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

With no annotations, the description carries the burden and does disclose two genuinely useful traits: the data source (live candles) and a per-call cost with the x402 payment model, which the agent must plan for. It stops short of describing the return shape, failure modes (insufficient history), or rate limits, so it is good but not complete.

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 sentences, front-loaded with the indicator inventory and followed by the cost model. No filler, and every clause (indicator set, live-candle source, cost) carries information the caller needs.

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 no-output-schema tool, the description does convey the return concept (one trend/momentum signal derived from the indicators). It would be stronger if it sketched the response fields or noted the warm-up requirement for long moving averages.

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 100%, so pair, interval and paymentProof are already fully documented, including the omit-on-first-call 402 handshake. The description adds no parameter-level meaning beyond the schema, making the baseline 3 correct.

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?

Names a specific verb (computes) plus an enumerated set of indicators and the derived trend/momentum signal, which clearly separates it from raw-data siblings like ohlcv and crypto_price. An agent can tell exactly what it will get without opening the schema.

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?

Usage is implied by the indicator list — you call it when you want computed technicals rather than raw candles — but the description never states when to prefer it over ohlcv or crypto_price, nor any exclusions or prerequisite (e.g. sufficient candle history for SMA200).

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