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

The description discloses key behavioral side effects: billing the advertiser, creating a ledger entry, and decrementing the media buy budget. It also specifies the output format (Event ID, charged amount, etc.). These go beyond the annotation flags (readOnlyHint=false, destructiveHint=false) and provide useful context about the financial impact. However, it could be more explicit about irreversibility or idempotency, though the annotations partially cover this.

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 well-structured with clear sections: tool_description, when_to_use, combination_hints, and output_format. Each section is concise and directly useful, with no redundant or filler content. The main purpose is front-loaded in the first sentence, making it easy for an agent to quickly grasp the tool's function.

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?

The tool has 6 parameters, nested objects, and no output schema, so the description needs to cover return values and usage context. It does this by providing an output format (Event ID, charged amount, etc.) and workflow hints. It also mentions the ledger entry and budget decrement side effects. However, it does not explain what happens if `brand_content_id` is omitted or edge cases like partial data delivery, which could be useful but are not critical given the schema coverage.

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?

The input schema descriptions cover 100% of the parameters, so the baseline is 3. The description adds value by explaining how `snippet_type` maps to billing tiers (basic: 10¢, etc.), which clarifies the semantic meaning of that parameter beyond its enum values. It also hints at the purpose of `brand_content_id` (for analytics) indirectly through the billing context, though the schema already describes that. Overall, it enhances parameter understanding.

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 the tool's function: 'Track delivery of an enriched snippet and bill the advertiser. Creates a ledger entry and decrements the media buy budget.' This uses a specific verb (track/bill) and resource (enriched snippet, media buy), distinguishing it from siblings like activate or get_campaign_report which serve different purposes.

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 `when_to_use` section explicitly states when to use the tool ('When an agent delivers enriched content from a media buy') and provides tier-based billing details. The `combination_hints` further clarify workflow with activate and get_campaign_report. However, it does not explicitly state when NOT to use it or name alternative tools for related scenarios, so it misses the full 'when-not/alternatives' criteria.

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