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Glama

Brand Memory: what is still open

brain_onboarding
Read-only

Fetch open Brand Memory setup questions, ask a human for answers, and save them with brain_write under each item's path until none remain.

Instructions

What is still open in Brand Memory, as the questions a human answers, with hints. Ask the human, write the answers as markdown under the question headings with brain_write at the item's path, then call again until open is empty. Needs the read scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
howNo
doneYes
openYes
percentYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.4

TDQS

A4.2/5.0
Behavior4/5

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

Beyond the readOnlyHint/destructiveHint annotations, it discloses an auth prerequisite ('Needs the read scope') and the iterative loop semantics with a clear exit condition (until open is empty). It correctly routes the mutation to brain_write rather than implying this tool writes, so it is consistent with readOnlyHint=true. Return shape detail is left to the output schema.

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?

Three compact sentences, front-loaded with what is returned and followed by the operational loop; no filler. Some phrases ('with hints', 'at the item's path') are telegraphic and would benefit from a touch more precision without adding length.

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

Completeness4/5

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

For a zero-parameter read tool with an output schema, the description covers purpose, auth scope, and the expected human-in-the-loop cycle, which is what an agent needs to act. It does not describe pagination or list sizing, but with the output schema present and a clear 'until empty' condition, the gap is minor.

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?

Zero parameters, so there is nothing for the description to clarify and the baseline is 4. The mention of 'the item's path' usefully ties the response items to the brain_write call without adding undocumented inputs.

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

Purpose4/5

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

The description states a concrete resource and scope: the open questions in Brand Memory returned as human-facing questions with hints, which is a specific onboarding surface rather than generic memory retrieval. The verb is implicit (returns/lists) and it never contrasts itself with brain_read or brain_tree, so an agent must infer the distinction from context.

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?

It prescribes the full workflow: ask the human, write answers as markdown under the question headings via brain_write at the item's path, then re-call until open is empty. This gives both the when (while open items remain) and the terminating condition, plus the partner tool, leaving nothing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.