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

Annotations are absent, so the description carries the full burden. It discloses that the check is 'live from Meta' (real-time) and that each check returns pass/fail, which sets expectations for output. It also implies a read-only diagnostic operation by describing 'health checks' and 'diagnose'—no mutation is suggested. However, it does not explicitly state that no data is modified, and it doesn't mention potential failure modes or rate limits. Given the absence of annotations, this is a strong but not perfect disclosure.

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 slightly long but every sentence earns its place: it states the purpose, lists specific checks, provides usage context, names a complementary tool, and gives parameter sourcing guidance. The most critical information (what it does and when to use) is front-loaded. It avoids fluff and is well-organized, though it could be tightened by removing the trailing 'and more' clause.

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 there is no output schema, the description explains that each check returns pass/fail, which is sufficient for an agent to understand the result shape. It covers the source of the pixel_id, the diagnostic purpose, and the complementary sibling. It does not mention error cases or permissions, but these are likely handled generically across tools. The description is complete enough for an agent to select and invoke this tool correctly in most scenarios.

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 100% with clear descriptions for both parameters (pixel_id and ad_account_id). The description adds extra value beyond the schema by telling the agent where to source the pixel_id ('Get it from adsap_list_meta_assets') and explaining that ad_account_id 'scopes the request and anchors the Meta budget check.' This enhances the agent's understanding without redundancy.

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?

Description uses a specific verb ('Get'), names the exact resource (Dynamic/Advantage+ catalog-ads readiness health checks for a Meta pixel), and enumerates concrete checks (event-source match rate, missing DPA parameters, iOS 14.5+ AEM setup). It clearly distinguishes itself from siblings by naming its complementary tool (adsap_get_pixel_stats) and explicitly stating it's a diagnostic for catalog/Advantage+ ads, unlike adsap_get_pixel_details or adsap_get_pixel_stats.

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 guidance: 'Use to diagnose why catalog/Advantage+ ads under-deliver or why events aren't matching products, before launching.' It also names the sibling that complements it (adsap_get_pixel_stats for event volume), and instructs how to obtain the pixel_id (from adsap_list_meta_assets with asset_type:"pixels"). This leaves no ambiguity about when and how to invoke it.

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