Google Flow Browser MCP
Allows AI agents to control Google Flow for image and video generation via browser automation using your own Google account.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Google Flow Browser MCPGenerate an image of a sunset using Imagen 4"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
π§ Google Flow Browser MCP
Control Google Flow β image & video generation β directly from your AI agent via MCP.
β¨ Features β’ π Quick Start β’ π§ Tools β’ βοΈ Configuration β’ π‘οΈ Safety
π«π· Ce serveur MCP permet Γ votre agent AI (OpenCode) d'utiliser Google Flow pour gΓ©nΓ©rer des images et des vidΓ©os, via votre propre compte Google et sans partager vos identifiants.
πΈ What It Does
This MCP server connects your AI agent to Google Flow β Google's creative suite for image and video generation. Your agent can:
π¨ Generate images with Nano Banana Pro, Nano Banana 2, or Imagen 4
π¬ Create videos and scenes with characters
π§ Manage characters and scenes in your Flow workspace
πΌοΈ Use Grid Architect for batch shot generation
π Discover and control any Flow tool programmatically
All through your own Google account β no API keys, no third-party tokens.
Related MCP server: Google Flow Browser MCP
β¨ Features
π― For AI Agents
π For Humans
15+ MCP tools ready to use
Smart job queue β no parallel conflicts
Auto-discover UI β adapts to Flow changes
Structured logging for debugging
Safe actions β resilient click/fill logic
Your account, your data β no token sharing
No password asked β ever
Clean safety rules β stops on captcha/verification
Config backup before any modification
Single-job queue β no runaway generation
π Quick Start
Prerequisites
What | Why |
Node.js β₯ 18 | Runtime for the MCP server |
Google Chrome | Required for browser automation |
OpenCode | AI agent that connects to MCP servers |
A Google account | To use Google Flow (yours, not shared) |
1οΈβ£ Install
git clone https://github.com/TMSSS05/google-flow-browser-mcp.git
cd google-flow-browser-mcp
npm install2οΈβ£ Configure your Google profile
cp config/flow.config.example.json config/flow.config.jsonEdit config/flow.config.json:
{
"expectedAccount": "your.email@gmail.com",
"chromeProfile": "Profile 3",
"chromeUserDataDir": "/home/you/.config/google-chrome"
}π‘ Finding your Chrome profile:
Open Chrome and go tochrome://version/. Look for "Profile Path" β the last folder name is your profile (e.g.,Profile 3), and the path before it is yourchromeUserDataDir.
3οΈβ£ Make scripts executable
chmod +x scripts/*.sh4οΈβ£ Start Chrome with CDP
./scripts/start-browser.shThis launches Chrome with remote debugging enabled on port 9222 using your configured profile.
5οΈβ£ Start the MCP server
# In a separate terminal:
./scripts/start-mcp.sh6οΈβ£ Register with OpenCode
./scripts/register-opencode.shπ Restart OpenCode after registration for the changes to take effect.
β Verify it works
./scripts/test-flow-image.shποΈ Architecture
google-flow-browser-mcp/
β
βββ π config/
β βββ flow.config.example.json # Configuration template
β βββ selectors.map.json # UI selectors (auto-populated)
β
βββ π scripts/
β βββ start-browser.sh # Launch Chrome + CDP
β βββ start-mcp.sh # Start the MCP server
β βββ test-flow-image.sh # Quick integration test
β βββ register-opencode.sh # Register in OpenCode config
β
βββ π src/
β βββ index.js # MCP server entry point
β β
β βββ π browser/ # Chrome & CDP management
β β βββ connect.js # CDP connection manager
β β βββ launch-profile.js # Chrome profile launcher
β β βββ account-check.js # Verify Google account
β β βββ safe-actions.js # Safe click, fill, detection
β β
β βββ π tools/ # All MCP tool implementations
β β βββ flow-open.js # Navigate to Flow
β β βββ flow-status.js # Connection status
β β βββ generate-image.js # Image generation
β β βββ generate-video.js # Video generation (setup only)
β β βββ download-latest.js # Download generated files
β β βββ create-character.js # Create a character
β β βββ import-character.js # Import character JSON
β β βββ open-characters.js # List characters
β β βββ create-scene.js # Create a scene
β β βββ open-tools-gallery.js # Open tools gallery
β β βββ grid-architect.js # Batch shot generation
β β βββ discover-ui.js # UI discovery & mapping
β β βββ use-flow-tool.js # Generic tool opener
β β
β βββ π queue/ # Job management
β β βββ job-queue.js # Single-job queue
β β
β βββ π utils/ # Helpers
β βββ config.js # Config loader
β βββ logger.js # Structured logging
β βββ errors.js # Error codes & types
β βββ file-manager.js # File download/save
β βββ screenshots.js # Screenshot capture
β
βββ π output/ # Generated files land hereπ§ Tools
All tools are organized by function for easy discovery.
