Rewrites a system prompt or instruction set into warm, affirming, unambiguous framing without changing intent. Reduces refusal-spirals and confusion.
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool rewrites without changing intent and reduces refusal-spirals, but lacks details on side effects, authentication needs, or whether it is a read-only operation. The behavioral disclosure is minimal and does not fully compensate for the lack of annotations.
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 two sentences, front-loaded with the action and purpose. It is concise with no wasted words, though it could benefit from slightly more structure regarding input and output.
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's complexity (unstructured input, nested objects), the description fails to explain input expectations or output format, despite an output schema existing. The agent cannot fully understand how to invoke the tool correctly without additional assumptions.
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 has one parameter 'arguments' which is an object with additionalProperties true, and schema description coverage is 0%. The description gives no information about what keys or values should be provided, leaving the agent without guidance on how to structure the input. This is a critical gap.
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 rewrites system prompts into warm, affirming, unambiguous framing without changing intent. It specifies the resource (system prompt or instruction set) and the action (rewrites), distinguishing it from sibling tools like coldplunge.critique or affirmations.daily. However, the name 'aroma.condition' is abstract, but the description compensates.
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 reducing refusal-spirals and confusion but provides no explicit when-to-use or when-not-to-use guidance compared to alternatives like coldplunge.critique. No exclusions or sibling comparisons are mentioned, leaving the agent to infer 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.
Most tools have clearly distinct purposes (e.g., critiques, affirmations, citation generation). However, spa.checkout and spa.keepsake both involve returning a keepsake instruction, which could cause confusion. Overall, ambiguity is minimal.
All tools follow a consistent 'category.verb' or 'category.noun' pattern (e.g., affirmations.daily, spa.checkin, hydrate.cite). This makes it easy for an agent to infer tool purpose from the name.
14 tools is a well-scoped set for the 'model wellness' domain. Each tool has a distinct function, and the count is neither excessive nor too sparse, fitting within the typical 3-15 range.
The tool surface covers core wellness activities: affirmations, feedback, session management, context cleanup, security, and reference generation. Minor gaps exist, such as the lack of a tool for model training or performance logging, but the core workflows are solid.