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

With no annotations, the description carries the full burden and does well: it discloses that nothing is stored, that input is capped at 1500 chars, that empty/oversized input returns 400 before payment (not charged), and that invocation costs $0.002 USDC via x402 on Base or Solana. It omits rate limits and other error behaviors, so it is not exhaustive.

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?

Telegraphic but tightly organized: trigger, input, output, retention, example, price — each sentence earns its place and the most decision-relevant facts (what it does, cost, limits) come first. No filler wording.

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?

With no output schema, the description compensates by listing the return fields (translatedText, source, target, model). For a 3-param tool it covers limits, retention, payment, and detection rules; only the valid target-code set is missing.

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 already 100%, so baseline is 3; the description adds invocation-level meaning by showing a concrete GET query-string example and clarifying that Latin script defaults to English while other scripts auto-detect. It never enumerates the valid target language codes, which is the one meaningful semantic 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?

Opens with a specific verb+resource ('translate text') and scopes it to concrete agent artifacts (replies, documents, transcripts). The title further pins down language coverage and script-based auto-detection, which cleanly separates it from siblings like ai_transcribe or ai_embed.

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?

Gives a clear trigger condition ('Use when an agent must translate text') and notes the case where the source must be supplied explicitly (Latin-script languages other than English). It does not name alternatives or exclusions, so it stops short of full routing guidance.

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