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EezyMAcc

Tattoo Feed

by EezyMAcc

record_preference

Log a note about your tattoo taste after you confirm the observation. Captures style preferences for curated recommendations.

Instructions

Record a note about the user's tattoo taste.

IMPORTANT: Before calling this tool, propose the observation to the user in
your own words and obtain their explicit confirmation. Only call it once the
user has agreed the observation is accurate. This captures taste (e.g.
"prefers fine-line botanical work"), which is distinct from saving a
specific image with save_to_inspiration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
observationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
observationYes
created_atNo
Behavior4/5

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 records a taste observation and requires user consent, which is important for a write operation. However, it does not mention any potential side effects (e.g., overwriting existing preferences), but it is concise enough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, no fluff. The critical instruction is bolded for emphasis. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a single parameter and an existing output schema, the description fully covers when to use, what to capture, and the prerequisite step. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains that the 'observation' parameter captures taste and provides an example ('prefers fine-line botanical work'), adding meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool records a note about the user's tattoo taste. It distinguishes itself from the sibling tool 'save_to_inspiration' which saves specific images, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs the agent to propose the observation to the user and obtain explicit confirmation before calling. This is a crucial prerequisite, and the description also clarifies when to use this tool versus saving an image, providing clear guidance.

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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