reproduce
Un-flatten a flat design image into editable layers and reproduce it bit-perfect, returning the fidelity score. Returns: A JSON string with a bit_perfect flag and fidelity metrics (mae, psnr, exact-match %, stray px).
This record as markdown: /tools/design-reprise-reprise/reproduce.md
What reproduce does on Reprise
AI agents invoke reproduce to trigger actions in Reprise. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
image | string | — | The source design image as an http(s) URL or a base64 data URL. |
Parameters from the server's own tool schema.
Why reproduce is rated High
The tool performs a non-trivial computational operation (image analysis, layer decomposition, and reproduction) that goes beyond simple data retrieval or storage write. It executes an image processing pipeline and returns derived metrics. It does not irreversibly delete data, move money, or merely read existing records — it actively transforms and reproduces an artifact, classifying it as Execute.
From the tool's definition 'Un-flatten a flat design image into editable layers and reproduce it bit-perfect' — triggers an external operation (image processing/layer decomposition) and returns computed fidelity metrics; 'reproduce it bit-perfect' implies running a generation/rendering…
Attacks that exploit this kind of access
The rule that runs reproduce safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Reprise, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For reproduce, this is the rule to start with:
reproduce stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Reprise, apply this rule, and every reproduce call is checked against it from then on.
Questions about reproduce
Un-flatten a flat design image into editable layers and reproduce it bit-perfect, returning the fidelity score. Returns: A JSON string with a bit_perfect flag and fidelity metrics (mae, psnr, exact-match %, stray px). It is categorised as a Execute tool in the Reprise MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
reproduce accepts 1 parameter: image. The full parameter table on this page comes from the server's own tool schema.
Register the Reprise MCP server in PolicyLayer and add a rule for reproduce: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Reprise. Nothing to install.
reproduce is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the reproduce rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for reproduce. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
reproduce is provided by the Reprise MCP server (https://tepesama-reprise-mcp.hf.space/gradio_api/mcp/http). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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