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gavxm
by gavxm

anilist_explain

Read-only

Analyze an anime or manga against your taste profile to understand why you would or wouldn't like it. Returns match score and affinity breakdown.

Instructions

Score a specific title against a user's taste profile and explain the alignment. Use when the user asks "why would I like this?", "is this for me?", or wants to know how well a specific anime/manga matches their preferences. Returns match score, genre/theme affinity breakdown, mood fit, and existing list status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mediaIdNoAniList media ID to evaluate against your taste profile
titleNoSearch by title if no ID is known
usernameNoAniList username. Falls back to configured default if not provided.
typeNoBuild taste profile from anime list, manga list, or bothBOTH
moodNoOptional mood context, e.g. "dark and brainy"
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. Description adds valuable behavioral details: returns match score, genre/theme affinity breakdown, mood fit, and existing list status. No contradictions.

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?

Two sentences, front-loaded with purpose, no wasted words. Highly efficient.

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?

No output schema, but description lists return values. Covers main aspects of what the tool does and returns. Context about parameters is fully covered.

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?

Schema coverage is 100%, so baseline is 3. Description adds some context (e.g., 'Search by title if no ID is known', 'Falls back to configured default') but does not significantly enhance beyond schema 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?

Description uses specific verbs 'score' and 'explain' and clearly identifies the resource: a title against a user's taste profile. It distinguishes from sibling tools by focusing on explanation of match, which is unique among tools like anilist_search, anilist_details, etc.

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?

Explicitly states when to use: when user asks 'why would I like this?' or similar. Provides clear context but does not mention when not to use or alternatives.

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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