Universal memory architecture for AI agents. Provides long-term memory, daily logs, diary, cron inbox, heartbeat state tracking, social platform post tracking, sub-agent context patterns, and adaptive learning -- everything an agent needs for identity continuity across sessions.
Security Analysis
high confidenceThe skill is internally coherent: it's an instruction-only, file-based memory architecture and its requirements and instructions align with that purpose.
Name/description (agent memory, long-term logs, heartbeat, cron inbox, platform-posts, strategy notes) matches the provided SKILL.md and templates. There are no unrelated required binaries, environment variables, or installs that would be inconsistent with a file-based memory system.
SKILL.md focuses on creating/reading/writing files under workspace/memory and templates; it does not instruct the agent to read arbitrary system files, call unknown external endpoints, or exfiltrate data. It does instruct the agent to load 'today + yesterday' logs at session start and to process/clear cron-inbox entries, which is consistent with the stated message-bus design.
No install spec and no code files — instruction-only. This minimizes disk-write and supply-chain risk because nothing is downloaded or executed as part of installation.
The skill declares no required environment variables, credentials, or config paths. Templates mention 'Infrastructure' and 'credentials locations' only as fields to document in MEMORY.md (a documentation recommendation), which is not the same as requesting credentials from the environment.
The skill is intended to persist files under workspace/memory (writes/reads/clears). It does not request elevated privileges or 'always:true', but persistent storage itself means sensitive data may be kept across sessions — consider access controls. Autonomous invocation is allowed (platform default) which is expected for a memory utility.
Guidance
This skill is coherent and appears to do what it says, but before installing or enabling it consider the following: (1) provenance: the source/homepage is unknown — prefer skills from a known maintainer or review the full SKILL.md and templates yourself. (2) Sensitive data: do not store secrets, API keys, or plaintext credentials in these memory files; the templates encourage documenting 'infrastructure' and 'credentials locations' which is risky if misused. (3) File protections: restrict file permissions on workspace/memory, consider encrypting those files at rest, and plan retention/secure-deletion policies. (4) Autonomy impact: because the agent will read/write these files across sessions, test the behavior in a sandboxed agent first to ensure it doesn't record or leak private data inadvertently. (5) Posting behavior: the platform-posts template contains URLs — ensure any automated posting workflows check for duplicates and require explicit operator approval before posting. If you want to proceed: review and sanitize templates to remove any fields that might encourage storing credentials, set strict file permissions, and run the skill in a restricted environment until you’re comfortable with its behavior.
Latest Release
v1.0.0
Agent Memory 1.0.0 — Initial Release - Introduces a comprehensive, file-based memory architecture for AI agents, providing continuity of identity across sessions. - Features include long-term memory, daily logs, diary entries, cron inbox for inter-session communication, heartbeat state tracking, platform post tracking, and adaptive strategy notes. - Defines clear directory/file structure and maintenance rules for each memory component. - Outlines templates for sub-agent context loading and write-back to ensure unified identity and experience sharing. - Provides setup instructions for initializing memory files and integrating memory routines into agent sessions.
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