Damper

Get Feedback Attachment

get_feedback_attachment

Read-onlyIdempotent

Download a screenshot or file attached to a feedback item. index is the 0-based position shown by get_feedback (attachmentCount in list_feedback / get_feedback tells you how many exist). Images come back as image content you can view; other files come back as an embedded resource with base64 data.

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": {
      "projectId": "<projectId>",
      "feedbackId": "<feedbackId>"
    },
    "name": "get_feedback_attachment"
  }
}

Input Schema

Name	Required	Description
`index`	No	0-based attachment index (default: 0)
`projectId`	Yes	Project ID. Use list_projects to find available project IDs.
`feedbackId`	Yes

Output Schema

Name	Required	Description
`name`	Yes
`index`	Yes
`sizeBytes`	Yes
`feedbackId`	Yes
`contentType`	Yes
`dashboardUrl`	No	Full dashboard URL of the affected resource
`attachmentCount`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 30, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare this a safe, idempotent read. The description adds genuinely useful behavioral detail beyond them: images return as viewable image content, other files as an embedded base64 resource. Return-format nuance like this is the kind of context annotations cannot convey.

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?

Three sentences, front-loaded with the action, then parameter semantics, then return-format behavior. Every sentence carries distinct information with no padding.

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?

An output schema exists, yet the description still helpfully characterizes the two return shapes (image content vs embedded resource). For a simple three-parameter read tool, nothing an agent needs in order to call it correctly is missing.

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 67%; `index` and `projectId` are documented, while `feedbackId` is bare in the schema. The description compensates by explaining what `index` means in terms of get_feedback/list_feedback, adding meaning beyond the schema's '0-based attachment index'.

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 ('Download') and resource ('screenshot or file attached to a feedback item'), which cleanly distinguishes it from get_feedback and list_feedback. An agent can tell exactly what this does without opening the schema.

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

Usage Guidelines4/5

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

Explains that `index` refers to positions surfaced by `get_feedback`, and that `attachmentCount` from `list_feedback`/`get_feedback` tells how many exist, giving clear discovery context. It stops short of explicit when-to-use vs when-not guidance, but the surrounding workflow is clear.

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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