coin_analysis

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns 'detailed analysis with all indicators and metrics,' implying a read-only, informative operation and a comprehensive result set. However, it does not mention data sources, freshness, potential failures, or any operational limitations. It is not contradictory, but it is not rich in behavioral detail.

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-organized: a one-sentence purpose, then a clean Args list with examples, and a Returns line. Every section earns its place, with no wasted words. It is appropriately concise for a 3-parameter tool.

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 three parameters, no output schema, and no annotations, the description provides sufficient information for invocation by specifying all parameters and return type at a high level. It could be more complete by detailing what 'all indicators and metrics' includes, but the tool is still usable and understandable in its current form.

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 0% schema description coverage, the description fully compensates by documenting all three parameters with explicit examples and allowed values: symbol examples for crypto and stocks, a list of supported exchanges, and timeframe intervals. It adds meaning beyond the raw schema by providing concrete usage patterns, making correct invocation much easier.

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 states a specific action: 'Get detailed analysis for a specific asset (coin or stock) on specified exchange and timeframe.' It clearly identifies the resource (asset) and scope, distinguishing it from bulk scanners/overviews. However, it does not explicitly distinguish itself from similar sibling tools like combined_analysis or multi_agent_analysis, so it falls short of a perfect 5.

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?

Usage context is implied: use this tool when you need detailed analysis for a single symbol on a particular exchange/timeframe. The presence of analyzer siblings like multi_timeframe_analysis and combined_analysis makes this guidance implicit rather than explicit. There is no 'when not to use' or mention of alternatives, so the agent must infer selection criteria from the examples.

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