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/add-memory-kind

Add a new business memory kind end-to-end. Pick the storage combination (Markdown / SQLite / LanceDB), pick the markdown strategy (daily-log / skill-named / single-file), then wire up the schema(s), repo(s), and writer(s).

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everos
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Install
$ npx -y skills add evermind-ai/everos --skill add-memory-kind --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/add-memory-kind

Context preview

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

Add a new business memory kind end-to-end. Pick the storage combination (Markdown / SQLite / LanceDB), pick the markdown strategy (daily-log / skill-named / single-file), then wire up the schema(s), repo(s), and writer(s).

SKILL.md

add-memory-kind.SKILL.md
name: add-memory-kind
description: Add a new business memory kind end-to-end. Pick the storage combination (Markdown / SQLite / LanceDB), pick the markdown strategy (daily-log / skill-named / single-file), then wire up the schema(s), repo(s), and writer(s).

/add-memory-kind — Add a new business memory kind

When to invoke

Adding a new persisted business entity (Episode, Case, Skill, AtomicFact, Foresight, Profile, or something custom). Multiple storage layers may be involved; this skill walks the decision then the wiring.

1. Decide the storage combination

A memory kind **does not have to use all three** layers. Pick by what the kind actually needs:

| Need | Markdown | SQLite | LanceDB | |---|:-:|:-:|:-:| | Human-readable / agent-editable source-of-truth text | ✅ | | | | Structured state, ACID transactions, joins, predicates | | ✅ | | | Vector / BM25 / hybrid retrieval | | | ✅ |

Common combinations seen in EverOS:

| Combo | Example | Rationale | |---|---|---| | **md only** | scratch notes / dump bins | text-of-truth, no index needed | | **md + lancedb** | episode / memcell / case | text-of-truth + semantic retrieval | | **md + sqlite** | profile / playbook / soul.md state | text-of-truth + structured state to query | | **md + sqlite + lancedb** | full-blown business records | when you need *both* transactional state AND retrieval | | **sqlite only** | audit log / task queue / LSN watermark | system state, never user-facing | | **lancedb only** | rare; usually you still want md | derived embeddings without text-of-truth |

Rule of thumb: **markdown is the truth**; sqlite and lancedb are derived indexes that can be rebuilt from md. Drop md only when the kind has no human-readable form (pure system state).

2. Pick the markdown storage strategy (if md is in your combo)

Three strategies — declared in the EverOS Markdown First spec:

| Strategy | Filename | Mutation | Examples | |---|---|---|---| | **Daily-log append** | `<prefix>-YYYY-MM-DD.md` | append entries | memcell / episode / case / atomic_fact / foresight | | **Skill-named in-place** | `skill_<name>.md` | overwrite the file | skills (procedural memory) | | **Single-file rewrite** | `user.md` / `agent.md` / `soul.md` / `behaviors.md` / `tools.md` | overwrite the file | profiles / playbooks |

This skill currently has a **complete recipe for daily-log append**. Skill-named and single-file recipes are sketched at the bottom — their base writers (`BaseSkillWriter` / `BaseProfileWriter`) land later in the project; until then build a thin wrapper over `MarkdownWriter` directly.

---

3. Markdown daily-log: 4 steps

3.1 Frontmatter schema — `infra/persistence/markdown/mds/<name>.py`

"""Episode daily-log frontmatter."""

from __future__ import annotations

import datetime as _dt
from typing import ClassVar, Literal

from everos.core.persistence.markdown import UserScopedFrontmatter


class UserEpisodeDailyFrontmatter(UserScopedFrontmatter):
    """``users/<u>/episodes/episode-<YYYY-MM-DD>.md``."""

    ENTRY_ID_PREFIX: ClassVar[str] = "ep"
    DIR_NAME: ClassVar[str] = "episodes"
    FILE_PREFIX: ClassVar[str] = "episode"

    type: Literal["user_episode_daily"] = "user_episode_daily"
    date: _dt.date
    entry_count: int = 0
    last_appended_at: _dt.datetime | None = None

For agent-track kinds subclass `AgentScopedFrontmatter` instead. If user-track and agent-track share a kind name (e.g. `memcell`), give each a **distinct** `ENTRY_ID_PREFIX` (e.g. `umc` vs `amc`) so reverse lookup is unambiguous.

3.2 Re-export — `mds/__init__.py`

from .episode import UserEpisodeDailyFrontmatter as UserEpisodeDailyFrontmatter

3.3 Business writer — `infra/persistence/markdown/writers/<name>.py`

"""Episode appender."""

from __future__ import annotations

from pathlib import Path

from everos.core.persistence import MarkdownReader

from ..mds import UserEpisodeDailyFrontmatter
from .base import BaseDailyWriter


class UserEpisodeAppender(BaseDailyWriter):
    schema = UserEpisodeDailyFrontmatter

    # OPTIONAL: override the count strategy. Default is len(entries);
    # override to trust the frontmatter field instead.
    def _current_count(self, path: Path) -> int:
        if not path.exists():
            return 0
        return MarkdownReader.read(path).frontmatter.get("entry_count", 0)

3.4 Re-export — `writers/__init__.py`

from .episode import UserEpisodeAppender as UserEpisodeAppender

Done — usage

from everos.infra.persistence.markdown.writers import UserEpisodeAppender

appender = UserEpisodeAppender(memory_root)
eid = appender.append("u_jason", "I went to the doctor today.")
# → users/u_jason/episodes/episode-<today>.md
# → entry markers carry an auto-generated EntryId (e.g. ep_20260507_001)

---

4. (Optional) SQLite table — 4 steps

Skip this section if the kind doesn't need structured state beyond markdown.

4.1 Schema — `infra/persistence/sqlite/tables/<name>.py`

from everos.core.persistence.sqlite import BaseTable, Field


class EpisodeState(BaseTable, table=True):
    __tablename__ = "episode_state"  # type: ignore[assignment]

    id: int | None = Field(default=None, primary_key=True)
    entry_id: str = Field(index=True, unique=True)
    cluster_id: str | None = Field(default=None, index=True)
    status: str = Field(default="active")

`BaseTable` already provides `created_at` / `updated_at` (auto-bumped).

4.2 Re-export — `tables/__init__.py`

from .episode import EpisodeState as EpisodeState

4.3 Repo — `infra/persistence/sqlite/repos/<name>.py`

from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker

from everos.core.persistence.sqlite import RepoBase

from ..sqlite_manager import get_session_factory
from ..tables import EpisodeState


class _EpisodeStateRepo(RepoBase[EpisodeState]):
    model = EpisodeState

    def _factory_lookup(self) -> asy
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Ships witheveros

One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

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Repo: evermind-ai/everos

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