list_labels
List all labels defined in your workspace to categorize and filter social media posts.
Instructions
List all labels defined in the workspace
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List all labels defined in your workspace to categorize and filter social media posts.
List all labels defined in the workspace
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. The verb 'List' implies a read-only operation, which is good, but it does not disclose details like return format, pagination, ordering, or authorization requirements. Adds only minimal behavioral context beyond the operation itself.
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?
The description is a single, front-loaded sentence that fully states the tool's purpose without any filler. It is appropriately concise for a simple tool with no parameters.
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 zero-parameter, simple listing tool, the description is complete. It specifies what is listed (labels) and the scope (in the workspace). No output schema exists, but the outcome is self-evident: a list of labels. No additional context is necessary given the low complexity.
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?
There are zero parameters, so the schema is empty. The description does not need to add parameter details, and the baseline of 4 applies. No information is missing about inputs.
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?
The description uses a specific verb 'List' and a clear resource 'labels defined in the workspace', which distinguishes it from sibling tools like list_workspaces, list_accounts, or list_posts. No ambiguity about what the tool does.
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?
No explicit when-to-use guidance is provided, but the scope 'in the workspace' implies it is for the current workspace's labels. There are no alternatives mentioned, so usage is only implied by the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/pawel-tkaczyk/publer-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server