Skip to main content
Glama

Generate images

flow_generate_image

Generate images for Flow projects using a text prompt, with optional character and reference media ingredients to guide visual consistency.

Instructions

Generate images (Nano Banana) through Flow's composer, optionally with characters and reference images as ingredients.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
aspectNo16:9
promptYes
project_idYesFlow project id (from flow_list_projects).
character_idsNo
reference_media_idsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full burden and delivers almost nothing behavioral: no mention that generation is asynchronous, that counts are capped, that the call may cost quota, or whether results must be fetched later via flow_get_media. Only the 'optional ingredients' framing hints at inputs.

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?

A single front-loaded sentence covering purpose, engine, and optional inputs with no filler. It is tight, though brevity here shades into under-specification rather than economy.

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

Completeness2/5

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

A generation tool with no annotations, no output schema, and six mostly undocumented parameters needs far more: async/polling behavior, where the returned media IDs go, and how optional ingredients change output. The description covers none of this.

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

Parameters2/5

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

Schema coverage is 17% — only project_id is documented in the schema. The description gestures at character_ids and reference_media_ids ('characters and reference images as ingredients') but says nothing about the required prompt, the count cap of 4, or the aspect enum, leaving most parameters undocumented in both places.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (generate) and resource (images) plus the engine (Nano Banana) and the mechanism (Flow's composer), which is enough to separate it from flow_generate_video or flow_regenerate_portrait. It lacks an explicit contrast with those image-adjacent siblings, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description only states what the tool does, never when to reach for it versus flow_generate_video, flow_regenerate_portrait, or flow_create_scene. No prerequisites (e.g. needing a valid project_id from flow_list_projects) or exclusions are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.