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

With no annotations, the description carries the full burden and does disclose material behavior: data comes from the recorded archive (not live), freshness/dates must be checked elsewhere, and each call costs $0.12 in USDC settled via x402. That pricing/payment and data-provenance detail is genuinely useful. It does not describe latency or error behavior, 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?

Front-loads the core value proposition and the output list in the first two sentences, with cost and data-source caveats after. The inline param string is somewhat redundant with the schema but serves as a quick reference and stays compact, so overall it is efficient.

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 and no annotations, the description compensates by enumerating the returned statistics and flagging the archive source, freshness caveat, and per-call cost. It is complete enough to call correctly, though it omits any note on the shape/format of the 'plain-language read' or failure modes.

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% and both enums are documented in the schema, so the schema already does the heavy lifting. The inline '?symbol=BTC &window=... &basis=...' line merely restates the schema values and adds no new semantics (e.g., default resolution rules), so the baseline 3 applies.

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 resource (kimchi premium) and a precise operation (place the current premium within its own recent distribution), then enumerates the exact outputs: percentile, mean, stdev, z-score, min/max/median, plus a plain-language read. This is clearly distinguishable from the raw-value sibling kimchi_premium and the historical sibling kimchi_premium_history.

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?

States the triggering question ('is this premium unusual right now?') and points to the free coverage endpoint as the place to check dates/freshness, which is real routing guidance. It stops short of explicit when-not-to-use or a direct comparison against kimchi_premium/kimchi_premium_history, so it is strong but not fully prescriptive.

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