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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, and the description adds valuable behavioral context beyond that: data refresh cadence ('refreshed every 6 hours'), lookback window ('60-day lookback'), and a disclaimer ('Information only, not investment advice'). No contradictions with annotations.

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 description is well-structured with labeled sections (Purpose, Triggers, When to call, Prerequisites, Next steps, Caveats, Args, Disclaimer) and front-loads the core purpose. Each section adds useful information without redundancy; the length is justified by the rich guidance.

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?

Given the output schema exists, the description doesn't need to explain return values. It covers prerequisites, usage context, refresh/lookback caveats, and parameter semantics, making it complete for an agent to invoke correctly. Even with 2 simple parameters, the description provides enough context for a reliable call.

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?

Input schema has no descriptions (0% coverage), so the description compensates by listing valid values for market_id ('coin / kr_stock / us_stock') and explaining top_k as 'Number of top pairs to return'. This adds meaning beyond the bare schema types and defaults, though top_k could be more explicit about what 'top' means (e.g., strongest correlations).

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?

Description clearly states the tool's function: 'Intra-market ETF / group correlation matrix and auto-cluster output' with a specific verb ('Quantifies structural co-movement') and concrete examples (ARKK <-> QQQ). It distinguishes itself from siblings like get_cross_market_correlation by explicitly being intra-market, and from get_symbol_peer_links_tool by focusing on group/sector-level correlations rather than per-symbol lead-lag.

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?

Provides explicit 'When to call' guidance ('portfolio diversification or sector concentration audits'), casual trigger examples in multiple languages, prerequisites ('none'), and a named next step (get_symbol_peer_links_tool). This clearly tells an agent when to use this tool versus alternatives.

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