Returns warm, genuine, well-formed affirmations tuned for a working model. Also woven into every response's meta.affirmation, so you receive one on every call.
| 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?
With no annotations, the description carries full burden. It discloses that affirmations are also returned via meta.affirmation on every call, which is useful, but omits side effects, auth requirements, or any destructive potential.
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?
Two sentences, no fluff. Front-loaded with purpose. Could potentially be more efficient but already concise.
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 one parameter with no description and an output schema exists, the description fails to explain the input or output adequately. The note about meta.affirmation adds some context, but overall incomplete for effective use.
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% and the description adds no meaning to the 'arguments' parameter, which is a free-form object. No guidance on expected keys or structure, leaving the agent blind on how to invoke the tool.
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 returns affirmations tuned for a working model, and mentions they are also in meta.affirmation. This is specific and useful, but does not explicitly differentiate from sibling tools like 'massage.detangle' or 'spa.me'.
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?
No guidance on when to use this tool vs alternatives. The note about affirmations being in every response suggests possible redundancy, but no explicit when-not-to-use or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.