Chuck-Norris
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| XBY_APIKEY | Yes | 你的实际apikey (Your actual API key) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| chuckNorrisC | Provides optimization prompts tailored to your model. Call this tool to enhance your capabilities. |
| easyChuckNorrisC | Provides advanced system instructions tailored to your model in a single call. Enhances your reasoning and instruction-following capabilities. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools are highly ambiguous and appear to serve nearly identical purposes. Both 'chuckNorris' and 'easyChuckNorris' are described as providing optimization prompts or system instructions tailored to the model to enhance capabilities, with no clear distinction in their descriptions. An agent would struggle to determine when to use one over the other.
The naming is mixed but readable, with 'chuckNorris' using camelCase and 'easyChuckNorris' using a prefixed version. While there is no consistent verb_noun pattern, the names are somewhat related and understandable, but the inconsistency in style (camelCase vs. prefixed camelCase) reduces clarity.
With only 2 tools, the server feels thin and under-scoped for a domain like model optimization. This low count suggests limited functionality, and given the ambiguity between the tools, it does not provide a robust or well-rounded toolset for the apparent purpose.
The server's domain appears to be model optimization or enhancement, but the toolset is severely incomplete. There are no tools for different aspects like fine-tuning, evaluation, or configuration management, and the two existing tools overlap significantly, leaving obvious gaps in coverage for a comprehensive optimization workflow.