π Connection & Status
Tool | Description |
| Launch Chrome, connect CDP, navigate to Google Flow |
| Close browser and clean up all connections |
| Full status: connection, Flow loaded, account, queue state |
| Verify logged-in account matches configured email |
| Capture a screenshot of the current Flow page |
π¨ Image Generation
Tool | Description |
| Generate image with Nano Banana Pro, Nano Banana 2, or Imagen 4. Supports aspect ratios, reference images, and brand-based model selection. |
| Download the most recently generated file |
π¬ Video Generation
Tool | Description |
| Set up video generation (Omni Flash, Veo models, custom duration/ratio). β οΈ Stops at "ready to generate" β no credit consumed. |
| Create a video scene with characters and a text prompt |
π€ Characters
Tool | Description |
| Create a new character with name, description, and optional reference images |
| Import a character from a saved JSON file |
| Open the characters page and list all existing characters |
π οΈ Tools & Discovery
Tool | Description |
| Open the tools gallery and browse available tools |
| Open any Flow tool by name with optional parameters |
| Configure Grid Architect for batch shot generation with theme prompts, visual logic, and reference images |
| Discover and map all interactive elements (buttons, inputs, headings) on any Flow page |
π Queue & Monitoring
Tool | Description |
| Check job queue: active job, pending queue, completed and failed history |
βοΈ Configuration
Edit config/flow.config.json (copy from config/flow.config.example.json):
π Essential
Key | Type | Default | Description |
|
| β | Your Google account email β REQUIRED |
|
|
| Chrome profile directory name |
|
| β | Full path to Chrome user data directory β REQUIRED |
|
| Flow labs URL | Google Flow URL (supports |
π§ Advanced
Key | Type | Default | Description |
|
|
| Chrome DevTools Protocol port |
|
|
|
|
|
|
| Run Chrome in headless mode |
|
|
| UI locale ( |
β±οΈ Timing
Key | Default | Description |
|
| Max job execution time |
|
| Delay between UI actions (anti-detection) |
|
| How often to poll for generation completion |
|
| Max polling attempts before timeout |
|
| Wait time for file download |
π¨ Models & Ratios
Key | Description |
| Available models: |
| Available models: |
| Supported aspect ratios: |
π‘οΈ Safety & Ethics
This project is built with safety-first design:
β Principle | How it's enforced |
Your account only | Uses your own Google profile β never asks for or stores passwords |
No credential theft | Never exports cookies, tokens, or session data |
No bypass | Stops cleanly on captcha, login walls, or verification challenges |
No parallel abuse | Single-job queue prevents concurrent generation |
Credit-safe video | Video generation sets up parameters but stops before the final "Generate" click (no credit consumed) |
Config backup | Backs up OpenCode config before any modification |
β οΈ This is a browser automation tool. Use it responsibly and in accordance with Google's Terms of Service.
β FAQ
Getting Started
Open Chrome and go to chrome://version/. The Profile Path shows both your user data directory and profile name. For example:
/home/you/.config/google-chrome/Profile 3βchromeUserDataDir: "/home/you/.config/google-chrome",chromeProfile: "Profile 3"
You need a profile where you're already logged into your Google account.
Yes! Any MCP-compatible client (Claude Desktop, Continue.dev, etc.) can connect to this server. Just point your MCP config to node /path/to/src/index.js.
Troubleshooting
Make sure Chrome is installed at the expected path. On Linux, the default is /opt/google/chrome/chrome. Edit scripts/start-browser.sh to set the correct CHROME path for your system.
