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hipocampo_auto_repair

Automatically detects and repairs common system issues including restarting PostgreSQL, creating missing tables, and verifying NVIDIA API key configuration.

Instructions

Intenta reparar automáticamente problemas detectados en el sistema.

Reparaciones posibles:

  • Reiniciar PostgreSQL si está caído

  • Crear tablas faltantes desde esquema.sql

  • Verificar/configurar NVIDIA_API_KEY

Returns: Reporte de reparaciones ejecutadas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description outlines the tool's actions (restarting PostgreSQL, creating tables, verifying a key) and states it returns a report. Since no annotations are provided, the description carries the full burden. It is adequate but could be improved by indicating that operations like restarting PostgreSQL may cause temporary unavailability or that the tool attempts repairs but does not guarantee success.

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?

The description is concise and well-structured. It starts with a one-sentence purpose, then uses a bullet list for repair actions, and ends with the return type. Every part is informative without redundancy.

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?

Given that there are no parameters and an output schema exists, the description covers the essential aspects: what repairs are attempted and what is returned. However, it could be more complete by explaining how the tool detects issues (e.g., from 'hipocampo_health'?) or when an agent should invoke it.

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?

The input schema has zero parameters, so the schema already fully defines the interface. The description adds value by listing the specific repair actions, giving an agent context on what the tool will do with no input. This aligns with the baseline of 4 for no-parameter tools.

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 clearly states the tool's purpose: 'Intenta reparar automáticamente problemas detectados en el sistema' (attempts to auto-repair detected system issues). It enumerates specific repairs like restarting PostgreSQL, creating missing tables, and verifying NVIDIA_API_KEY. However, it does not differentiate itself from siblings like 'hipocampo_health' or 'hipocampo_maintenance', which could overlap in functionality.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It lists possible repairs but does not specify prerequisites, conditions for use, or scenarios where it should be avoided. Sibling tools like 'hipocampo_health' or 'hipocampo_maintenance' might be more appropriate in certain contexts, but no comparison is made.

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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