run_tracking_diagnostic

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

No annotations exist, so the description must fully describe behavior. It states it runs a diagnostic (likely read-only) and returns results, but does not disclose potential side effects, authentication requirements, rate limits, or if it modifies any data. This is a gap for safe invocation.

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 concise with two short paragraphs plus an 'Args' section. The main action is front-loaded, and every sentence contributes value 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?

Given 2 parameters and no output schema, the description covers the tool's purpose, inputs, and output (health classification with issues and fixes). It is complete for a diagnostic tool, though more detail on return format could improve usability.

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?

With 0% schema description coverage, the description adds meaning: 'account_id' gets an example format ('act_123456789'), and 'archetype' is explained as 'account archetype for requirement matching'. This goes beyond the minimal schema titles and types.

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 runs a comprehensive tracking diagnostic for an ad account, detailing specific checks (pixels, event coverage, parameters, Meta flags) and outputs (health classification with issues). It distinguishes itself from sibling tools like 'diagnose_pixel_on_site' which focuses on pixel-on-site issues.

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 provides clear context on what the tool does but does not offer explicit guidance on when to use it versus alternatives like 'diagnose_pixel_on_site' or 'check_token_status'. Usage context is implied but not articulated.

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