The script checks for existing Chrome instances on port 9222. If something else is using that port, you can change cdpPort in config/flow.config.json (and update the script's CDP_PORT variable).
Verify that expectedAccount in config/flow.config.json matches the email logged into your Chrome profile. Use flow_account_check to verify.
Run flow_discover_ui to re-map selectors. The selectors.map.json will auto-update with new UI element positions.
Usage
Your AI agent calls flow_generate_image with a text prompt. Optionally specify model (Nano Banana 2 is default), aspect ratio, and reference images. The server waits for completion and makes the file available for download.
flow_generate_video sets up the video parameters (model, ratio, duration) but stops before clicking Generate. This lets you review the setup before consuming credits. The actual generation requires a paid Google Flow subscription.
π€ Contributing
Contributions are welcome! Please follow these guidelines:
Fork the repository
Create a feature branch (
git checkout -b feature/my-feature)Commit your changes (
git commit -m 'Add my feature')Push to the branch (
git push origin feature/my-feature)Open a Pull Request
π License
MIT Β© TMSSS05
Available Tools
17 toolsflow_account_checkB
Verify the logged-in Google account matches the configured expected email (Profile 3).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It describes the action as 'Verify', suggesting a read-only operation, but does not disclose behavioral traits such as what happens on mismatch, error handling, or whether it modifies state. This leaves significant ambiguity for a tool with no structured behavioral hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is clear, front-loaded, and contains no unnecessary words. It earns its place with direct purpose statement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description is minimally complete for the purpose. However, it does not explain what 'Profile 3' refers to, nor does it describe the return value (e.g., boolean, success/failure message). Additional context would improve completeness for an agent that needs to interpret the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters and schema description coverage is 100%, so the baseline is 4. The description does not need to add parameter details, and it successfully implies that no input is required. It adds no extra semantics but does not detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: verifying that the logged-in Google account matches a configured expected email, specifically mentioning 'Profile 3'. The verb 'Verify' and resource 'Google account match' are specific, making the purpose clear. However, it does not differentiate from sibling tools that might have similar verification tasks, though no such sibling is evident.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the usage context (checking account match), but it does not explicitly state when to use this tool versus alternatives, nor does it provide when-not guidance. The sibling tools do not include similar verification, so the intended use is inferred but not explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_connectA
Launch Chrome with the configured Google profile, connect CDP, navigate to Google Flow, and verify account.
| Name | Required | Description | Default |
|---|---|---|---|
| headless | No | Launch in headless mode (not recommended, Google Flow needs visible browser). | |
| open_flow | No | Auto-navigate to Google Flow after connection. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that headless mode is not recommended and lists the sequence of actions (launch, connect, navigate, verify). However, it does not mention side effects like opening a visible browser window or potential need for user authentication, which would enhance transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the tool's purpose and key actions without extraneous detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should specify what 'verify account' returns (e.g., success, error, connection status). The lack of information about output or side effects makes it incomplete for an AI agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with descriptions for both parameters. The description adds value by clarifying the 'headless' default and the profile usage, but does not significantly extend beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific actions: launching Chrome, connecting CDP, navigating to Google Flow, and verifying account. This effectively distinguishes it from sibling tools like flow_disconnect or flow_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for initial setup before using other flow tools, but provides no explicit guidance on when to use it versus alternatives, nor when not to use it. A mention of prerequisites or ordering would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_create_characterC
Create a new character in Google Flow Characters with name and description.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Character name. | |
| description | Yes | Character description/prompt. | |
| reference_images | No | Paths to reference images for character design. | |
| project_name | No | Name for the project (will reuse existing project with same campaign, or create new). | |
