Expose Skill/MCP Configuration Errors to Agent and Enable Agent Self-Awareness and Corrective Guidance
- Linguagem predominante
- Shell
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Descrição
### Describe the feature or problem you'd like to solve
Skill/MCP configuration errors should be exposed to the agent so that it can become aware of the issue and provide users with appropriate correction suggestions.
### Proposed solution
**Required Behavior:**
- When a user runs the skill command and discovers that some or all skills fail to load, the error messages shown to the user (such as malformed YAML header) should also be exposed to the Copilot agent. When the user asks for modifications, the agent should be aware of the existing issues.
- When a user runs the mcp command and finds that some or all MCP configurations fail to load, the error messages displayed to the user (such as JSON formatting errors) should likewise be exposed to the Copilot agent. When the user requests changes, the agent should clearly understand where the problem lies.
- The Copilot agent should understand its own configuration format instead of searching for documentation online when responding to user issues. In practice, the agent often retrieves incorrect documentation and modifies the configuration using the wrong format, resulting in even more inconsistent and problematic outcomes.
### Example prompts or workflows
Sample prompts:
- I ran `skill` and got: "Malformed YAML header". Can you fix my skill configuration?
- The `skill list` command shows that 2 out of 5 skills failed to load. Error: "Invalid field 'descriptin' in metadata." Please help me correct it.
- I ran `mcp` and it says: "JSON parse error: Unexpected token } in position 245." Can you fix my json configuration?
### Additional context
_No response_
Guia de contribuição
Direção de pesquisa
Comece rastreando os fluxos de comandos de skill e mcp e identificando onde os erros de configuração são relatados. Determine como essas mensagens existentes podem chegar ao Copilot agent e, em seguida, verifique se as configurações de skill ou MCP com falha são identificadas com precisão e se o agente fornece orientações corretivas usando os formatos documentados.
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Avaliação
- Stack de tecnologia
- shell
- Domínio
- ai, cli
- Tipo de issue
- Funcionalidade
- Dificuldade
- 4/5
- Tempo estimado
- 3-5 dias
- Status de atividade
- Pouca atividade
- Clareza
- Razoavelmente clara
- Facilidade para iniciantes
- 38/100