Demonstrates annotation usage for metadata in content, showing different patterns for error, success, and debug messages with optional image examples.
Demonstrates how annotations can be used to provide metadata about content
| Name | Required | Description | Default |
|---|---|---|---|
| messageType | Yes | Type of message to demonstrate different annotation patterns | |
| includeImage | No | Whether to include an example image |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions demonstrating annotation patterns but doesn't disclose behavioral traits such as whether it's read-only, if it modifies state, what the output looks like, or any side effects. This is inadequate for a tool with no annotation coverage.
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, efficient sentence that gets straight to the point without waste. It's appropriately sized for a simple tool, though it could be more front-loaded with operational details.
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?
Given no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, how annotations are demonstrated, or the complexity involved. For a tool with 2 parameters and full schema coverage, more context on behavior and output is needed.
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?
Schema description coverage is 100%, so the schema already documents both parameters fully. The description adds no meaning beyond the schema, such as explaining why to choose specific message types or image inclusion. Baseline 3 is appropriate when schema does the heavy lifting.
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 states the tool demonstrates annotation usage for content metadata, which is a clear purpose, but it's vague about what the tool actually does operationally. It doesn't specify a concrete action like 'generate' or 'display' annotated messages, nor does it distinguish from siblings like 'structuredContent' or 'echo' that might handle similar content.
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?
There is no guidance on when to use this tool versus alternatives. Given siblings like 'structuredContent' and 'echo' that might handle content, the description lacks explicit when/when-not instructions or prerequisites, leaving usage context implied at best.
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/epicweb-dev/epic-me-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server