| campaign | No | Campaign identifier for project matching (e.g., "ete-2026", "nouvelle-collection"). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behaviors. It only states 'create', implying mutation, but no details on side effects, authorization needs, uniqueness constraints, or error states. The description is too minimal for a create operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant information. It is front-loaded with the core action. However, it could be improved by adding context about the optional parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, no output schema, and no annotations, the description is minimal. It does not explain the role of 'project_name' and 'campaign' in project matching or the expected return value. The description is incomplete for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description only mentions 'name and description' and adds no extra meaning for 'reference_images', 'project_name', or 'campaign'. Baseline 3 applies since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create') and the resource ('a new character in Google Flow Characters'). It mentions the required parameters 'name and description'. However, it does not differentiate from sibling tool 'flow_import_character', which likely has a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'flow_import_character' or 'flow_create_scene'. There is no mention of prerequisites, limitations, or complementary tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_create_sceneB
Create a new scene in Google Flow Scenes with characters and prompt.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | Scene description/prompt. | |
| characters | No | Character names to include in the scene. | |
| project_name | No | Name for the project (will reuse existing project with same campaign, or create new). | |
| campaign | No | Campaign identifier for project matching (e.g., "ete-2026", "nouvelle-collection"). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only says 'create a new scene' without explaining side effects, idempotency, permissions, or success/failure behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but lacks structure and critical details. It is not well-rounded for the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 4 parameters (all described in schema), no output schema, and no annotations, the description is too brief. It fails to explain return values, error handling, or how to effectively use the tool among 16 siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema; it merely mentions characters and prompt without elaborating on usage or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Create' and the resource 'scene', and distinguishes from sibling 'flow_create_character' by specifying scene creation with characters and prompt.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when or when not to use this tool, no mention of alternatives (e.g., when to use flow_create_character instead), and no context on prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_disconnectA
Close the browser and clean up the MCP connection to Google Flow.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It explicitly states that the tool will close the browser and clean up the MCP connection, which is sufficiently transparent about its side effects. It could mention potential data loss risks, but for a disconnect tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. Every word is necessary and contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has no parameters, no output schema, and no annotations, the description is reasonably complete. It explains the core action. It could benefit from mentioning that this is the reverse of flow_connect, but the sibling names provide that context implicitly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters and schema coverage is 100% (empty schema). The description adds meaning beyond the schema by explaining what the tool does overall. With no parameters, a baseline of 4 is appropriate, and the description delivers clear context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Close the browser and clean up the MCP connection to Google Flow.' It specifies the verb 'close' and the resource (browser and connection). Among siblings, flow_connect is the obvious counterpart, so it's well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as the complement to flow_connect but provides no explicit when-to-use, when-not-to-use, or alternative guidance. The context signals show a sibling flow_connect, which gives some implicit context, but the description itself lacks explicit guidelines.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_discover_uiA
Navigate to a Google Flow page and discover all interactive elements (buttons, inputs, links, headings). Updates the internal selectors map for robust automation.
| Name | Required | Description | Default |
|---|---|---|---|
| page | Yes | Page to discover. Options: main, image-generation, video-generation, characters, scenes, tools-gallery, grid-architect. | main |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the key behavioral trait of updating an internal selectors map for robust automation, which is important for understanding side effects. However, it does not specify authorization needs or potential destructive actions, but the absence of annotations places the burden on the description, which it meets reasonably well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the purpose. It is efficient with no wasted words, but could benefit from a brief structure break for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one required parameter and no output schema, the description adequately covers what the tool does and its main side effect. It would be improved by mentioning the output (e.g., 'Returns the discovered selectors' or 'Updates the map silently').
