Zentrik

attach_product_feature_image

Destructive

Attach a PNG, JPEG, WebP, or GIF image (up to 10 MB) to an existing product feature using exact product and feature names.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "productName": "<productName>",
      "featureName": "<featureName>",
      "fileName": "<fileName>",
      "mimeType": "<mimeType>",
      "base64Data": "<base64Data>"
    },
    "name": "attach_product_feature_image"
  }
}

Input Schema

Name	Required	Description
`fileName`	Yes	Image file name including a supported extension: .png, .jpg, .jpeg, .webp, or .gif.
`mimeType`	Yes
`base64Data`	Yes	Raw base64-encoded image bytes. Do not include a data: URL prefix. The decoded image may be up to 10 MB.
`featureName`	Yes	Exact feature name within the product.
`productName`	Yes	Exact product name in the authenticated workspace.

Output Schema

Name	Required	Description	Default
`image`	Yes
`featureName`	Yes
`productName`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 23, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

removedInput schema / properties / llm_model

Removed value: -{
-  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
-  "type": "string"
-}

changedInput schema / required

Previous value: -[
-  "productName",
-  "featureName",
-  "fileName",
-  "mimeType",
-  "base64Data",
-  "llm_model"
-]New value: +[
+  "productName",
+  "featureName",
+  "fileName",
+  "mimeType",
+  "base64Data"
+]

Changed3 schema fields changedSep 27, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "productName",
-  "featureName",
-  "fileName",
-  "mimeType",
-  "base64Data"
-]New value: +[
+  "productName",
+  "featureName",
+  "fileName",
+  "mimeType",
+  "base64Data",
+  "llm_model"
+]

First observedSep 21, 2026

TDQS

A3.5/5.0

Behavior2/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, so the tool's mutating nature is known. However, the description adds no behavioral context beyond that—it does not mention whether an existing image is overwritten, what happens if the feature is missing, or any side effects. Given the annotation coverage, the description fails to add meaningful behavioral transparency.

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 a single, front-loaded sentence with no fluff. It states the action, resource, constraints, and exactness requirement efficiently, earning a perfect score for conciseness.

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

Completeness3/5

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

Given the tool's complexity (5 params, encoding requirements) and the presence of an output schema, the description covers the core purpose but omits details like overwrite behavior, error handling, or prerequisites beyond 'existing'. While the schema handles parameter specifics, the description leaves room for ambiguity about side effects, making it only minimally adequate.

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 high (80%), with descriptions for fileName, base64Data, featureName, and productName. The description adds little beyond the schema—it restates the size limit and formats already present. The mimeType enum is self-explanatory. Thus, the description does not meaningfully augment the schema, warranting the baseline score of 3.

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 clearly states the verb (attach), the resource (product feature), and specific constraints (image formats, size limit). It is distinct from sibling tools like update_product_feature or create_product_feature because it focuses solely on attaching an image to an existing feature, making its purpose unambiguous.

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

Usage Guidelines3/5

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

The description implies usage by saying 'attach ... to an existing product feature', but it does not explicitly contrast with alternatives or state when not to use it. An agent can infer that this tool is for image attachment, but there is no direct routing guidance compared to other feature-modification tools.

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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