Rachunek opłacalności wcześniejszego wykupu obligacji.
| Name | Required | Description | Default |
|---|---|---|---|
| series | Yes | Catalyst series ticker, e.g. BST0930. | |
| holdingsValuePLN | Yes | User's bond position value at par: number of bonds × faceValue. | |
| redemptionPricePct | No | Redemption price as percent of par. Defaults to lastPricePct, then 100. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already signals a safe read operation, and the description adds no behavioral context beyond that: no mention of what inputs drive the calculation, what the result represents, or any caveats about defaults. The description contributes nothing beyond the annotation.
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 a single short phrase, but this is under-specification rather than conciseness. There is no front-loaded verb sentence and no structured content that earns its place.
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?
With no output schema, the description should at least indicate what the calculation returns, but it says nothing about the result or how to interpret profitability. For a 3-parameter financial calculation tool, this is incomplete.
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 description coverage is 100% with strong inline explanations (par-value formula, default chain for redemptionPricePct), so the schema carries the full meaning and the baseline of 3 applies. The description itself adds no parameter-level value.
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 Polish description ('Calculation of profitability of early redemption of bonds') identifies the resource (bonds) and the action (profitability calculation), but it is a noun phrase that mostly restates the tool name. It never explains what 'profitability' is measured against, and the non-English phrasing reduces clarity for an AI agent.
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 no guidance on when to use this tool, what prerequisites exist (e.g., knowing the bond series and holdings value), or when a sibling tool would be more appropriate. A single terse phrase provides no decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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