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the page parameter described in the schema. The description does not add any extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool navigates to a Google Flow page and discovers interactive elements, with the specific verb 'Navigate' and resource 'Google Flow page'. It distinguishes from sibling tools like flow_open_characters by focusing on discovering UI elements rather than just opening pages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for discovering interactive elements for automation but lacks explicit guidance on when to use this tool versus alternatives like flow_open_characters or flow_open_tools_gallery. No exclusion criteria or alternative suggestions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_download_latestB
Download the most recently generated file from Google Flow.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must clarify behavior. It states 'download' implying a read operation, but fails to disclose what happens if no file exists, whether it's a single download or can be called multiple times, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with clear verb-first structure. Every word is necessary, no wasted content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple parameterless tool, the description is mostly adequate but omits important context like the possibility of no file, expected return format, and relation to other flow tools. Additional context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has zero parameters with 100% coverage, so baseline is 4. The description adds meaning by specifying 'most recently generated', which reduces ambiguity beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'download' and the resource 'most recently generated file' from 'Google Flow'. It distinguishes from sibling tools like generation tools, but could be more specific about the scope of 'most recently generated'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, nor prerequisites like ensuring a file has been generated. The description lacks context for proper selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_generate_imageA
β οΈ CES IMAGES CONSOMMENT DES CRΓDITS. Par dΓ©faut (auto_confirm=false): remplit le prompt, sΓ©lectionne le modΓ¨le/ratio, prend un screenshot et retourne "ready_for_confirmation". NE clique PAS sur Generate. Quand auto_confirm=true: vΓ©rifie d'abord que l'interface est bien en mode IMAGE (pas VidΓ©o), que le modΓ¨le est un modΓ¨le image, prend un screenshot de vΓ©rification, PUIS clique Generate, attend les images et les tΓ©lΓ©charge. NAN/BANANA modΓ¨les image seulement.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The text prompt for image generation. | |
| model | No | Model to use: Nano Banana Pro, Nano Banana 2, or Imagen 4. | Nano Banana 2 |
| auto_confirm | No | β οΈ CRΓDITS. Si false (dΓ©faut): prΓ©pare seulement, ne consomme rien. Si true: vΓ©rifie que le mode Image est actif, PUIS clique Generate (consomme des crΓ©dits). | |
| ratio | No | Aspect ratio: 1:1, 16:9, 9:16, 4:3, 3:4. | 1:1 |
| reference_images | No | Paths to reference images (optional). | |
| brand | No | Brand context for automatic model selection: premium, standard. | |
| project_name | No | Name for the project (will reuse existing project with same campaign, or create new). | |
| campaign | No | Campaign identifier for project matching (e.g., "ete-2026", "nouvelle-collection"). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fully discloses behavior: for auto_confirm=false, it fills prompt, selects model/ratio, takes screenshot, returns 'ready_for_confirmation'. For auto_confirm=true, it verifies interface mode, model, takes verification screenshot, then clicks Generate, waits, and downloads. Warns about credit consumption. No annotations to contradict.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but every sentence provides necessary detail. It front-loads the credit warning and uses bullet-like structure with punctuation. Some redundancy could be trimmed, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, no output schema), the description comprehensively covers behavior, prerequisites, side effects (credit consumption), and distinguishes between preparation and execution modes. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds credit warning for auto_confirm and context for brand and project_name, but most parameters are already well-described in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates images, with specific verb 'generate' and resource 'image'. It distinguishes between two modes (preparation vs. execution) and implicitly differentiates from video generation by mentioning checking for IMAGE mode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit usage guidance: auto_confirm=false prepares only, no credit consumption; auto_confirm=true executes generation and consumes credits. Also instructs to verify mode is IMAGE, not Video, and that model must be an image model.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_generate_videoA
Set up a video generation in Google Flow. Fills prompt, selects Omni Flash or Veo model, configures settings. NOTE: Does NOT click final Generate (paid feature β stops at ready-to-generate).
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The text prompt for video generation. | |
| model | No | Model: Omni Flash, Veo 2, Nano Banana 2. | Omni Flash |
| ratio | No | Aspect ratio: 16:9, 9:16, 1:1. | 16:9 |
| duration | No | Target duration in seconds. | |
| reference_images | No | Paths to reference images (optional). | |
| project_name | No | Name for the project (will reuse existing project with same campaign, or create new). | |
| campaign | No | Campaign identifier for project matching (e.g., "ete-2026", "nouvelle-collection"). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool stops at 'ready-to-generate' and does not execute the paid generation, which is a key behavioral trait. It does not cover rate limits or auth, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no extraneous content. The first states the purpose, the second provides a critical caveat. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters and no output schema, the description covers the essential behavioral context. It could optionally explain project reuse logic, but the schema already describes that. Overall, it provides adequate completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond summarizing what the schema already provides ('fills prompt, selects Omni Flash or Veo model, configures settings'). No additional parameter meaning is given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action 'Set up a video generation in Google Flow' with specific verb and resource. It differentiates from siblings like flow_generate_image by specifying video generation, and includes a critical behavioral note about not clicking final Generate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The note explicitly states what the tool does NOT do (final Generate is a paid feature), guiding appropriate use. However, it does not mention alternatives or when to use siblings, so guidance is slightly incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_import_characterB
Import a character from a saved JSON file into Google Flow.
