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kernel_config_set

Set a configuration value and apply it immediately without restarting; changes persist to the .env file for later use.

Instructions

Set a configuration value. Changes take effect immediately (no restart needed) and are persisted to the .env file. Examples: set LIFE_CITY to 'Berlin', set CHAT_DEFAULT_PROVIDER to 'openai', set PROACTIVE_MORNING_TIME to '08:00'.

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": {
      "key": "<key>",
      "value": "<value>"
    },
    "name": "kernel_config_set"
  }
}

Input Schema

NameRequiredDescriptionDefault
keyYesEnvironment variable name, e.g. LIFE_CITY
valueYesNew value to set

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses that changes apply immediately without a restart and are persisted to the .env file, which is the key behavioral fact for a mutation tool. It omits validation/error behavior (e.g., whether arbitrary keys are accepted or unknown keys rejected) and any permission requirements.

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?

Front-loaded with the action, followed by the behavioral guarantee and then a compact list of examples. The examples are illustrative rather than padding, though three of them is close to redundant for a two-parameter tool.

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-required-param setter with no output schema and no annotations, the description covers action, immediacy, persistence, and example values — enough to call it correctly. The remaining gap is what happens on invalid or unknown keys.

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 description coverage is 100%, so both parameters are already documented in the schema. The examples add format intuition for values (a city name, a provider id, an 'HH:MM' time) but nothing about key constraints or validation, so this stays at the baseline.

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?

States a specific verb and resource ('Set a configuration value') that clearly separates it from read-oriented siblings like kernel_config_get and kernel_config_list. It does not name kernel_config_set_many as the bulk alternative, so the boundary with that sibling is left implicit.

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 examples imply the intended usage for single-key updates and give a feel for realistic keys and values. There is no explicit when-to-use/when-not guidance and no mention that multiple keys should go through kernel_config_set_many.

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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