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AI Manga & Anime Generator - Mangii MCP

List story panels

manga.list_panels
Read-onlyIdempotent

List panels you own for a story. Use this to get panel_id values before changing Image 1 or Image 2 on manga.continue_story or manga.regenerate_panel. Each row has ref_role: identity on the first panel, scene on the last distinct panel, otherwise null.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
story_idYesStory id from manga.create_story. Example: a Firestore story document id returned as story_id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNoHow to override Image 1 and Image 2 on continue or regenerate.
errorNoMachine error code such as invalid_request, insufficient_credits, or quality_forbidden.
panelsYesPanels in reading order, with ids for identity_panel_id and continuity_panel_id.
messageNoHuman-readable error. Never includes stack traces or internal paths.
story_idNoStory id from manga.create_story. Example: a Firestore story document id returned as story_id.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already communicate readOnly, idempotent, open-world, and non-destructive behavior. The description adds meaningful context beyond those hints: the 'you own' scoping and the ref_role semantics on the first panel, last distinct panel, and otherwise null. This is genuine behavioral detail that helps the agent interpret rows correctly.

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 compact and well organized: an initial statement of what the tool returns, a practical usage instruction, and then the most important data nuance about ref_role. No filler or repeated annotation information is included.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, single-parameter listing tool that already has an output schema and read-only/idempotent annotations, this description is complete. It tells the agent what it will get and why, and the workflow guidance removes the likely source of misuse. 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 input schema already fully documents the only parameter, story_id, with an explanation and example. The description does not add new parameter-level semantics beyond saying the panels belong to a story, so a baseline score of 3 is appropriate because the schema carries the load.

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 uses specific verbs and resources: it 'List[s] panels you own for a story', identifies the primary value returned (panel_id), and mentions the story context. It also distinguishes this tool from the sibling mutation tools by framing it as the lookup step before continue_story or regenerate_panel.

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 gives an explicit usage rule: use this tool to get panel_id values 'before changing Image 1 or Image 2 on manga.continue_story or manga.regenerate_panel.' This tells the agent both the task and the correct sequencing relative to two sibling tools, so there is no ambiguity about when it should be called.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: story creation, continuation, regeneration, panel listing, story listing, style listing, credit lookup, credit purchase, and job polling. Even the credit-related tools are clearly separated by purchase versus query. There is no meaningful overlap that would confuse an agent.

Naming Consistency5/5

All tools consistently use the manga. prefix with snake_case verb_noun names like create_story, list_panels, and regenerate_panel. The pattern is uniform across the entire set, making the API predictable and easy to navigate.

Tool Count5/5

Nine tools is a well-scoped size for a manga generation server: three creation-oriented tools, three listing tools, two credit tools, and one async job helper. Each tool serves a clear, non-redundant role in the workflow.

Completeness4/5

The core manga creation lifecycle is well covered: create, continue, regenerate, list stories, and list panels, plus style discovery and credit management. The only notable gaps are destructive operations like deleting stories or panels and perhaps a story detail endpoint, but these are not essential to the primary generation workflow.