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

With no annotations, the description carries the full transparency burden, and it delivers: it states that forecasts were written before the window opened, settled from the exchange public feed, and that raw rows are returned for independent recomputation. It also explicitly disclaims being a backtest, which is a meaningful behavioral 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 well front-loaded with 'FREE: the live track record of this miner' and then gives concrete detail about provenance and returned metrics. It is slightly wordy with the repeated 'Free' at the end and the rhetorical backtest contrast, but those sentences still add differentiating value.

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?

There is no output schema, so the description must communicate what the agent will get back. It lists the key metrics, raw rows, and the settlement methodology, which is enough for an agent to know what this call does and what to expect. It does not describe the exact output envelope or possible error cases, but for a read-only data retrieval tool this is a minor gap.

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 already documents both parameters fully: rows specifies how many raw rows to return, max 500, default 50, and symbol restricts to one symbol. The description adds no parameter-specific semantics beyond reinforcing that raw rows are part of the response, so the schema does the heavy lifting.

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 identifies the resource: the live track record of this miner, and states exactly what it returns: settled count, base rate, Brier skill, coverage, calibration error, and a reliability curve. It also distinguishes itself from a backtest, which separates it from related forecast/analysis tools.

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 clear context that this is a free, verifiable, live track record rather than a self-computed backtest. It does not name a specific alternative tool, but it does make the when-to-use boundary explicit: anyone who wants an auditable, non-backtest performance record for this miner.

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