Continuity Framework

Asynchronous reflection and memory integration for genuine AI development. Use on heartbeat to reflect on recent sessions, extract structured memories with confidence scores, generate follow-up questions, and surface those questions when the user returns. Transforms passive logging into active development.

This skill is coherent with its stated purpose and contains only local-file operations in the provided code. Before installing: 1) Review and, if desired, change the memory directory by setting CONTINUITY_MEMORY_DIR to a secure path (the default is ~/clawd/memory). 2) Understand that it will persist conversation-derived data (questions, identity, reflection logs) on disk — treat that data as sensitive and apply retention/encryption policies if needed. 3) The current analyze_session() is a placeholder; if you (or an upstream package) modify the skill to call an external LLM or other network services, audit those additions — they could transmit conversation transcripts. 4) If you do not want autonomous background reflection, do not add the heartbeat trigger described in SKILL.md. Test with non-sensitive transcripts first and review any future commits that introduce network I/O or additional environment/credential requirements.

Type: OpenClaw Skill Name: vektor-continuity Version: 1.0.0 The skill bundle is designed for AI agent self-reflection and memory integration. The `SKILL.md` provides clear instructions for its use and integration without any prompt injection attempts against the analyzing agent or instructions for the OpenClaw agent to perform unauthorized actions. The `scripts/continuity.py` handles local file operations within a designated memory directory (`~/.clawd/memory` by default) for managing questions and identity. There are no network calls, external command executions, or attempts to access sensitive system files or credentials. The `analyze_session` function, which would typically involve LLM interaction, is a placeholder in the current implementation, returning an empty structure, thus mitigating potential risks associated with advanced processing.