npv-irr-calcNet present value and internal rate of return calculation.
| Name | Required | Description | Default |
|---|---|---|---|
| cashFlows | Yes | Cash flow entries (year 0 should be negative for initial investment) | |
| discountRate | No | Discount rate (%) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / properties / cashFlowsAdded value: +{
+ "description": "Cash flow entries (year 0 should be negative for initial investment)",
+ "items": {
+ "properties": {
+ "amount": {
+ "description": "Cash flow amount in JPY (negative for outflow)",
+ "type": "number"
+ },
+ "label": {
+ "default": "",
+ "description": "Label for this cash flow",
+ "type": "string"
+ },
+ "year": {
+ "description": "Year number (0 = initial investment)",
+ "type": "number"
+ }
+ },
+ "required": [
+ "year",
+ "amount"
+ ],
+ "type": "object"
+ },
+ "minItems": 2,
+ "type": "array"
+}Input schema / properties / discountRateAdded value: +{
+ "default": 5,
+ "description": "Discount rate (%)",
+ "maximum": 100,
+ "minimum": 0,
+ "type": "number"
+}Input schema / requiredAdded value: +[
+ "cashFlows"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It does not mention return values, side effects, limitations, or error handling. The behavior is implied but not stated, leaving the agent without expectations for outputs or edge cases.
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 sentence and not overly verbose, but it is under-specified. It lacks actionable verbs and critical details that would make the brevity effective. It is concise in length but not in conveying necessary information.
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?
There is no output schema and no annotations, so the description must explain what the tool returns and how to interpret results. It does neither. While the tool is relatively simple, the description is incomplete for an agent to confidently invoke it correctly.
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 input schema provides 100% description coverage for both parameters (cashFlows and discountRate), so the baseline is 3. The description adds no additional meaning beyond the schema, such as relationships between parameters or interpretation of cash flow signs.
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 identifies the tool as performing NPV and IRR calculations, which is clear but expressed as a noun phrase rather than a specific verb+resource. It does not distinguish this tool from sibling calculators like investment-simulator or bond-yield-calc. The purpose is understandable but lacks operational specificity.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of appropriate use cases, prerequisites, or exclusions. The description simply states the function without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.
Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.
202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.
The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.