Explain the payout mechanics of a ROSCA with a concrete example: fixed contribution each cycle, one member receives the pot per cycle, rotates until everyone has had a turn, interest-free. No personal data.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool explains with an example, is interest-free, and does not use personal data. For a read-only explanatory tool, this is clear and sufficient.
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 concise sentence that front-loads the core purpose with no unnecessary words. Every part adds value.
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 tool has no parameters, no output schema, and low complexity, the description fully covers what the agent needs to know to 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?
There are no parameters, so the description does not need to add meaning beyond the schema. Schema description coverage is 100%, meeting baseline expectations.
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 explains payout mechanics of a ROSCA with a concrete example, using a verb and specific resource. It distinguishes from sibling tools like 'what_is_a_rosca' and 'rosca_payout' by focusing on the process and example.
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 understanding payout mechanics with an example but does not explicitly state when to use this tool versus alternatives such as 'what_is_a_rosca' or 'rosca_payout'. No when-not or explicit context 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 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.