korelasyon_raporu

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 the statistical method (Pearson correlation, mean deviation percentage), which adds context beyond the tool name. However, it does not mention data sources, whether the operation is read-only, or any side effects. Given the zero-parameter nature, basic transparency is acceptable but not rich.

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 succinct and front-loaded with the primary action. The two rhetorical questions add value without redundancy. Every sentence contributes to understanding the tool's purpose and output.

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 zero-parameter tool with an output schema, the description is reasonably complete. It covers the purpose, methodology, and typical use cases. However, it lacks explicit usage boundaries and alternative tool references, which prevents a perfect score.

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?

The tool has zero parameters, so the baseline is 4. The description adds meaningful context about what the report contains (correlation and deviation metrics), which is helpful even though there are no parameters to document.

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 computes target price correlation between brokerage houses, using Pearson correlation coefficient and mean deviation percentage. It also provides example questions it answers, which differentiates it from siblings like sapma_analizi_raporu and konsensus_analiz.

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 implies usage by describing the questions it addresses ('Which institutions make close estimates? Which deviates?'), but it provides no explicit when-to-use guidance, exclusions, or comparisons to alternative tools. The sibling tools offer related analyses, but no differentiation is made.

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