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

With no annotations, the description carries the transparency burden. It discloses cost ($0.02 via x402) and describes output content (from/to values, when), but it does not explain payment mechanics, pagination, errors, or auth behavior. Partial but not fully transparent.

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 dense and efficient, front-loading the paid warning and then providing purpose, use guidance, exclusions, and input meaning in a few sentences. No filler or redundant restatement.

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 three parameters, no output schema, and no annotations, so the description needs to carry a lot. It covers purpose, usage, cost, and `since`, but omits crucial invocation details like how to provide the payment header and what `dataset` values are valid. Adequate but incomplete for a paid tool.

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 0%, so the description must compensate. It meaningfully explains `since` as a unix timestamp and says omitting it returns the whole archive. However, `dataset` and `payment_header` are not directly documented beyond their names and the paid hint, leaving a gap.

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 action and scope: field-level diffs across a whole dataset, showing which field moved, from/to values, and when. It distinguishes itself from the price-related siblings and frames its purpose as detecting movement across many keys without pulling every series.

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?

It explicitly says when to use it ('Use it to detect movement across many keys without pulling every series') and when not to ('Do NOT use it for LLM prices specifically'), naming the alternatives anansi_price_changes_recent and anansi_price_changes. This is clear, actionable guidance relative to siblings.

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