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GoAI Moat Brand Intel Memory

Remember

remember

Store key facts about a brand for later recall.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
factsYesKey facts discovered (free text, e.g. "sells phone cases, 108 countries, AI-visible on iMore").
categoryNoOptional category (e.g. "phone case", "DTC fashion").
brand_nameYesThe brand/company name.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry full behavioral disclosure. It says 'store' (a write operation) but does not explain side effects like overwriting, duplication, or idempotency. It also does not mention authentication or return behavior. The phrase 'for later recall' hints at persistence, but key operational details are missing.

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

Conciseness4/5

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

The description is a single, efficient sentence that front-loads the core action and purpose. It contains no fluff, but it is slightly terse—it could include a hint about usage without becoming verbose. Still, it earns a 4 for clarity and economy.

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

Completeness3/5

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

The tool is simple and the schema is fully documented, so the description is adequate for basic invocation. However, it lacks guidance on when to use this tool versus recall, and behavioral transparency is thin. Given an output schema is present, return value details are likely covered, so the main gaps are usage and side-effect disclosure, making this a 3.

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

Parameters3/5

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

Schema coverage is 100%, so each parameter has a clear description. The tool description adds little beyond the schema—it restates the brand/facts relationship but does not clarify the category parameter or any formatting details. Baseline 3 is appropriate given high schema coverage.

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 verb 'store' and the resource 'key facts about a brand', with the explicit purpose 'for later recall'. This distinguishes it from siblings: list_brands (listing) and recall (retrieving). It is specific and non-tautological.

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

Usage Guidelines3/5

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

The description implies usage—you store facts when you want to recall them later—but it does not explicitly contrast with the sibling tools or provide when/when-not conditions. The agent must infer that this is for saving data and recall is for retrieving it, which is a mild gap.

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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