mcp-relight-harmonize

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synthesize_diffusion_prompt

Generate photorealistic diffusion prompts for GPT Image or Nano Banana from an image's optical analysis. Outputs calibrated denoising parameters and lighting directives for external AI generators.

Instructions

Synthesize precision enhancement and relighting diffusion prompts based on physical optical analysis of an image, tailored specifically for GPT Image (DALL-E 3 / GPT-4o) and Nano Banana. Outputs photorealistic prompts with physical keywords (exact Kelvin CCT, 3D light angles, volumetric dust rays, contact shadows) and calibrated denoising parameters (0.35 - 0.45).

• Purpose: Generative AI prompt synthesis. Unlike 'generate_relight_variations' which creates image files locally, this tool translates optical geometry into targeted text prompts and hyperparameter sets for external diffusion generators. • Behavior: Completely read-only, deterministic, zero filesystem modifications, no network calls, and no authentication required. • When to use: Use when you want to feed photorealistic lighting directives or inpainting prompts into GPT Image or Nano Banana. • When NOT to use: Do NOT use if you need local image rendering without an external AI model (use 'generate_relight_variations'), or if merging cutouts locally (use 'harmonize_composite'). • Alternatives: Use 'generate_relight_variations' for instant offline image files, or 'analyze_optical_profile' for raw numerical statistics.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`image_path`	Yes	Path to the local reference image (.png, .jpg, .jpeg) to extract optical geometry from.
`user_intent`	No	Optional creative context or scenario description (e.g., 'golden sunset portrait', 'cyberpunk studio product').
`target_model`	No	Target generative engine: 'gpt_image' (outputs natural descriptive studio directives with 85mm prime lens and physical illumination) or 'nano_banana' (outputs dense tokenized optical shaders, roughness index, raytraced bounce, and ground contact shadow). Defaults to 'gpt_image'.	gpt_image

Output Schema

TableJSON Schema

Name	Required	Description
`data`	Yes
`status`	Yes	Execution status.
`summary`	Yes	Human-readable executive summary of the operation.
`evidence`	Yes
`warnings`	Yes	Non-fatal warnings if applicable.
`nextActions`	Yes	Actionable follow-up guidance.

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedv1.0.2Sep 13, 2026

changedInput schema / properties / image_path / description

Previous value: -"Path to the reference image."New value: +"Path to the local reference image (.png, .jpg, .jpeg) to extract optical geometry from."

changedInput schema / properties / target_model / description

Previous value: -"Target engine: 'gpt_image' (GPT Image) or 'nano_banana' (Nano Banana)."New value: +"Target generative engine: 'gpt_image' (outputs natural descriptive studio directives with 85mm prime lens and physical illumination) or 'nano_banana' (outputs dense tokenized optical shaders, roughness index, raytraced bounce, and ground contact shadow). Defaults to 'gpt_image'."

addedInput schema / properties / user_intent / default
```
Added value: +""
```

changedInput schema / properties / user_intent / description

Previous value: -"Creative intent (e.g. 'golden sunset', 'studio commercial')."New value: +"Optional creative context or scenario description (e.g., 'golden sunset portrait', 'cyberpunk studio product')."

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "data": {
+      "properties": {
+        "enhancementPrompt": {
+          "description": "Prompt for micro-surface detail and lens clarity upgrade.",
+          "type": "string"
+        },
+        "opticalKeywordsUsed": {
+          "items": {
+            "type": "string"
+          },
+          "type": "array"
+        },
+        "recommendedParameters": {
+          "description": "Calibrated diffusion settings (denoising 0.35-0.45, etc.).",
+          "type": "object"
+        },
+        "relightingPrompt": {
+          "description": "Prompt for physical relighting with angles, CCT, and contact shadows.",
+          "type": "string"
+        },
+        "targetModel": {
+          "enum": [
+            "GPT Image",
+            "Nano Banana"
+          ],
+          "type": "string"
+        },
+        "userIntent": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "targetModel",
+        "userIntent",
+        "enhancementPrompt",
+        "relightingPrompt",
+        "recommendedParameters",
+        "opticalKeywordsUsed"
+      ],
+      "type": "object"
+    },
+    "evidence": {
+      "properties": {
+        "artifacts": {
+          "items": {
+            "properties": {
+              "label": {
+                "type": "string"
+              },
+              "uri": {
+                "type": "string"
+              }
+            },
+            "required": [
+              "label"
+            ],
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "inputsDigest": {
+          "description": "SHA-256 digest of input parameters.",
+          "type": "string"
+        },
+        "sources": {
+          "items": {
+            "properties": {
+              "label": {
+                "type": "string"
+              },
+              "uri": {
+                "type": "string"
+              }
+            },
+            "required": [
+              "label"
+            ],
+            "type": "object"
+          },
+          "type": "array"
+        }
+      },
+      "type": "object"
+    },
+    "nextActions": {
+      "description": "Actionable follow-up guidance.",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "status": {
+      "description": "Execution status.",
+      "enum": [
+        "success",
+        "partial",
+        "blocked",
+        "failed"
+      ],
+      "type": "string"
+    },
+    "summary": {
+      "description": "Human-readable executive summary of the operation.",
+      "type": "string"
+    },
+    "warnings": {
+      "description": "Non-fatal warnings if applicable.",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "status",
+    "summary",
+    "data",
+    "warnings",
+    "evidence",
+    "nextActions"
+  ],
+  "type": "object"
+}

First observedv0.1.1Sep 13, 2026

TDQS

A4.6/5.0

Behavior5/5

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

With no annotations at all, the description carries the full burden and discharges it: read-only, deterministic, zero filesystem modifications, no network calls, no authentication required. It also discloses the output shape (photorealistic prompt text plus calibrated denoising parameters 0.35-0.45), which is behavioral context beyond a plain read.

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

Conciseness4/5

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

Front-loaded with the core purpose, then cleanly bulleted by Purpose/Behavior/When-to-use/Alternatives. Slightly verbose and partly restates schema-level enum detail, but no sentence is wasted and the structure is easy to scan.

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

Completeness5/5

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

For a 3-parameter, read-only synthesis tool with an output schema present, the description supplies everything an agent needs: purpose, side-effect profile, selection criteria, and sibling routing. Return-value explanation is unnecessary given the output schema.

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 description coverage is 100%, so image_path, user_intent, and target_model are already documented with examples and enum semantics in the schema. The description reinforces the output character for each target model but adds little parameter syntax or format detail beyond what the schema already provides; baseline 3 applies.

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?

States a specific verb (synthesize) and resource (diffusion prompts from physical optical analysis) and names the target engines. It explicitly distinguishes itself from siblings such as generate_relight_variations and analyze_optical_profile, so an agent can route without opening any schema.

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?

Provides explicit 'When to use', 'When NOT to use', and 'Alternatives' sections naming concrete siblings for each condition (generate_relight_variations for local rendering, harmonize_composite for local merging, analyze_optical_profile for raw stats). Nothing is left to inference.

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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