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Show an AI influencer

get_character
Read-only

One AI influencer in full: who the influencer is (age, nationality, vibe, the description it was made from), whether the user's plan unlocks it, its finished looks and its finished clips, as a profile card the user can browse and play. Use it when the user names or picks one influencer; list_characters is for browsing many. Costs no credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOr the influencer name, when the id is not known ("Ida"). The closest public or own match wins.
characterNoThe influencer id from list_characters.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nextYes
clipsYesFinished clips, newest first, up to 12. list_clips has all of them.
looksYesFinished looks, newest first, up to 12. list_images has all of them.
characterYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds real value beyond that: it discloses the returned payload shape (identity, plan unlock status, looks, clips) and the cost profile ('Costs no credits'), which is not derivable from annotations.

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?

Front-loaded with the core purpose and tightly packed with useful content; the long single sentence covering payload contents is dense but each clause earns its place. Minor risk of being slightly overloaded in one breath.

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?

With an output schema present and full schema coverage on parameters, the description only needs to frame selection and behavioral context, which it does. Read-only, zero-cost, identity-or-list routing are all 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 both parameters (name, character) are fully documented in the schema, including the fallback matching behavior 'The closest public or own match wins.' The description adds nothing further about parameters, so the baseline 3 applies.

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?

States a specific verb+resource ('One AI influencer in full') and enumerates what the profile card contains: identity attributes, plan unlock status, finished looks, and clips. It explicitly names the sibling it is not (list_characters is for browsing many), so the agent can route without opening either schema.

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?

Gives an explicit trigger ('when the user names or picks one influencer') and an explicit alternative with its condition ('list_characters is for browsing many'). Nothing about when-to-use is left to inference.

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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