Release 0.8.0

Added

• Approval system (F-028): Full runtime approval support via ElicitationApprovalHandler that bridges MCP elicitation to apcore's approval system. New approval_handler parameter on serve(). Supports request_approval() and check_approval() methods.
• ElicitationApprovalHandler: Presents approval requests to users via MCP elicitation. Maps elicit actions (accept/decline/cancel) to ApprovalResult statuses.
• CLI --approval flag with choices: elicit, auto-approve, always-deny, off (default).
• Approval error codes: APPROVAL_DENIED, APPROVAL_TIMEOUT, APPROVAL_PENDING added to ERROR_CODES.
• Enhanced error responses with AI guidance: ErrorMapper now extracts retryable, ai_guidance, user_fixable, and suggestion fields from apcore ModuleError and includes non-None values in error response dicts. ExecutionRouter appends AI guidance as structured JSON to error text content for AI agent consumption.
• AI intent metadata in tool descriptions: MCPServerFactory.build_tool() reads descriptor.metadata for AI intent keys (x-when-to-use, x-when-not-to-use, x-common-mistakes, x-workflow-hints) and appends them to tool descriptions for agent visibility.
• Streaming annotation: DEFAULT_ANNOTATIONS now includes streaming field. AnnotationMapper.to_description_suffix() includes streaming=true when the annotation is set.

Changed

• APPROVAL_TIMEOUT auto-retryable: ErrorMapper sets retryable=True for APPROVAL_TIMEOUT errors, signaling to AI agents that the operation can be retried.
• APPROVAL_PENDING includes approval_id: ErrorMapper extracts approval_id from error details for APPROVAL_PENDING errors.
• Error text content enriched: Router error text now includes AI guidance fields as a structured JSON appendix when present, enabling AI agents to parse retry/fix hints.