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MemoryBrain

by ai.memorybrain
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Leer un chat importado

read_chat
Read-only

Devuelve el texto de un chat importado, por páginas de 15.000 caracteres. Úsala para leerlo antes de sacar notas con feed_brain (source.chat = su id); para buscar en lo ya guardado, usa search_brain. Si next no es null, vuelve a llamar con from = next para seguir.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "read_chat"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesEl id que dio list_chats.
fromNoDesde qué carácter seguir: el next de la llamada anterior (0 por defecto).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / from / description
      Added value: +"Desde qué carácter seguir: el next de la llamada anterior (0 por defecto)."
  2. First observed

TDQS

A4.6/5.0
Behavior4/5

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

The pagination behavior is fully disclosed: 15.000-character pages and the instruction to re-call with from = next when next is not null, which goes beyond the readOnlyHint/openWorldHint annotations. It stops short of describing error behavior for an unknown id or what the terminal call looks like, so it is not exhaustive.

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 short sentences, front-loaded with what the tool returns, then usage routing, then the continuation instruction. No filler and every sentence carries actionable information.

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 two-parameter read tool without an output schema, the description covers the return nature (paged text) and the one output field that drives the next call (next). It could say more about what a final page looks like or the minimum for the 'from' value, but nothing essential to invoking it correctly is missing.

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?

With 100% schema coverage the baseline is 3, but the description adds meaning by tying 'from' to the 'next' value returned by the prior call, a field not present in the input schema. It thereby explains the continuation loop rather than just restating the parameter descriptions.

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 opens with a specific verb and resource ('Devuelve el texto de un chat importado') and immediately bounds the output as 15.000-character pages. It also distinguishes itself from siblings by naming feed_brain (for note-taking) and search_brain (for querying saved content), so an agent can route correctly without inspecting other schemas.

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?

Explicit when-to-use is given: read the chat before extracting notes with feed_brain, passing source.chat = its id. It also states when NOT to use it ('para buscar en lo ya guardado, usa search_brain') and names the alternative, 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.

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