compound_interest_calculatorFuture balance and interest earned: A = P(1 + r/n)^(nt). Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| years | Yes | Number of years | |
| locale | No | Language for the source_url link (default en) | |
| principal | Yes | Starting amount | |
| annual_rate | Yes | Annual rate, percent | |
| compounds_per_year | No | Compounding periods per year (default 12) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions the formula and 'Runs on smart-tools.xyz' but does not disclose whether the result is a single value or two outputs, rounding behavior, or handling of invalid/edge-case inputs.
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 short and front-loaded with the core purpose and formula. However, the second sentence 'Runs on smart-tools.xyz' is filler that does not help an agent select or invoke the tool, preventing a perfect score.
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?
The description lacks details about the output structure (does it return both future balance and interest earned?), locale parameter effects, parameter constraints (e.g., positive values), or any error handling. For a no-output-schema tool, this is a significant gap.
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%, so parameters are already well-documented. The formula adds context relating principal, rate, and compounding periods, but this is marginal beyond the schema's own descriptions.
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 future balance and interest earned, with an explicit formula. This distinguishes it from sibling calculator tools and uniquely identifies its function.
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 for when to use this tool versus alternative calculators, nor are there any exclusions or prerequisites. The intended use is only implied by the name and formula.
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.
Most tools are clearly distinct, but there are notable overlaps. 'hash_generator' and 'file_hash' effectively do the same thing (SHA hashing of text), and several CSV/TSV converters (csv_to_json, csv_to_sql, table_to_csv, markdown_table) have similar input handling, though outputs differ. The sheer number of converters is clear, but these near-duplicates create some ambiguity.
Names follow a generally consistent pattern: lowercase with underscores, often ending in 'converter', 'calculator', or 'generator'. A few names like 'base64', 'lorem_ipsum', and 'transliteration' deviate from the suffix pattern, but the naming style is uniform and predictable overall.
With 73 tools, this server is far over the typical well-scoped range. While the broad utility-toolkit purpose might justify a larger set, 73 is unwieldy and pushes well into 'too many' territory, making it harder for an agent to select the right tool efficiently.
The server covers a remarkably wide range of common utilities: unit conversions, calculators, text transformations, development helpers (JSON, regex, JWT, subnet), and generators. Minor gaps exist (e.g., currency converter, time zone converter), but for a general-purpose toolkit, it is largely comprehensive.