

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 opening line is front-loaded and the Args block is efficient, but the middle paragraph is somewhat convoluted ('Unlike the other tools here this one opens every asset it considers...') and the parenthetical coverage caveat runs long. Every sentence still earns its place, just not with maximal crispness.

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?

With no output schema, the description still tells the agent that results report coverage of the project scanned and must not be read as proof of non-usage, which is the key interpretive context. All four parameters are documented and the quota cost of calling it is disclosed. Nothing material is missing.

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 0%, so the description carries the whole burden and does: it explains table-name matching semantics (bare name = any qualification, qualified name narrows), the environment selector, the asset_type filter enumerating 'sql', 'notebook', 'data_canvas' (values absent from the schema), and max_assets as a ceiling on bodies read.

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?

States a specific verb and resource ('Find which Colab notebooks and saved queries reference a table') and immediately distinguishes itself from siblings via the write-vs-read contrast with ``list_scheduled_queries``. An agent can pick this tool over list_code_assets or get_code_asset without opening any schema.

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?

Explicitly frames the use case ('The question to ask before changing or dropping a table') and names the complementary tool with its role ('list_scheduled_queries says what writes it, this says who reads it'). No inference needed about when this tool is the right choice.

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