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

Annotations only provide readOnlyHint=false, destructiveHint=false, etc., which are minimal. The description goes far beyond by detailing side effects: it moves no money, calls no external service, never deletes or overwrites, and the response reports persistence status. It also discloses that conversions are recorded as 'reported' and never affect rank, and that gvt tokens are cryptographically verified. This is exemplary behavioral disclosure with no contradiction to annotations.

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 a single dense paragraph but is efficiently written. The core action is front-loaded, and every sentence adds relevant context (safety, optional parameters, verification). It could be split into bullet points for easier scanning, but it contains no filler or repetition. It is more verbose than necessary but earns its length.

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 mutation tool with no output schema, the description covers all essential aspects: what the tool does, its side effects, how to attribute correctly, and what the response conveys. It explains the demo-stub nature and the distinction between reported vs. rank input. Given the moderate complexity and available schema descriptions, nothing critical is missing for correct invocation.

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 schema already documents most parameters with descriptions (gvt, offer_code, agent_platform, conversation_id, order_value_usd). The description adds meaningful context for the optional parameters: gvt is verified against the Ed25519 key and provides provenance, and offer_code attributes the conversion to a captured deal. It does not add new semantics for required parameters like brand_id, but it compensates well for the optional ones, exceeding the schema's coverage.

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 begins with a precise action ('Appends one attributed-transaction event to a log'), identifies the resource (a log) and the domain (attributed conversions), and further clarifies it is a demo stub of a pay-on-real-acquisition loop. This clearly distinguishes it from sibling read/get tools like get_ledger or match_intent, making the purpose unmistakable.

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 implies when to use the tool (to report a real, attributed conversion) but does not explicitly contrast it with alternatives. It states payment flows only on real transactions and never on impressions or rank, which guides correct usage, but it never says 'use this when...' or names sibling alternatives. The context is clear from the sibling list, but the guidance is implicit rather than explicit.

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