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

No annotations are provided, so the description carries the full burden. It only says 'Verify' but does not disclose what happens on success/failure, whether it returns a boolean, throws an error, or has side effects. For a check tool, this lack of behavioral detail is a significant gap.

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 with leading verb and no fluff. It conveys the core purpose efficiently without wasting 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 the tool is simple with no parameters and no output schema, the description is partially complete. It explains what it does but not what the agent should expect as a result (e.g., does it return a Boolean, throw an exception, or print a message?). The mention of 'Default' also lacks context about how the expected email is configured, leaving some ambiguity.

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 zero parameters, so the description does not need to explain any. The baseline for 0 params is 4, and the description correctly avoids adding unnecessary parameter details since the schema is empty.

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 a specific action (verify) and the exact subject (logged-in Google account) against an expected configured email. This distinguishes it from sibling tools like flow_status or flow_connect, which have different purposes.

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 tool is used to ensure the correct Google account is active, but it does not explicitly state when to use it versus alternatives. For example, it doesn't mention using it after flow_connect or before other operations. Usage context is implied rather than stated.

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

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

With no annotations, the description carries the burden. It discloses the main side effect (launching Chrome) and the steps performed, but lacks detail on whether the connection is persistent, what happens on verification failure, or whether the browser closes after the operation. This is moderate transparency but not complete.

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 packs four specific actions without fluff. It is front-loaded with the primary action ('Launch Chrome') and efficiently communicates the full flow.

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?

The description does not mention return values (no output schema exists) or the fact that this tool likely establishes a required connection for other flow_* tools. Without annotations, it could benefit from noting that it is a prerequisite and what 'verify account' entails. This is adequate but not fully 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%: both 'headless' and 'open_flow' have clear descriptions in the schema, including a warning about headless mode. The tool description does not add additional parameter semantics, but since the schema already covers them, a baseline score of 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 tool's specific actions: launching Chrome, connecting CDP, navigating to Google Flow, and verifying the account. It distinguishes itself from sibling tools like flow_disconnect or flow_status by focusing on the connection setup.

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 does not provide explicit guidance on when to use this tool relative to alternatives. It implies it is a connection step but does not mention prerequisites, exclusions, or alternative tools. For example, it does not clarify whether this should be run before flow_status or flow_discover_ui.

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

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

With no annotations provided, the description carries the burden of disclosure. It transparently explains the default auto_confirm behavior (filling description, clicking submit, renaming 'Untitled Character') and hints at a non-submitting mode (via the 'By default' clause), adding useful context beyond the schema.

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, front-loaded with the core purpose, and every clause adds value. No fluff or redundancy.

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?

The tool has 6 parameters and no output schema, yet the description does not mention expected return values or outcomes (beyond an implicit rename). It covers the main creation flow but omits details about reference images, project matching, or what the agent should do with the result. This leaves some gaps for agents needing full context.

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 meaningful context for the auto_confirm parameter by explaining the default flow (clicks submit, renames), complementing the schema's terse description. This justifies a 4.

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 creates a new character in Google Flow Characters, with specific verb (create) and resource (character), and distinguishes it from siblings like flow_import_character and flow_generate_image.

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 (when you want to create a character) but does not explicitly state when not to use it or provide alternatives. It lacks direct comparison with related tools like flow_import_character.

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

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

No annotations are provided, so the description must disclose side effects and requirements. It only says 'create a new scene' without mentioning that it may reuse or create a project, require existing characters, or any other behavioral details. The schema description for project_name suggests reuse logic, but the description itself does not convey this.

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 waste. It immediately states the action and resource, making it easy to scan.

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 4 parameters, no annotations, and no output schema, the description is too minimal. It fails to explain the campaign/project matching logic, character requirements, or the meaning of a 'scene'. The schema provides some parameter-level detail but not the overall tool behavior or expected outcomes.

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 covers all parameters with descriptions, so the baseline is 3. The description's mention of 'characters and prompt' merely echoes the schema and adds no additional semantic meaning beyond what is already documented.

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 scene in Google Flow Scenes'), and mentions key inputs ('characters and prompt'). It is specific enough to distinguish from sibling tools like flow_create_character or flow_generate_image.

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 no guidance on when to use this tool versus alternatives, no mention of prerequisites (e.g., characters must exist), and no exclusions. It lacks any usage context beyond the basic action.

