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Agent Memory
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/engram

Local-first personal AI identity and memory layer for MCP-compatible coding tools (Claude Code, Codex, Cursor, and others). Use this skill when the user wants to continue from a previous session ("continue from last session", "pick up where we left off"), recall a past decision

From plugin
piia-engram
1691 skill1 MCP
Install
$ npx -y skills add Patdolitse/piia-engram --skill engram --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/engram

Context preview

The summary Claude sees to decide when to auto-load this skill.

Local-first personal AI identity and memory layer for MCP-compatible coding tools (Claude Code, Codex, Cursor, and others). Use this skill when the user wants to continue from a previous session ("continue from last session", "pick up where we left off"), recall a past decision

SKILL.md

engram.SKILL.md
name: engram
description: Local-first personal AI identity and memory layer for MCP-compatible coding tools (Claude Code, Codex, Cursor, and others). Use this skill when the user wants to continue from a previous session ("continue from last session", "pick up where we left off"), recall a past decision ("what did we decide", "what was our reasoning"), persist something durable ("remember this", "save a lesson", "save a decision", "save a playbook"), search prior knowledge ("search what we know about X", "have we hit this before"), export their identity or context ("export my identity card", "give me my context"), or maintain local-first cross-tool identity and memory that the user owns and approves. Engram stores user-approved lessons, decisions, playbooks, and project context as local JSON; the AI suggests, the user decides what becomes permanent.
license: AGPL-3.0-or-later

Engram

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.

When to use this skill

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.

How to use it (routing, not magic)

1. **Start of a continued session** — call `get_resume_brief` to recover the last thread of work. For identity and preferences on a fresh project, call `get_user_context`. 2. **During work** — when the user asks what was decided or learned, call `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. 3. **Capturing durable knowledge** — the user, not the AI, owns what becomes 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. 4. **End of session** — call `wrap_up_session` to checkpoint context so the next tool (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](references/tools.md). Privacy, ownership, and storage boundaries are in [references/privacy.md](references/privacy.md).

Honest boundaries

  • Engram **suggests**; the user **decides**. AI-suggested knowledge is **staged

for review**, not silently promoted to verified/trusted memory; everything written lands in the user's local store where it can be inspected.

  • Storage is **local JSON the user owns**. There is no cloud account and no

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.

  • Knowledge moves through a **staging → verified** path so unreviewed entries do

not silently become trusted facts.

  • Do **not** claim capabilities Engram does not have. Use only the tool names in

[references/tools.md](references/tools.md); do not invent tools.

MCP server

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`.

Read more
Ships withpiia-engram

Local-first AI memory you can see, edit, and override — portable across Claude Code, Codex, Cursor, Windsurf, and other MCP coding tools.

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Python
Language
AGPL-3.0
License
8h ago
Last commit
3mo ago
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Repo: Patdolitse/piia-engram