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

Annotations are entirely absent, so the description carries the full burden of behavioral disclosure. It states the tool 'gets results' but does not explain what those results include (e.g., metrics, time range, aggregation), how authentication works, whether it's a read-only operation, or any side effects. For a tool with zero annotation coverage, this is a significant gap.

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?

Two short, efficient sentences. The first states the core purpose and optional scope; the second gives usage context and a differentiation note. No wasted words or repetitive information.

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 that there is no output schema and no annotations, the description does not fully explain what the returned 'results' look like, what time period is covered, or whether there are any prerequisites (like the connection having exactly one ads account if ad_account_id is omitted). While the usage triggers are clear, the missing output and operational details leave an agent guessing about the response shape.

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 100%, so all three parameters (companyId, campaign_id, ad_account_id) have descriptive text in the schema. The tool description adds no extra semantic detail beyond what the schema already provides, so a baseline of 3 is appropriate – the schema handles the parameter meaning.

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 a specific verb ('Get') and resource ('X (Twitter) ads results'), and immediately clarifies the optional scope (account and campaign). It also explicitly distinguishes itself from the sibling get_ads_performance (Meta), making it unambiguous which tool to pick.

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 gives concrete when-to-use triggers: 'when the user asks how their X ads are doing, what they spent, or what it returned.' It also names the alternative tool for Meta ads, but doesn't explicitly say 'use this only for X, not for Meta' beyond the distinction line. The condition is clear enough to route an agent correctly.

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