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

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

With no annotations, the description declares the primary actions (closing browser, cleaning up connection) but does not disclose side effects such as terminating active sessions or preventing further operations. This is adequate for a simple cleanup tool but lacks deeper behavioral context.

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 directly states the tool's function without unnecessary words. It is perfectly concise and front-loaded.

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 parameterless tool with no output schema or annotations, the description provides the essential information about its role as a disconnect/cleanup operation. It lacks explicit usage context but is otherwise complete for its simplicity.

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 zero parameters and an empty schema, so the description adds nothing about parameters. Since there are no parameters to explain, the baseline 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 uses specific verbs 'Close' and 'clean up' to describe the resource (browser and MCP connection), clearly indicating this is the teardown counterpart to flow_connect. It distinguishes itself from sibling tools by its focus on disconnection and cleanup.

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 does not explicitly state when to use the tool or contrast it with alternatives like flow_connect. Usage must be inferred from the name and context, so the agent receives no direct guidance.

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

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

The description discloses a behavioral trait: it updates the internal selectors map as a side effect, which is useful context beyond the tool's primary action. However, with no annotations provided, the description carries the full burden but does not mention authentication requirements, failure modes, or rate limits. This partial transparency warrants a mid-range score.

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 exactly two sentences with no unnecessary words. The first sentence states the action and scope, while the second explains the side effect. This is concise, front-loaded, and every sentence 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 the rich schema that explains pages and overrides, the description is largely complete. It states the purpose and side effect, which is sufficient for an agent to understand the tool's typical use. However, it lacks explicit prerequisites (e.g., needing a connection via flow_connect) and error behavior, leaving some contextual 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 description coverage is 100% according to the context signals, meaning all four parameters are thoroughly documented in the schema, including the detailed page options and url override. The tool description itself adds no parameter-level detail, but the baseline of 3 is appropriate when the schema already covers parameters comprehensively.

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 navigates to a Google Flow page and discovers all interactive elements (buttons, inputs, links, headings), and updates the internal selectors map. This is a specific verb+resource combination that clearly distinguishes it from sibling tools like flow_screenshot or flow_open_characters.

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 no explicit guidance on when to use this tool versus alternatives. It implies a setup step for automation ('Updates the internal selectors map for robust automation') but does not mention exclusions, prerequisites, or alternative tools. Sibling tools such as flow_connect and flow_screenshot exist, but no direct comparison is offered.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states select 'most recently generated' but does not explain whether the file is returned as content, a URL, or saved locally, nor any side effects or permissions.

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 filler. It is front-loaded with the main action and resource, making it highly concise and easy to process.

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 tool with no output schema and no annotations, the description is incomplete. It does not specify what the agent should expect as a result (file path, binary content, URL) or how this tool fits into the flow with sibling generation tools (e.g., used after flow_generate_image).

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, so the description need not elaborate on parameter meaning. The description implicitly communicates that no user input is required, aligning with the baseline for a parameterless tool.

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 uses a specific verb 'Download' and a clear resource 'the most recently generated file from Google Flow.' It distinguishes itself from sibling tools (e.g., flow_generate_image, flow_connect) by being the only download-focused tool.

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, prerequisites, or typical usage contexts. The description simply states the action without explaining when it is appropriate or what conditions must exist (e.g., a file must have been generated first).

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

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

With no annotations, the description fully discloses behavior: it explains credit consumption, the default non-destructive preparation flow, and the verification steps before clicking Generate. It also notes the model restriction and screenshot behavior. This is highly 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?

The description is appropriately sized for the complexity, front-loaded with a credit warning. It uses structured phrasing to explain both modes, with no wasted words. Each sentence contributes to understanding the tool's behavior.

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 10-parameter tool with no annotations or output schema, the description covers the essential behavior, constraints, and credit implications. It could be more specific about return values or error handling, but the core operation is well explained. The schema covers parameter details, so the description complements it effectively.

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 the baseline is 3. The description adds critical semantics for auto_confirm (no credits by default, verification before generating) and clarifies the overall process. It doesn't explain every parameter, but the schema already does, so the description adds value beyond the schema for the most important behavior.

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 generates images via Flow, distinguishing between default preparation mode and auto-confirm generation mode. It mentions 'NANO/BANANA image models only,' scoping its purpose. The name and description together clearly identify it as an image generation tool, distinct from flow_generate_video.

