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

With no annotations, the description carries the full behavioral burden and delivers almost nothing: it does not say what the tool returns, whether it generates text, whether any auth is needed, or how the 'futures' are represented. The one genuine disclosure is the payment model (x402, 0.01 USDC on Base, pay-per-use), which is useful cost context but does not cover the operation itself.

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?

Two short segments, so it is not bloated, but the first segment is prefixed with 'Auto-created from research:' meta filler and the pricing bracket is bolted on. The core purpose is front-loaded, which is the main structural virtue.

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 tool with no annotations, no output schema, and an opaque 'input' string parameter, the description omits everything an agent needs to call it correctly: input expectations, output form, and differentiation from the futures-* family. Only the payment terms are supplied.

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?

One required parameter with 100% schema coverage, so the schema is nominally complete — but its description is the meaningless placeholder 'entrada', and the tool description adds nothing about what input should contain (a decision, a prompt, a context?). Per the high-coverage baseline this is a 3, though the schema text is uninformative enough that the description should have compensated and does not.

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 states an abstract purpose (help individuals consider a wider range of futures by countering over-reliance on AI recommendations), which is more than a restatement of the name, but it is conceptual rather than operational. It gives no basis to distinguish this tool from the many near-identical siblings (futures-expander, future-widener, futures-spectrum-expander, horizon-expander, option-expander). The 'Auto-created from research:' prefix is provenance noise, not purpose.

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?

There is no statement of when to use this tool, no preconditions, and no alternatives named — despite a sibling cluster of at least eight futures/horizon/option expansion tools that an agent must choose between. The only cue is the vague 'countering over-reliance on AI-generated recommendations', which does not map to a selection condition.

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