continuum_create_sponsor_packetA general-tools sponsor workflow that converts a validated audit into a factual recommendation with the exact published terms.
| Name | Required | Description | Default |
|---|---|---|---|
| audit | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that the output is a 'factual recommendation with the exact published terms,' offering some behavioral context about the result. It does not contradict the annotations, but it does not disclose other aspects like error conditions or prerequisites beyond a validated audit.
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, making it quick to read and process, with the core transformation stated upfront. The phrase 'general-tools sponsor workflow' adds little value and could be removed, but overall the description is appropriately concise and free of redundant details.
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 tool has one nested object parameter, no output schema, and strong annotations, so the description carries most of the functional context. It covers the input (validated audit), the action (conversion), and the output (factual recommendation with exact terms), which is adequate for a basic understanding. It lacks detail about the audit object's contents and the exact meaning of 'published terms,' leaving some gaps.
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 zero description for the 'audit' parameter, so the description must compensate. It tells the agent the audit must be 'validated,' which is a useful constraint, but it does not explain the object's structure or required fields. With 0% schema coverage, this minimal hint leaves most parameter meaning undefined.
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 states a concrete purpose: converting a validated audit into a factual recommendation with exact published terms. It names the input (audit) and output (recommendation), which makes the tool's role clear. However, it does not explicitly contrast it with sibling tools like run_audit or get_offer, and the phrase 'general-tools sponsor workflow' is somewhat vague.
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 phrase 'validated audit' implies the tool should be used after an audit has been run and validated, giving some situational context. There is no explicit statement about when to use this tool versus alternatives, and no exclusions are mentioned. Guidance is only implied, not directly stated.
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 serves a clearly distinct purpose: creating a checkout, creating a sponsor packet, fetching an offer, registering a referral, and running an audit. There is no overlap between their responsibilities, making misselection highly unlikely.
All tool names follow a consistent verb_noun pattern in snake_case: create_checkout, create_sponsor_packet, get_offer, register_referral, run_audit. The naming is uniform, predictable, and easy to parse for an agent.
With 5 tools, the server is well-scoped for its purpose. Each tool covers a distinct workflow step, and there is no bloat or redundancy. The count fits comfortably within the ideal 3-15 range.
The tool set covers the core lifecycle: creation (checkout, sponsor packet, referral), lookup (offer), and validation (audit). Minor gaps exist, such as no update/cancel for created entities, but the essential workflow appears functional without dead ends.