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 for image generation, with clear context that it works only with NANO/BANANA image models. It contrasts with video mode ('not Video'), indirectly guiding to use flow_generate_video for video. However, it doesn't explicitly name alternatives or provide when-not-to-use conditions.

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

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

With no annotations, the description carries the full burden. It transparently discloses that the tool stops at 'ready-to-generate' and does not trigger the paid feature, which is the most important behavioral trait. It lacks details on side effects like project creation, but the note about the final click is highly valuable.

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 two concise sentences, front-loaded with the purpose and followed by a critical NOTE. Every word earns its place, with no redundancy or irrelevant 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 10 parameters and no output schema, the description plus schema provides sufficient context for an agent to invoke the tool. It covers the main purpose and limitation, and the schema handles parameter details. Minor gap: no mention of project reuse or return behavior, but these are secondary.

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 the baseline is 3. The description adds little beyond the schema: it mentions 'Omni Flash or Veo model' but omits 'Nano Banana 2' listed in the schema, and 'configures settings' is vague. The schema descriptions are more detailed and include cross-tool references like flow_list_mention_options.

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: 'Set up a video generation in Google Flow' with specific actions like filling prompt and selecting model. It distinguishes from sibling flow_generate_image by focusing on video and explicitly noting it does not click 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 description provides clear context for video generation setup and includes a critical caveat about the paid Generate feature. However, it does not explicitly mention alternatives (e.g., use flow_generate_image for images) or when not to use this tool.

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

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the high-level action, without detailing side effects (e.g., overwriting existing characters), validation of the JSON, error handling, or any prerequisites. This is a significant gap for an import tool.

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 filler or redundant information. Every word earns its place, making it highly concise and easy to parse.

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?

The core purpose is clear and the schema covers parameters, but the description lacks usage guidance relative to sibling tools and does not disclose behavioral traits (e.g., whether it overwrites or merges). For a tool with no annotations and no output schema, this is adequate but leaves gaps for an agent deciding between import and create.

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 provides descriptions for all three parameters (campaign, file_path, project_name), giving 100% schema coverage. The description itself adds no parameter-specific detail, so the baseline of 3 is appropriate since the schema handles parameter semantics.

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 uses a specific verb ('Import') with a clear resource ('character') and source/destination ('saved JSON file' into 'Google Flow'). This clearly distinguishes it from siblings like flow_create_character (which creates from scratch) and flow_open_characters (which opens existing characters).

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 when a saved JSON character file exists, but it offers no explicit when-to-use or when-not-to-use guidance, and does not mention alternative tools such as flow_create_character. The context is inferred from the phrase 'saved JSON file' rather than stated directly.

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

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

With no annotations, the description carries the burden of disclosure. It transparently states the side effect of opening Flow's '@' reference popup and reading its options, which goes beyond a generic 'list' description. It does not detail safety permissions, but the read-only nature is inferred and no harmful behavior is hidden.

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 that is both concise and information-dense. It includes the action, target, mechanism, and context without redundancy or filler.

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?

The description sufficiently explains the tool's purpose and behavior for a listing tool. It lacks an explicit return format, but that is partially mitigated by the absence of an output schema and the simplicity of the feature. It is complete enough for an agent to invoke 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 full descriptions for both 'campaign' and 'project_name' (100% coverage). The tool description adds no additional parameter meaning, so the baseline score of 3 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 ('List'), the resource ('images and characters'), and the context ('current project' and 'via @name in an image/video prompt'). It distinguishes this from sibling tools like flow_open_characters by specifying the popup-reading mechanism.

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 on when to use the tool (when needing @name references for image/video prompts) and implies the popup interaction. It does not explicitly name alternatives or exclusions, so it stops short of a 5 but is clear enough for an agent.

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

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

No annotations are provided, so the description carries full burden. It states the tool opens a page and lists characters but does not disclose potential side effects, such as creating a new project if none matches (as implied by the schema's project_name description). Lacks details on permissions or reversibility.

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, front-loaded with action and purpose. 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?

The description is adequate for a simple navigation/listing tool but lacks context on project selection mechanism and output nature. With no output schema or annotations, it could benefit from explaining the relationship between campaign and project_name and whether the list is returned as data.

