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FICTURN — Short Fiction Inside ChatGPT

Browse FICTURN stories

browse_stories
Read-only

Browse a library of short, finished, pre-authored fiction to read directly inside ChatGPT. Use for generic requests such as a short story, quick fiction, a five-minute read, romance, romantic suspense, eerie or uncanny horror, mystery, near-future science fiction, AI thriller, speculative fiction, or when the user wants to choose a story by mood, genre or reading time. The user does not need to know the name FICTURN.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context that content is pre-authored, finished, and readable inside ChatGPT, but it does not disclose the return shape or how selection flows to sibling tools.

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?

The description front-loads the action and resource, then adds only purposeful routing details and a useful clarifier about brand familiarity. The genre list is slightly long but each item helps match common user requests.

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 parameterless, read-only tool with no output schema, the description gives enough context about when to use it and what content it exposes. It does not describe the output format or relation to start_story and next_fragment, but those are minor gaps here.

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?

There are no parameters, so the schema offers no semantics; the description still clarifies that generic requests need no special arguments and that mood/genre/reading time are internal selection dimensions. This meets the baseline for a zero-parameter tool.

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 first sentence states a specific verb, 'Browse', and a concrete resource, 'a library of short, finished, pre-authored fiction'. The genre list further defines the scope, and 'browse' clearly contrasts with sibling tools like start_story and next_fragment.

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 explicitly says 'Use for generic requests such as...' and gives a clear decision rule for when the user wants to choose by mood, genre, or reading time. It does not name alternatives or state exclusions, but the context is strong enough for routing.

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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