list_tables

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

Discloses read-only nature, hidden internal tables without pattern, empty result interpretation, and error conditions (no trace loaded). No annotations were provided, so the description carries full burden and covers it well.

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?

Well-structured, front-loaded with core purpose and read-only flag. Every sentence adds value—usage guidelines, parameter details, error handling—without redundancy.

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?

For a simple tool with one optional parameter and no output schema, the description is complete: purpose, usage, parameter behavior, error conditions, and even retry advice. No gaps.

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?

Adds concrete examples (e.g., chrome_*, slice*) and explains that internal stdlib tables are hidden without pattern, going beyond the schema's generic description. The single parameter is fully covered.

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 it lists tables and views in the loaded trace, and explicitly marks it as read-only. It distinguishes itself from siblings like execute_sql and list_table_structure by identifying it as the schema introspection path.

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?

Provides explicit when-to-use and when-not-to-use guidance, including alternatives like execute_sql with INCLUDE PERFETTO MODULE for known stdlib modules, and warns not to use the tool name inside SQL.

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