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review_flow

Analyze a user flow for animation quality, transitions, and loading feedback by capturing frame bursts and grading with a vision LLM.

Instructions

Run a scripted user-flow review against a URL. Captures frame bursts after every interaction and asks the vision LLM to grade animation quality, missing transitions, loading-state feedback, choreography, smoothness, and flicker. Use this when the user asks about animations, interaction states, or whether a flow feels good — NOT for static design issues (use review_url for those).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesBase URL for the flow (joined with each step's `navigate`).
nameNoHuman label for the flow (used in artifact filenames). Default: 'flow'.
modelNoModel override.
stepsNoInline DSL: semicolon-separated steps. Actions: navigate <path>, click <selector>, hover <selector>, type <selector>=<value>, press <key>, scroll <px>, wait <ms>, capture "<label>". e.g.: 'navigate /signup; type input#email=ada@example.com; click button[type=submit]; wait 1500; capture "after submit"'.
recordNoRecord the full Playwright video alongside the contact sheet. Default true.
providerNoLLM provider override (auto|ollama|anthropic|openai|google|mock).
spec_pathNoAlternative to `steps`: path to a flow spec JSON file.
consistencyNoSelf-consistency samples (1=off, 3=recommended for harder flows). Default 1.
burst_fullpageNoUse full-page captures in each burst frame (slower; for in-page scroll animations). Default viewport-only.
preferences_pathNoOptional path to a markdown file with team motion preferences. Embedded into the prompt and the report's CC handoff block.
Behavior4/5

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

No annotations are provided, so the description carries full burden. It clearly explains the tool's behavior: capturing frame bursts after each interaction and using a vision LLM to grade multiple aspects. While it doesn't detail potential side effects (e.g., execution time, network usage), it sufficiently communicates the non-destructive, review-oriented nature. Minor improvement could mention that it runs browser actions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: the first sentences states the core function; the second provides usage guidance. It is front-loaded and every word adds value. No extraneous information.

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

Completeness4/5

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

The tool has 10 parameters and no output schema. The description explains the purpose and expected output (grading of animation quality, etc.), which is sufficient for an agent to understand what the tool does. It does not detail return format, but the context of 'grades' implies a report. For a complex tool, this is fairly complete, though mentioning the artifact output could improve clarity.

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

Parameters3/5

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

Schema coverage is 100%, so the baseline is 3. The description does not add parameter-level details but provides overarching context. It does not compensate for any missing schema information, which is unnecessary here due to full coverage. Thus a score of 3 is appropriate.

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

Purpose5/5

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

The description specifies a clear verb ('Run a scripted user-flow review'), resource ('a URL'), and scope ('captures frame bursts... grades animation quality'). It distinguishes itself from the sibling tool 'review_url' by explicitly stating it is for flow/animations, not static design.

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

Usage Guidelines5/5

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

Explicitly states when to use ('when the user asks about animations, interaction states, or whether a flow feels good') and when not to ('NOT for static design issues'), naming the alternative 'review_url'. This provides clear decision guidance.

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

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