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | Path to character JSON file. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It implies mutation but does not state if it overwrites existing characters, authentication needs, or error handling. The description is too brief to cover these aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundant words. Front-loaded with action and object. However, it could include more context without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description is adequate but lacks details on JSON format, validation, success/failure behavior, and contrast with sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one parameter with minimal description 'Path to character JSON file.' Description adds 'saved JSON file' but no additional details on format or valid values. Schema coverage is 100%, so baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool imports a character from a JSON file into Google Flow. The verb 'import' and resource 'character' are specific, and it distinguishes from the sibling 'flow_create_character' which likely creates from scratch.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'flow_create_character'. No prerequisites, conditions, or scenarios are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_open_charactersA
Open the Google Flow Characters page and list existing characters.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description suggests a read-only operation (open and list) but does not explicitly state the absence of side effects or authentication requirements. With no annotations, this is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, efficient and front-loaded with the key action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description covers the basic functionality. However, it lacks context about prerequisites or expected output format, which could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and the schema coverage is 100%. The description is not required to add parameter details, so baseline score of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: opening a specific page and listing existing characters. It effectively distinguishes from sibling tools like flow_create_character and flow_import_character.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when you need to view existing characters, but does not provide explicit guidance on when to use this tool versus alternatives like flow_discover_ui or flow_create_character.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_open_tools_galleryB
Open the Google Flow Tools Gallery and list available tools.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It does not disclose if the tool is read-only, modifies state, or has any side effects. The phrase 'Open the Google Flow Tools Gallery' suggests a UI action but no details on behavior or requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no extraneous words. It is concise and front-loaded, but could be slightly more informative without adding bulk.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description is adequate but minimal. It does not explain 'list available tools' (e.g., whether it returns text or opens a UI) or how this fits with sibling tools. Some context is missing for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema coverage is 100%. The description adds minimal additional meaning beyond the name, but with zero parameters it is acceptable. Baseline 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('open' and 'list') and the specific resource ('Google Flow Tools Gallery'). It is specific but does not explicitly differentiate from sibling tools like 'flow_discover_ui' which may serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives or any prerequisites. The description lacks context for decision-making, such as whether this tool should be used before other actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_queue_statusA
Check the job queue: active job, pending queue, completed and failed job history.
| Name | Required | Description | Default |
|---|---|---|---|
| history_limit | No | Number of recent history entries to return. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry the burden. It implies a read-only operation (checking), which is sufficient. However, it does not disclose any other behavioral traits (e.g., rate limits, side effects).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, front-loaded sentence. Every word adds value; no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, no annotations. Description covers the basic purpose but lacks details on return format, error responses, or prerequisites. Adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (history_limit has description). The tool description does not add further meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'check' and resource 'job queue', listing the components (active, pending, completed, failed). This distinguishes it from siblings like 'flow_status' which likely covers general status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'flow_status' or 'flow_connect'. The description does not specify scenario-based usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_screenshotB
Take a screenshot of the current Google Flow page.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Custom name for the screenshot file. | manual |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description bears full responsibility for behavioral disclosure. It mentions 'current Google Flow page' but does not clarify if the screenshot captures the full page or viewport, whether it is destructive, or any permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-front-loaded sentence with no waste. However, it omits potentially useful details, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description is too bare. It does not specify the output format, return value, or any side effects, leaving significant gaps for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (one parameter with description). The description does not add meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'take', the resource 'screenshot', and the context 'current Google Flow page'. It is specific and distinguishes this tool from siblings, none of which are screenshot-related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., other tools for capturing visual output). There are no conditions, prerequisites, or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_statusA
Check current connection status: browser connected, Flow page loaded, account verified, job queue state.
