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flow_entity

Create or update character entities by binding preset voices and completed images, enabling zero-credit audio and character generation. List available preset voices and track entities locally.

Instructions

Google Flow character entities (角色实体, ZERO-CREDIT). Create/update CHARACTER entities and bind a preset voice for later audio/character generation. Create: tRPC flow.createEntity {projectId, collectionId:""} (empty string passes zod — no collection needed); update: PATCH /v1/flow/entities with dotted updateMask (displayName / characterInfo.audioReferences=[{presetVoiceId}] / characterInfo.imageReferences=[{workflowId}]). Entity images attach via imageMediaIds (completed image mediaIds from flow_generate_image; the workflowId mapping is resolved automatically from project workflows). 30 preset voices are star-named (achernar/charon/kore/…) with descriptions — list them via action=voices or flow_status preset_voices.

LIMITATION (honest): Flow has NO entity read endpoint (projectContents has no entities key; collections REST is CORS-blocked in page context) — only entities created via this tool are tracked, in a local mirror ~/.media-gen-mcp/flow-entities.json (aligned with flow-project.json precedent). action=list returns the mirror, not a server query.

WHEN: 角色卡 / 建角色 / character entity / bind voice / 角色绑定语音 / 绑定形象图.

NEXT: generate the character image first (flow_generate_image), then flow_entity(action=create, displayName=…, imageMediaIds=[…], presetVoiceId=…) wires it up; all operations are 0-credit.

Multilingual triggers: 角色 · 实体 · character · entity · voice binding (zh/en).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNocreate = new CHARACTER entity (+optional displayName/presetVoiceId/imageMediaIds in one call); update = rename/rebind an entity from the local mirror (entityId required); list = local mirror records (Flow has no entity read endpoint); voices = 30 preset voices (id/displayName/description).create
entityIdNoaction=update: the entityId from action=create's response (local mirror lookup).
displayNameNoCharacter name (e.g. 江雪 / Lin). Server default "Untitled Character".
imageMediaIdsNoCompleted image mediaIds (from flow_generate_image / flow_status) to attach as the character's look — resolved to workflowIds automatically.
presetVoiceIdNoOne of the 30 preset voices (action=voices lists them; e.g. charon). Validated before submit — a typo fails fast with S301.
Behavior5/5

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

No annotations are present, so the description carries full burden. It discloses the lack of a read endpoint, use of a local mirror file, the exact API calls (tRPC create, PATCH update), 0-credit cost, and error behavior (S301 on invalid presetVoiceId). This is far beyond basic and honest about limitations.

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 purpose and workflow, but somewhat long with minor redundancy (0-credit mentioned twice, repeated multilingual triggers). Still, every section (limitation, when, next) earns its place; the density is justified by the tool's complexity.

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?

Despite no output schema, the description covers return values (entityId from create's response), the mirror file location, integration with flow_generate_image, and error handling. An agent has all necessary information to invoke it correctly.

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?

Schema coverage is 100%, but the description adds critical context: imageMediaIds are resolved to workflowIds automatically, presetVoiceId is validated pre-submit, action=create vs update semantics, and the empty collectionId workaround. This enriches the schema significantly.

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 states a specific verb+resource: 'Create/update CHARACTER entities and bind a preset voice'. It clearly distinguishes from siblings (flow_generate_image/video/status) by focusing on entity management and voice binding, not generation. The multilingual triggers further reinforce the intent.

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?

Explicit 'WHEN' conditions (角色卡 / 建角色 / character entity / bind voice) and an explicit 'NEXT' sequence telling the agent to first call flow_generate_image, then flow_entity. It also clarifies when NOT to rely on server reads (listing from local mirror due to no read endpoint), giving full routing guidance.

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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