engram — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited engram (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Engram is a local-first personal AI identity and memory layer exposed over MCP. It lets MCP-compatible coding tools (Claude Code, Codex, Cursor, and other MCP clients) start from the same user-approved understanding of who the user is, what they've decided, and what they've learned — without a cloud account and without hidden memory the user cannot inspect.
This skill tells you when to reach for Engram and which existing MCP tools to use. It does not add new behavior; it routes to the Engram MCP server.
Reach for Engram when the user's request implies continuity, recall, or durable memory rather than a one-off task:
| Signal | Example phrasing | Where to start |
|---|---|---|
| Resume work | "continue from last session", "pick up where we left off" | get_resume_brief |
| Recall a decision | "what did we decide", "why did we choose X" | search_knowledge, get_relevant_knowledge |
| Save a lesson | "remember this", "save a lesson", "note this gotcha" | add_lesson |
| Save a decision | "record this decision", "we chose X because Y" | add_decision |
| Save a playbook | "save this as a playbook", "remember these steps" | add_playbook |
| Search prior knowledge | "have we seen this before", "search what we know about X" | search_knowledge |
| Identity / preferences | "who am I to you", "what are my preferences" | get_user_context, get_identity_card |
| Export identity/context | "export my identity card", "give me my context" | get_identity_card |
| End of session | wrapping up, summarizing what changed | wrap_up_session |
When the request is a normal coding task with no continuity or memory angle, do not invoke Engram — just do the task.
get_resume_brief to recover the lastthread of work. For identity and preferences on a fresh project, call get_user_context.
search_knowledge (topic known) or get_relevant_knowledge (let Engram pick what's relevant). Normal read/search tools provide session context; export surfaces such as get_identity_card are owner-gated and can write local files.
permanent. When the user says to remember something, propose it and write it with add_lesson / add_decision / add_playbook. These are user-approved writes, not automatic background memory.
wrap_up_session to checkpoint context so the nexttool (or the next session) can resume.
Some MCP clients also run session hooks that capture context automatically; that context lands in the user-visible daily log and the staging tier, where it is inspectable and is not silently promoted to verified/trusted knowledge.
The full read/write tool map is in references/tools.md. Privacy, ownership, and storage boundaries are in references/privacy.md.
for review**, not silently promoted to verified/trusted memory; everything written lands in the user's local store where it can be inspected.
vendor lock-in. Telemetry is off by default; if enabled it writes a local log only, and any remote sending is a separate explicit opt-in.
not silently become trusted facts.
references/tools.md; do not invent tools.
Engram runs as an MCP server via the piia-engram-mcp command. Configure your MCP client to launch it (the Cursor plugin skeleton under .cursor-plugin/ shows one such wiring). By default the server exposes a Tier-1 core tool set; the full set is available with ENGRAM_TOOLS=all.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.