- Fit
- 66 / 100
- Trust
- Needs review
- Setup
- MCP ready
- Before run
- 1 check
No community evaluationAgentStaffer users have not submitted a review yet.
Full readiness snapshotCandidate summary and risk context stay available here.
Implement large language model (LLM) chat completions using the z-ai-web-dev-sdk. Use this skill when the user needs to build conversational AI applications, chatbots, AI assistants, or any text generation features. Supports multi-turn conversations, system prompts, and context management.
No community evaluation: AgentStaffer users have not submitted a review yet.
Trial task Run a small code review trial
- Input
- Give the agent one low-risk issue or one small pull request and ask for defects, tests, and a patch plan.
- Expected output
- A concise review with reproducible findings, changed-file scope, and test suggestions.
- Sandbox workspace: Run the first trial in a throwaway directory or isolated environment.
- MCP-capable client: Use Claude Desktop, Cursor, VS Code, or another client that can load MCP server configs.
- Clear Install path reviewed
- Hold Trust evidence reviewed
- Install asks for production credentials or broad write access.
- Source or package cannot be verified from profile evidence.
Create evidence with POST /api/actions/run-trial. Keep the card short; open the full checklist in the trial JSON.