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AIStoryHub

Étincel MCP Server

by AIStoryHub

Add a word to a custom (allowed) words list

add_custom_word
Idempotent

Add a word or phrase to your custom allowed-words list so audit_text never flags it as an AI tell or banned term. Optionally scope to a specific style.

Instructions

Add a term to this installer's own allowed-words list, so audit_text never flags it even if it matches the built-in corpus or a banned word: the 'corporate dictionary' case, e.g. an org's own acronyms or house terms. Without styleId, this adds to the global list. With styleId, it only applies to that specific style, merged on top of the global list. Use this when the user says something like 'add [word] to my custom words list' or 'stop flagging [word], it's one of ours'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wordYesThe term or short phrase to always allow.
styleIdNoStyle id to scope this to, from list_styles. Omit to add to the global list.
Behavior4/5

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

The description goes beyond the annotations by explaining the merge behavior (style-specific list merged on top of global) and the effect of never flagging the term even if it matches a banned word. It does not contradict the idempotentHint annotation and provides useful context that the schema and annotations alone don't convey. Minor gaps exist around permissions or error handling, but they are not critical.

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, front-loading the primary action in the first sentence and then providing context and usage examples. Every sentence adds value, with no repetitive or unnecessary content. The length is appropriate for the tool's complexity.

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 simple two-parameter tool with no output schema and helpful annotations, the description provides sufficient context about purpose, effect, and behavior. It covers the most relevant aspects, though it omits details about return values or possible validation errors. These are minor and not critical for a tool of this simplicity.

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?

Schema description coverage is 100%, so baseline is 3. The description adds meaningful semantics beyond the schema for styleId, clarifying that 'merged on top of the global list' and that omitting styleId targets the global list. It also reinforces the purpose of the word parameter with a practical example. This incremental information justifies a 4.

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 action ('Add a term to this installer's own allowed-words list'), the resource (the list), and the intended effect on audit_text. It also distinguishes itself from banning words and explains the global vs style-specific scope, which differentiates it from sibling tools like add_banned_word or remove_custom_word.

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

Usage Guidelines4/5

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

The description provides explicit user-phrase triggers ('add [word] to my custom words list' or 'stop flagging [word], it's one of ours') and clarifies when to use global vs style-scoped additions. It does not explicitly mention alternative tools for when not to use it (e.g., if the user wants to ban a word), so it falls short of a 5.

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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