multi_timeframe_analysis

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful behavioral context: the exact timeframe chain, that it operates on ONE symbol only, the canonical name warning (avoiding the incorrect 'get_' variant), and the supported exchanges/markets. It does not describe output format or pagination, but the safety profile is well covered by annotations, and the added details are valuable.

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 longer than average but every sentence serves a purpose: purpose, sibling alternatives, a working example, and parameter semantics. It is well-structured with an 'Args' section, avoids filler, and front-loads the key takeaway. No redundant text is present.

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 tool with no output schema and no return value documentation, the description adequately covers what the tool does, when to use it, and how to call it with valid parameters. It could be enhanced by summarizing the expected output shape (e.g., alignment signals per timeframe), but the core selection and invocation context is complete enough for an agent to use correctly.

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 descriptions cover 0% of the parameters, but the description fully compensates by explaining `symbol` with concrete crypto and stock examples (e.g., 'BTCUSDT', 'COMI', '600519') and `exchange` with explicit lists for both crypto and stock exchanges. This provides far more meaning than the raw schema, making the invocation precise and reducing guesswork.

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 clearly states the tool performs multi-timeframe alignment analysis with specific timeframes (Weekly to 15m). It explicitly distinguishes this from `coin_analysis` and `combined_analysis`, making the tool's purpose unambiguous even among many siblings.

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 description gives direct usage guidance: use for cross-timeframe trend alignment on one symbol, with explicit alternatives for single-timeframe deep dive (`coin_analysis`) and combined TA+sentiment+news (`combined_analysis`). It also provides a concrete calling example, clearly telling the agent when and how to invoke.

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