list_skills
List learned skills with optional filters for status and category to retrieve reusable context for future tasks.
Instructions
列出已学习的技能。
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| status | No | ||
| category | No |
List learned skills with optional filters for status and category to retrieve reusable context for future tasks.
列出已学习的技能。
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| status | No | ||
| category | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It merely restates the tool name ('List learned skills') without revealing any behavioral traits such as ordering, pagination, read-only guarantees, or error conditions. This adds no value beyond the tool name 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 short sentence with no filler, but it is under-specified to the point of being unhelpful. Conciseness should accompany substance; here it sacrifices necessary context, so it earns a low score.
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 tool with three optional parameters, no output schema, and no annotations, the description is grossly inadequate. It fails to explain parameter semantics, filtering options, return structure, or when to use this tool over siblings, making it nearly unusable for an agent.
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?
The schema has 0% description coverage for its three parameters (limit, status, category), and the description does not mention any of them. There is no explanation of what each parameter does, how they interact, or what formats are expected, leaving the agent completely in the dark.
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 a clear action ('列出' - list) and resource ('已学习的技能' - learned skills), which conveys the basic purpose. However, it does not distinguish this tool from siblings like search_skill or get_skill, which might also return skill lists, so it falls short of a top score.
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 guidance is provided on when to use this tool versus alternatives. It does not mention triggering conditions, prerequisites, or how it differs from search_skill or get_skill, leaving the agent without decision support.
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/top777/memory-engine'
If you have feedback or need assistance with the MCP directory API, please join our Discord server