multi_timeframe_analysis

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

Annotations (readOnlyHint=true, openWorldHint=true, destructiveHint=false) already establish this is a read-only safe operation. The description adds the specific timeframe hierarchy (Weekly → Daily → 4H → 1H → 15m), which is genuine behavioral context, but doesn't discuss rate limits, auth, or return-value behavior. Adheres to the calibration baseline of 3 for annotations covering the safety profile with some but limited additional behavioral context.

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 fairly long, but nearly every sentence earns its place: a one-line summary, anti-hallucination note about the canonical name, sibling routing, a worked example, and parameter docs. The 'canonical name' clarification is slightly unusual and reads as a guardrail, but the overall structure is well-organized and front-loaded with the purpose.

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 low-complexity tool (2 params, no output schema, no nested objects), this is nearly complete: purpose, alternatives, full parameter semantics, and a runnable example. The only gap is no mention of the return shape or behavior, but with no output schema and a self-evident analysis output, this is a minor omission.

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?

With schema description coverage at 0% and no enums, the description carries the full burden — and it excels. It documents concrete symbol formats per market ('BTCUSDT', 'COMI' (EGX), '600519' (SSE)) and enumerates all valid exchange values across crypto and stock venues. This goes far beyond the bare schema and is genuinely load-bearing for correct invocation.

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?

States a specific verb+resource ('Multi-timeframe alignment analysis') and immediately differentiates from siblings: 'for a single-timeframe deep dive use coin_analysis; for TA + sentiment + news use combined_analysis.' An agent can instantly tell this apart from the siblings without opening any schema.

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?

Explicit when-to-use guidance is front and center: 'Use this for cross-timeframe trend alignment on ONE symbol' followed by named alternatives for other cases. Explicitly names two sibling tools with the conditions that select them (single-timeframe vs. combined analysis), leaving nothing to inference.

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