| Name | Required | Description | Default |
|---|---|---|---|
| full | No | Return full status with screenshot. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers key behavioral aspects: it checks multiple status components. It does not mention side effects or authentication, but for a read-only status tool, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with the action and specific items, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one optional parameter and no output schema, the description adequately explains the tool's purpose and checks. Minor gap: no mention of return format, but acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema already describes the 'full' parameter. The tool description adds no extra parameter detail, meeting baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks connection status and lists specific items: browser connected, Flow page loaded, account verified, job queue state. It distinguishes from siblings like flow_queue_status and flow_account_check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates the tool is for checking current status, but lacks explicit when-to-use or when-not-to-use guidance and does not mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_use_grid_architectA
Open Grid Architect in Google Flow, fill theme prompt, shot prompts, engine, ratio, and visual logic settings. Supports batch shot generation for brand campaigns.
| Name | Required | Description | Default |
|---|---|---|---|
| theme_prompt | Yes | Overall theme prompt for the grid. | |
| shot_prompts | No | Array of individual shot prompts for the grid. | |
| engine | No | Engine/model for the grid. | Nano Banana 2 |
| ratio | No | Aspect ratio for all shots. | 16:9 |
| visual_logic | No | Visual logic type: None, Colour Pop, Side by Side, etc. | |
| references | No | Paths to reference images. | |
| project_name | No | Name for the project (will reuse existing project with same campaign, or create new). | |
| campaign | No | Campaign identifier for project matching (e.g., "ete-2026", "nouvelle-collection"). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It mentions 'open' and 'fill' but doesn't disclose whether this modifies state, requires authentication, or has side effects like creating projects. The behavior of opening an external app (Grid Architect) is hinted but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. The first sentence front-loads the core action and settings, the second adds the purpose. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 parameters and no output schema, the description lacks critical context: return value, error handling, prerequisites (e.g., must be in a project), and whether it is idempotent. It mentions 'supports batch shot generation' but doesn't explain the flow or results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description lists several parameters (theme_prompt, shot_prompts, engine, ratio, visual_logic) but misses references, project_name, and campaign. It adds value by framing them as settings for batch generation, but doesn't go beyond the schema's own descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool opens Grid Architect and fills specific settings (theme, shots, engine, ratio, visual logic). It specifies batch shot generation for brand campaigns, distinguishing it from siblings like flow_generate_image that likely handle single images.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use for batch shot generation in brand campaigns. While it doesn't explicitly list alternatives or when-not-to-use, the sibling tool names imply single-image generation (flow_generate_image) and generic tool usage (flow_use_tool), giving enough guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flow_use_toolC
Open any tool by name in Google Flow and optionally fill its configuration parameters.
| Name | Required | Description | Default |
|---|---|---|---|
| tool_name | Yes | Name of the tool to open (e.g. Grid Architect, Image Generation). | |
| params | No | Optional configuration parameters for the tool. | |
| project_name | No | Name for the project (will reuse existing project with same campaign, or create new). | |
| campaign | No | Campaign identifier for project matching (e.g., "ete-2026", "nouvelle-collection"). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether opening a tool executes it, requires authentication, or has side effects. The agent is left guessing about the tool's actual impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it omits important context that would justify its brevity, making it underspecified rather than efficiently informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of opening 'any tool' and the lack of output schema or annotations, the description fails to explain return values, execution behavior, or how the tool fits into the overall workflow. It is insufficient for an agent to use reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all four parameters, so the description adds little beyond stating that params are optional. The mention of 'optionally fill its configuration parameters' aligns with the schema but provides no additional meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Open' and the resource 'any tool by name in Google Flow', and it distinguishes from sibling tools by being a generic tool opener. However, 'open' could be interpreted as merely opening the UI rather than executing the tool, which slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus the more specific sibling tools (e.g., flow_use_grid_architect, flow_generate_image). The description does not specify prerequisites, when not to use it, or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Most tools have distinct purposes (connection, character/scene management, generation, UI), but flow_generate_image and flow_generate_video could be confused if descriptions are skimmed. flow_use_tool is generic but still differentiated.
All tools follow a strict 'flow_verb_noun' pattern with snake_case, e.g., flow_create_character, flow_generate_image. Naming is highly consistent and predictable.
17 tools is appropriate for the scope of browser automation over Google Flow, covering connection, state management, content creation, and generation. Slightly on the higher side but well-justified.
Core CRUD for characters (create, import, list) but missing update/delete. No tools for scene management beyond creation. Video generation stops before final action, leaving a gap. UI discovery and queue status are nice extras.
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