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mcp-relight-harmonize

by MarwanDevSpace
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TypeScript
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synthesize_diffusion_prompt

Synthesize physically accurate relighting prompts from image optical analysis, outputting Kelvin color temperatures, 3D light angles, and calibrated denoising parameters for any image generator.

Instructions

Synthesize precision enhancement and relighting diffusion prompts based on physical optical analysis of an image, compatible with Any Image Generator Model (optimized for GEMINI 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 Any Image Generator (optimized for Antigravity). • 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 your Image Generator or Antigravity's generate_image. • 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
NameRequiredDescriptionDefault
image_pathYesPath to the local reference image (.png, .jpg, .jpeg) to extract optical geometry from.
user_intentNoOptional creative context or scenario description (e.g., 'golden sunset portrait', 'cyberpunk studio product').
target_modelNoTarget generative engine format: 'universal' (outputs natural descriptive studio directives with 85mm prime lens and physical illumination compatible with Any Image Generator) or 'nano_banana' (outputs dense tokenized optical shaders for GEMINI Nano Banana). Defaults to 'universal'.universal

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
statusYesExecution status.
summaryYesHuman-readable executive summary of the operation.
evidenceYes
warningsYesNon-fatal warnings if applicable.
nextActionsYesActionable follow-up guidance.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv1.0.5
    • changedInput schema / properties / target_model / default
      Previous value: -"gpt_image"New value: +"universal"
    • changedInput schema / properties / target_model / description
      Previous 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'."New value: +"Target generative engine format: 'universal' (outputs natural descriptive studio directives with 85mm prime lens and physical illumination compatible with Any Image Generator) or 'nano_banana' (outputs dense tokenized optical shaders for GEMINI Nano Banana). Defaults to 'universal'."
    • changedInput schema / properties / target_model / enum
      Previous value: -[
-  "gpt_image",
-  "nano_banana"
-]New value: +[
+  "universal",
+  "nano_banana"
+]
    • addedOutput schema / properties / data / properties / detailedJsonSpecification
      Added value: +{
+  "description": "Structured JSON optical specifications for layer-guided rendering.",
+  "type": "object"
+}
    • addedOutput schema / properties / data / properties / masterDescriptivePrompt
      Added value: +{
+  "description": "Accurate general descriptive master prompt for photorealistic generation.",
+  "type": "string"
+}
    • removedOutput schema / properties / data / properties / targetModel / enum
      Removed value: -[
-  "GPT Image",
-  "Nano Banana"
-]
    • changedOutput schema / properties / data / required
      Previous value: -[
-  "targetModel",
-  "userIntent",
-  "enhancementPrompt",
-  "relightingPrompt",
-  "recommendedParameters",
-  "opticalKeywordsUsed"
-]New value: +[
+  "targetModel",
+  "userIntent",
+  "detailedJsonSpecification",
+  "masterDescriptivePrompt",
+  "enhancementPrompt",
+  "relightingPrompt",
+  "recommendedParameters",
+  "opticalKeywordsUsed"
+]
  2. Changed5 schema fields changedv1.0.2
    • 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"
+}
  3. First observedv0.1.1

TDQS

A4.9/5.0
Behavior5/5

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

No annotations are provided, so the description carries full disclosure burden. It explicitly states the tool is read-only, deterministic, performs zero filesystem modifications, makes no network calls, and requires no authentication. It also describes the output characteristics, such as exact Kelvin CCT, 3D light angles, volumetric dust rays, and denoising ranges.

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 uses structured bullets with clear labels and front-loads the core capability before enumerating use cases. Every sentence adds distinct value — purpose, behavior, when to use, when not to use, and alternatives — with no filler.

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?

Given the output schema exists, no annotations are present, and there are three sibling tools, the description covers everything an agent needs for correct invocation: purpose, behavior, parameter semantics, usage boundaries, and alternatives. No material gap is evident.

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

Parameters4/5

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

Schema coverage is 100% and the schema already documents all three parameters well. The description adds value by clarifying the functional meaning of the tool's outputs and by distinguishing target_model formats conceptually ('universal' vs 'nano_banana'), reinforcing how user_intent and image_path feed into the prompt synthesis. This exceeds the high-coverage baseline without duplicating the schema.

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 uses a specific verb-resource pairing: 'Synthesize ... diffusion prompts' based on physical optical analysis, and states the exact output type (photorealistic prompts with physical keywords and denoising parameters). It also explicitly distinguishes itself from siblings like 'generate_relight_variations' and 'analyze_optical_profile'.

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?

Dedicated 'When to use', 'When NOT to use', and 'Alternatives' sections explicitly name sibling tools and the conditions that select them. An agent can clearly decide between this tool, 'generate_relight_variations', 'harmonize_composite', and 'analyze_optical_profile' without guesswork.

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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