Compare a savings circle (ROSCA) against a bank loan for the same goal. Inputs: goal amount (>=100), months (2-60), loan APR percent (0-60). Returns the loan's monthly payment, total repaid, and interest cost, versus the ROSCA's zero interest, plus the honest tradeoff (a loan pays out now; a ROSCA pays on your turn). Faithful port of the wiremi.ca ROSCA-vs-loan tool. No personal data.
| Name | Required | Description | Default |
|---|---|---|---|
| apr | Yes | ||
| goal | Yes | ||
| months | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It describes inputs, outputs, and the tradeoff, and notes that no personal data is used. However, it does not explicitly state that the tool is read-only or mention any assumptions or limitations.
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 concise, with two sentences covering purpose, inputs, and outputs. It is front-loaded and contains no redundant 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?
Given the complexity (3 required params, no output schema), the description adequately explains inputs, output items, and the tradeoff, making it complete for an agent to use 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?
Schema coverage is 0%, so the description fully explains the three parameters: goal (>=100), months (2-60), and APR (0-60), adding constraints and meaning beyond the schema's type and name.
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 compares a ROSCA against a bank loan for the same goal, using specific verb and resources. It distinguishes from sibling tools that explain or ask about ROSCAs, as this is the only comparison tool.
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 when to use this tool (when comparing a ROSCA to a loan) but does not explicitly state when not to use it or provide alternatives. Given the clear purpose, an agent can infer usage 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.
Each tool targets a distinct aspect of ROSCAs or Wiremi, with minimal overlap. The catch-all 'ask_wiremi' is explicitly designed for queries that don't fit other tools, preventing ambiguity.
All tool names follow snake_case and a descriptive style, often starting with 'what', 'how', or 'rosca_'. The pattern is uniform and predictable.
10 tools is an appropriate count for the server's educational/marketing purpose, covering definitions, mechanics, comparisons, calculations, and company info without being excessive or insufficient.
The tool set comprehensively covers the domain of ROSCAs and Wiremi: from basic concepts, mechanics, and comparisons to research and operational details. No obvious gaps for an educational marketing server.