coin_analysis

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

No annotations are provided, so the description carries full burden. It does not disclose behavioral traits such as whether the tool is read-only, requires authentication, has rate limits, or any side effects. It only states what it returns, lacking transparency about system interactions.

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 sections (Args, Returns) and an example. It is longer than necessary but each sentence adds value. Minor redundancy: "Detailed analysis with all indicators and metrics" could be more specific.

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 3 parameters, no output schema, and a large sibling set, the description covers all essential aspects: purpose, parameters, usage guidelines, and error behavior. Missing details on return structure or pagination, but adequate for basic usage.

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 coverage is 0%, yet the description adds comprehensive meaning to all parameters: explains symbol format (crypto vs stock examples), exchange list with error handling hint, timeframe options. This greatly enriches the bare schema.

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 it provides detailed analysis for a specific asset on an exchange and timeframe. It distinguishes itself from siblings like multi_timeframe_analysis and combined_analysis, making the purpose unmistakable.

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?

Explicitly tells when to use this tool versus alternatives: use multi_timeframe_analysis for trend alignment across timeframes, combined_analysis for news sentiment. Also provides an example call and detailed parameter guidance.

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