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

With no annotations, the description must disclose side effects and behavioral traits. It mentions 'create or reuse a private dataset,' indicating a potential write operation, and 'return a compact forecast card,' but it does not clarify persistence, cost, or other side effects. The token_id parameter in the schema describes payment, but the description itself omits this, leaving the agent under-informed about behavioral consequences.

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 compact—two sentences with no filler. It front-loads the main action and then adds the use case. While it could be longer given the tool's complexity, the brevity is not wasteful.

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 22-parameter tool with no output schema and no annotations, this two-sentence description is severely incomplete. It lacks guidance on inputs, output structure, and edge cases like tokenized payment. It covers the high-level purpose but leaves the agent with many unanswered questions.

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 only 5%, so the description should compensate by explaining parameter semantics. It vaguely alludes to 'candle data' and 'dataset' but does not map to specific fields like rows, datasetId, or interval. No direction is given on which parameters are needed for creation vs. reuse.

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: 'Create or reuse a private dataset, import candle data, and return a compact forecast card in one call.' It identifies a specific multi-step workflow and even names the intended use case. However, it does not explicitly contrast with sibling tools like find_market_analogs, so it earns a 4 rather than a 5.

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 provides a clear usage context: 'Ideal for users who want to upload exchange or ML-derived candle history, inspect analogues immediately, and only then decide whether to run RLXBT.' This tells when to use the tool (combined upload-inspect-forecast workflow). It does not explicitly state exclusions or name alternatives, so a 4 is appropriate.

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