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echo-xianyu

Danbooru Search MCP

by echo-xianyu
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Python
Remote

danbooru_get_character_profile

Read-onlyIdempotent

Retrieve a full Danbooru character profile with co-occurring tags, wiki description, aliases, and tag implications. Automatically corrects misspelled tags.

Instructions

RECOMMENDED FIRST CHOICE for any character/tag lookup.

Returns everything in one call: visual traits (co-occurrence frequencies), wiki description, multilingual aliases, and tag implications in both directions (what this tag implies, and what tags imply this one — e.g. all costume variants).

Aggregates these data sources in parallel:

  1. Related tags (co-occurrence frequencies) -> visual traits.

  2. Wiki page -> textual description and multilingual aliases.

  3. Tag implications (antecedent) -> tags auto-added by this tag.

  4. Tag implications (consequent) -> tags that auto-add this tag (e.g. costume variants like hoshino_(swimsuit)_(blue_archive) imply hoshino_(blue_archive)).

Each source degrades gracefully: a missing wiki page or empty implications do not fail the whole request.

When auto_resolve is enabled (default) and the queried tag does not exist on Danbooru, the tool corrects the tag name via autocomplete and rebuilds the profile. The correction is reported in resolved_from.

Args: params (GetProfileInput): Validated input: - tag (str): Character tag, e.g. 'hoshino_(blue_archive)'. - limit (int): Max characteristic tags (1-100, default 25). - response_format (ResponseFormat): 'markdown' or 'json'. - auto_resolve (bool): Auto-correct misspelled tags (default True).

Returns: str: Markdown profile or JSON. Success JSON schema: { "tag": {"name": str, "category": str, "category_id": int, "post_count": int}, "characteristics": [ {name, category, post_count, frequency}, ... ], "wiki_page_tags": [ {name, category, post_count}, ... ], "implied_by": [ {antecedent_name, consequent_name, status}, ... ], "implies_this": [ {antecedent_name, consequent_name, status}, ... ], "wiki": {"title": str, "other_names": [str], "body": str} | null, "resolved_from": {"original": str, "resolved": str, "corrected": bool} | null, "suggestions": [ {name, category, post_count, is_alias}, ... ] } Error: "Error: ".

Examples: - "Give me everything about Hoshino from Blue Archive" -> params with tag='hoshino_(blue_archive)'. - "Full profile of Rem from Re:Zero" -> params with tag='rem_(re:zero)'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

The description discloses key behavioral details beyond annotations: it aggregates data sources in parallel, each degrades gracefully, and auto_resolve corrects misspelled tags. Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint) are consistent and complemented by this context.

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 is well-structured and front-loaded with key information. It is longer than minimal but every section (recommendation, capabilities, data sources, parameters, return schema, examples) adds value. Could be slightly tightened in wording.

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?

Given the tool's complexity and the presence of an output schema, the description is completely thorough: it explains data sources, graceful degradation, auto_resolve behavior, return schema fields, error handling, and provides examples. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite schema description coverage being 0%, the description compensates fully by explaining each parameter (tag, limit, auto_resolve, response_format) with behavior, defaults, and examples. It adds meaning beyond the schema's own descriptions.

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 returns everything in one call for a character/tag lookup, listing visual traits, wiki description, multilingual aliases, and implications. It explicitly recommends it as the first choice, distinguishing it from sibling tools like danbooru_get_tag_implications or danbooru_get_wiki_page.

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 recommends this tool as the first choice for any character/tag lookup, implying it should be used over siblings when a comprehensive profile is needed. It does not explicitly state when not to use it, but the contrast with siblings provides clear context.

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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