savings_goalThe monthly saving needed to hit a target by a deadline. Given a target amount, what you already have, a time horizon, and an expected return, computes the required monthly contribution — and shows what waiting a year would cost you.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | Target amount | |
| rate | No | Annual return (%) Use a conservative rate for short horizons. | |
| years | No | Years to goal (yr) | |
| current | No | Already saved |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating no side effects. The description adds that the tool 'computes the required monthly contribution — and shows what waiting a year would cost you', which reveals key output features without contradictions.
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, informative sentence that efficiently conveys purpose and a notable output feature. It is concise without sacrificing clarity, though could be broken into two sentences for readability.
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 full schema coverage and no output schema, the description adequately explains the computation and highlights the 'cost of waiting' feature. It provides sufficient context for an agent to understand the tool's function, but lacks return format details.
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 coverage is 100%, so the description adds minimal new semantics. The description paraphrases schema fields (target amount, already saved, time horizon, expected return) but does not provide additional constraints or examples.
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's purpose: computing the required monthly saving to reach a financial goal given target, current savings, time horizon, and expected return. It specifically distinguishes from common sibling tools like 'loan_payment' or 'mortgage' which serve different calculations.
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 for financial goal planning but does not explicitly state when to use this tool versus alternatives such as 'fire_number' or 'compound_growth'. No direct comparison or exclusion criteria are provided.
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.
Each tool targets a distinct niche (e.g., specific country tax rules, loan types, or legal calculations), with detailed descriptions that clarify boundaries. However, the large number of tools (66) could cause some confusion for an agent trying to select the right one for a general query, especially when multiple tools relate to the same country.
Tool names follow a mostly predictable pattern: lowercase words separated by underscores, often starting with a country name (e.g., 'uk_stamp_duty_sdlt') or a topic (e.g., 'compound_growth'). There are minor deviations, such as abbreviations ('npv_irr', 'sip') and varying use of verbs, but overall the naming is clear and consistent.
At 66 tools, the server is unusually large and covers an extensive range of financial and legal calculators. While each tool justifies its existence, the count exceeds the typical well-scoped range (3–15), making the server feel bloated. A more modular design might improve coherence.
The tool set covers a wide array of domains: personal income taxes, property taxes, loan calculations, investment returns, and specific country regulations. Minor gaps exist (e.g., missing tools for corporate taxes, general retirement planning, or insurance), but the overall coverage is thorough and addresses many niche scenarios that general AI handles poorly.