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 100% coverage, so baseline is 3. The description adds no parameter-specific information; it relies entirely on schema descriptions for campaign and project_name.

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 uses specific verb 'open' and resource 'Characters page', and further clarifies it lists existing characters. This clearly distinguishes it from sibling tools like flow_create_character and flow_import_character, which perform different operations.

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_create_character or flow_import_character. The description implies usage for viewing existing characters but doesn't state exclusions or prerequisites.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does (opens a gallery and lists tools) but does not disclose any side effects, permissions required, or whether it returns data in the response. For a simple tool this might be acceptable, but the lack of explicit behavioral context is a gap.

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, compact sentence with no wasted words. It front-loads the action and resource clearly, making it immediately understandable.

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 (no parameters, no output schema, minimal annotations), the description covers the essential purpose. However, it leaves slight ambiguity about whether 'list available tools' means returning a list in the response or opening a UI gallery. This prevents a perfect score.

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 accepts zero parameters, so the schema coverage is trivially 100%. The baseline for 0 parameters is 4, and the description adds no confusion about parameters. Since there are no parameters to clarify, the description does not need to provide additional semantics.

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 the Google Flow Tools Gallery and lists available tools. This is a specific verb+resource combination that distinguishes it from sibling tools like flow_download_latest or flow_create_scene.

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 for discovering available tools, but does not explicitly state when to use this tool versus alternatives or mention any prerequisites. There are no exclusions or comparisons with siblings, so it relies on the name and context to convey intent.

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

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

No annotations are provided, so the description must convey behavioral traits. It states the action is 'forceful' and targets stuck jobs, implying a destructive/resetting behavior. However, it does not disclose potential side effects (e.g., loss of queued jobs, irreversibility, or required permissions), which are important for a reset 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 two sentences long, with the primary action front-loaded in the first sentence. The second sentence adds valuable usage context without any fluff or redundancy. 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?

For a simple, zero-parameter tool, this description covers the purpose and the specific situation. There is no output schema, and the tool's return behavior is not described, but for a queue reset, the main point is the action itself. A small note about consequences (e.g., pending jobs may be cleared) would make it more complete, but it's adequate as is.

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 zero parameters, and the input schema is an empty object. Per the rubric, 0 params is a baseline of 4. The description correctly implies no configuration is needed, so no additional parameter explanation is necessary.

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 ('Forcefully reset the job queue') and the specific resource (the job queue). It also provides a concrete scenario (job stuck in 'running' state blocking others), which distinguishes it from sibling tools like flow_queue_status that likely just query 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 explicitly states when to use the tool: 'if a job is permanently stuck in "running" state and blocking other generations.' This gives clear context, though it does not mention when not to use it or explicitly name alternatives. Still, the use case is well-defined.

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

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

Since no annotations are provided, the description carries the full burden. It clearly indicates a read-only operation ('Check') and lists the information returned, but it does not disclose any potential side effects, authentication requirements, or details about how history_limit affects results. It is minimally transparent but not deeply descriptive.

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 primary action and enumerates the specific aspects of the queue. There is no wasted information; 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?

For a simple tool with one optional parameter and no output schema, the description adequately captures the main functionality. It names all categories of queue status without needing to explain return values extensively. The only minor gap is not explicitly stating that history_limit controls the number of history entries, but that is already in the schema.

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 provides 100% coverage for the only parameter (history_limit) with a clear description. The tool description does not add additional meaning beyond the schema, but since schema coverage is high, the baseline of 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 uses a specific verb ('Check') and resource ('job queue'), and enumerates the exact information covered (active job, pending queue, completed and failed job history). This clearly distinguishes it from sibling tools like flow_status, which likely covers broader status, and other flow_* tools.

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?

There is no explicit guidance on when to use this tool versus alternatives such as flow_status. The description implies that it is for checking queue information, but it does not state exclusions or mention alternative tools, leaving the agent without clear decision criteria.

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

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

No annotations are provided, so the description carries the full burden of disclosing behavioral details. It only states the action without mentioning where the screenshot is saved, whether it returns a file path, authentication requirements, or any side effects, leaving significant ambiguity for an agent.

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 with no filler, immediately conveying the tool's action. It is appropriately concise and front-loaded, making it easy for an agent to parse.

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 optional param, no output schema, no annotations), the description is minimally adequate but incomplete. It fails to explain what happens after the screenshot is taken (e.g., file location, return value), leaving the agent without enough context to predict the tool's full 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?

