list_commentsList comments on a Figma design file. Returns each comment's id, message, author handle, created time, and resolved time. Use to review feedback and discussion on a design.
| Name | Required | Description | Default |
|---|---|---|---|
| file_key | Yes | The Figma file key (the segment after /file/ or /design/ in a Figma URL). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "file_key": "abc123xyz"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, non-destructive. Description adds value by listing returned fields (id, message, author handle, created time, resolved time). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. Each sentence serves a purpose: defining the action and stating return fields and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, well-annotated tool with one parameter, the description is complete. It specifies the resource, action, return fields, and usage context. No output schema needed given the explicit listing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with a clear description for file_key. The tool description does not add additional parameter information beyond what the schema provides, so baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'List' and resource 'comments on a Figma design file'. Distinguishes from sibling tools like get_file and get_file_nodes by targeting comments specifically.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: 'Use to review feedback and discussion on a design.' No explicit alternatives or when-not-to-use, but the sibling set lacks direct comment-focused alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and the set mixes Figma-specific tools with a large library of data-lookup tools, making it hard for an agent to distinguish when to use which.
Naming conventions are inconsistent: snake_case (ask_pipeworx, deep_research), camelCase (get_me, get_file), and mixed underscores (list_comments). There is no consistent pattern across the tool set.
The server is named 'Figma' but has 36 tools, only 5 of which are Figma-related. The remaining 31 are Pipeworx data tools, indicating a severe scope mismatch and unnecessary bloat for a Figma server.
The Figma-specific tools lack essential CRUD operations (e.g., no create, update, or delete for files or nodes). The Pipeworx tools, while extensive, are irrelevant to Figma, so the server is severely incomplete for its stated purpose.