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

With no annotations, the description carries the full burden and does deliver key operational context: it is a paid vendor asset at $0.02 USDC per call (or prepaid credits), and payment headers (X-Payment / X-Payment-Tx / Authorization: Bearer fg_...) must go in the MCP request headers, not in parameters. It does not cover failure behavior when payment is missing, data source/freshness, or rate limits.

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 purpose is front-loaded, but the text is bloated by full CN/EN duplication, and the argument list is repeated twice plus a dangling '参数同左' reference. The full-width pipe separators and mixed-language blocks make it slower to parse than necessary.

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 4-parameter tool with no annotations and no output schema, the description does cover the returned metrics and the payment mechanism, which is the most critical missing piece an agent would otherwise lack. It still leaves parameter formats and the quick/full selection criteria unaddressed.

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 0%, so the description must compensate, but it only re-lists the four names (symbols, interval, days, base) without formats, enum values, or defaults. The only implicit meaning added is that 'base' is the benchmark for the beta metric ('相对基准 beta'), and that days/interval scope the lookback window — thin compensation for a complete documentation 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?

The description names the concrete output set — pairwise correlations, return, volatility, drawdown, beta, latest price — so an agent knows exactly what the tool returns, and 'full' versus the sibling corr_now implies a comprehensive vs quick variant. However it never names corr_now explicitly, and the cross-reference '参数同左' ('params same as the left/tool above') points at nothing in a standalone tool listing.

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 framing question 'how correlated are these tokens' gives implied usage context for portfolio/correlation analysis. There is no explicit when-not, no prerequisite statement, and no named alternative (correlation.corr_now) to route the agent between the quick and full versions.

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