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config_set

Write a config.yaml value with an explicit type, preventing 'off' or 'yes' from becoming booleans. Backs up the file before applying changes.

Instructions

Write one config.yaml value with an explicit type.

value_type is one of str, int, float, bool, null, json. Passing a type avoids the YAML trap where "off", "no" and "yes" silently become booleans - several Hermes options compare against the string, so an auto-parsed value quietly does nothing. A .bak copy is written before the file changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
valueYes
value_typeNostr

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.4/5.0
Behavior4/5

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

Despite no annotations being provided, the description proactively discloses important behaviors: it writes a .bak copy before changing the file, and it explains the type-safety reason (avoiding the YAML trap with 'off', 'no', 'yes'). This goes beyond a simple 'write' verb and gives the agent essential safety and side-effect information.

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 succinct, front-loads the core purpose in the first line, and then uses two short paragraphs to explain the value_type parameter and the .bak backup. Every sentence contributes meaning without waste, making it easy to scan.

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 the tool's simplicity (3 params, 2 required) and the presence of an output schema, the description is complete enough for an agent to call it correctly. It covers the critical type-safety caveat and the backup behavior, and the output schema likely clarifies return values, so nothing critical is missing.

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?

The schema has 0% description coverage, so the description must compensate. It explains the purpose and allowed values of 'value_type' without using an enum, providing crucial semantics. It does not explain 'key' or 'value' beyond what their names imply, but the main ambiguity is covered.

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 tool writes one config.yaml value with an explicit type. It specifies the verb 'write', the resource 'config.yaml value', and the distinguishing feature 'explicit type', which differentiates it from config_get and other sibling tools.

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?

The description explains when to use this tool (to avoid YAML type coercion) and warns against relying on auto-parsed values, suggesting a clear context for use. It does not explicitly name alternatives, but the sibling list includes config_get, so the usage is implicitly differentiated.

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