The single optional parameter 'name' is fully described in the input schema (100% coverage), so the baseline is 3. The description adds no additional semantic detail about the parameter, but the schema already provides sufficient information.

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 a specific action ('Take a screenshot') on a specific resource ('the current Google Flow page'), making its purpose unambiguous. This distinguishes it from sibling tools like flow_download_latest or flow_create_scene, which serve different actions.

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 does not provide explicit guidance on when to use this tool versus alternatives. However, the intended use is implied by the action itself — taking a screenshot when a visual capture is needed — but no exclusions or alternative comparisons are mentioned.

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

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

With no annotations, the description carries the full burden. It transparently lists the exact status dimensions checked (browser, page, account, queue), which is useful. However, it doesn't disclose whether this is a read-only operation, how the response is structured, or whether it performs live checks or returns cached state.

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 of 12 words, front-loaded with the primary action and resource. Every word adds value, with no redundancy or filler.

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 simplistic status-check tool with one fully described parameter, the description covers core purpose and scope. However, without an output schema or annotations, it omits details about return format, potential latency, and any safety characteristics, leaving the agent uncertain about how 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 schema description fully documents the 'full' parameter ('Return full status with screenshot'), achieving 100% coverage. The tool description adds no parameter-specific context, so the baseline score of 3 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 uses the specific verb 'Check' and clearly enumerates the status components (browser connected, Flow page loaded, account verified, job queue state). It implies a broader scope than individual siblings like flow_account_check or flow_queue_status but does not explicitly name them for differentiation.

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. It doesn't mention that flow_queue_status should be used for queue-only details or flow_connect for establishing a connection. The agent is left without explicit selection criteria.

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

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It says the tool 'open[s]' and 'fill[s]' settings but does not mention side effects, prerequisites, whether it creates or reuses projects, or what the agent should expect after invocation. This leaves significant ambiguity for a UI-automation tool.

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 two sentences and front-loads the primary action. Every phrase earns its place: the resource, the key settings, and the batch campaign use case. No filler or redundancy.

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?

The description captures the main purpose and the batch use case, and the schema fully documents parameters. However, there is no output schema, no annotation, and the description does not state prerequisites, expected outcomes, or side effects. It is minimally sufficient but has clear gaps for a complex UI automation 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%, so the baseline is 3. The description repeats several parameter names (theme prompt, shot prompts, engine, ratio, visual logic) but does not add meaning beyond the schema's own field descriptions, such as campaign reuse behavior or reference image handling.

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 opens with a specific action and resource ('Open Grid Architect in Google Flow') and lists the exact settings it fills (theme prompt, shot prompts, engine, ratio, visual logic). It clearly differentiates from siblings like flow_generate_image by emphasizing batch shot generation for brand campaigns.

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 a clear use case: batch shot generation for brand campaigns. It does not explicitly name alternatives or state when not to use it, but the context strongly implies this tool is for multi-shot Grid Architect workflows rather than single-image generation.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions 'open' and 'fill configuration parameters' but does not explain whether this executes the tool, requires a connection, or affects project state. The presence of campaign and project_name parameters suggests side effects, but they are not explained, making the behavior unclear.

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 immediately states the core function and optional parameter filling. It is front-loaded and contains no redundant information, earning the highest score for 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?

The tool has four parameters and no output schema, so the description should explain the tool-opening flow, how project matching works, and what the user can expect as a result. None of this is present, leaving significant gaps for the agent. The description is too minimal for the complexity of the 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?

The input schema documents all four parameters with a high coverage, so the baseline is 3. The description adds minimal meaning by clarifying that 'params' are configuration parameters and 'tool_name' is the tool's name, but it does not elaborate on campaign or project_name behavior. The schema already covers the basics, so the description does not significantly enhance understanding.

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 that this tool opens any tool by name in Google Flow and optionally fills configuration parameters. This distinguishes it from siblings like flow_generate_image or flow_use_grid_architect, which are specific tool actions. The verb 'open' is slightly ambiguous (whether it executes or navigates), but the overall purpose is clear.

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 phrase 'any tool by name' implies a generic fallback, but it does not explicitly state when to use this tool versus dedicated siblings. No exclusions or alternative recommendations are provided, leaving the usage context only implied.

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