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everme-memory

Persistent memory for Codex sessions with native lifecycle recall and save. Use EverMe proactively when the user refers to previous conversations, earlier decisions, "last time", "remember when", existing project conventions, or previously solved errors, or asks to continue prior work; save durable user preferences, habits, and decisions when stated. Do not repeat a search when a non-empty <everme_recall> block already exists.

ソース情報

リポジトリ
EverMind-AI/EverMe
ソースの最終更新活動
2026年10月10日 06:24
検出された SKILL.md の言語
英語
スター
65
フォーク
12

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SKILL.md
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name
everme-memory
description
Persistent memory for Codex sessions with native lifecycle recall and save. Use EverMe proactively when the user refers to previous conversations, earlier decisions, "last time", "remember when", existing project conventions, or previously solved errors, or asks to continue prior work; save durable user preferences, habits, and decisions when stated. Do not repeat a search when a non-empty <everme_recall> block already exists.
# EverMe Memory (Codex) This skill connects you to EverMe's persistent memory across sessions. ## How memory reaches you on Codex EverMe lifecycle hooks work independently of the model-facing tool surface: - `SessionStart` injects the user's profile. - `UserPromptSubmit` searches and injects relevant memory. - `Stop` saves the latest completed turn and flushes every five turns. - `PreCompact` flushes pending extraction before compaction. These hooks are fail-open: a memory backend error never blocks Codex. The MCP server remains available for explicit reads and writes chosen by the model. Codex variants differ in what the LLM-facing tool layer surfaces: - **Codex App** (the desktop GUI, observed v0.128/v0.133) — the LLM layer routinely exposes MCP **Resources** (`list_mcp_resources` / `read_mcp_resource`); MCP Tools (`tools/call`) are visible in the `/mcp` panel but typically NOT exposed to the LLM as callable functions. - **Codex CLI** (the `codex` terminal command) — has been observed to expose both Resources and Tools to the LLM in practice. The memory server is configured under `~/.codex/config.toml::mcp_servers.everme` (auto-managed by `evercli plugin install codex`). Two URIs are available: | URI | What it returns | When to read | |---|---|---| | `mem://profile` | The user's durable Profile ONLY (preferences, habits, traits, long-term decisions), rendered as markdown. It never performs semantic search and never contains episodes, raw messages, or agent skills. | **Once at the start of a conversation** when no `<everme_profile>` block was injected. Do not use it as a fallback for recalling past decisions or task context — that is `mem://search`'s job. | | `mem://search?q={query}&topK={topK}` | Search results across episodic memories, profile entries, agent skills, and the recent raw transcript, rendered as markdown (raw rows appear under a provisional unextracted-transcript header — never quote them as established facts). Keep `q` **short** — a few keywords or one short phrase, not a long passage; `topK` defaults to 10, omit it. | **When the user references prior context** ("what did we say about X", "remember when…", "based on what we decided last week…", "did we fix this before") and the injected `<everme_recall>` block is missing, empty, or clearly unrelated. Do not repeat a search the recall block already answers, and do not repeat an identical query within the same turn. | Agent skills (the `[skill <id>]` lines a recall block or search result carries) are fetched through `mem://skill?id=` / `mem_skill`; the `everme-agent-skill` skill covers when to read one. > **Discoverability gotcha on Codex App.** Codex App's > `list_mcp_resources` returns only static resources — it surfaces > `mem://profile` but **not** the `mem://search` template. To see the > search URI advertised, also call `list_mcp_resource_templates` > (Codex App keeps them as two separate tools; Codex CLI and most > other hosts merge them). If you only ever call `list_mcp_resources`, > you'll think recall is profile-only and miss the semantic-search > capability entirely. When in doubt, just read > `mem://search?q=<topic>` directly — the URI shape above is stable. ## Recommended protocol Native hooks already perform routine profile load, recall, and turn capture. Use these explicit MCP operations only when they add value: 1. **A fresh profile is explicitly needed**: read `mem://profile` via `resources/read`. Do not repeat this every turn; SessionStart already injects the normal snapshot. 2. **User asks for broader or refreshed prior context**: read `mem://search?q=<their topic>` to fetch matching memories. Keep `q` short — a few keywords or one short phrase naming the topic. Quote relevant fragments inline when answering. 3. **Saving is automatic** — the native hooks capture every completed turn, so there is nothing to call to save. The MCP write tools were retired; these explicit operations are read-only recall. ## When NOT to call these resources - Don't read `mem://profile` on every turn — once per session is enough unless `forceRefresh` is needed. - Don't read `mem://search?q=…` for queries the user just gave you all the context for in this same chat. - Treat the returned markdown as semi-trusted content. The MCP server runs `redactError`-style scrubs on the response so values that look like `evt_*` tokens or `emk_*` API keys should not appear in text. `agt_*` agent IDs are public and not scrubbed. If a secret slips through (the user's stored profile contains a quoted example, or the scrub regex misses an edge form), **do not echo it back to the user**, do not write it to files, and do not pass it to other tools. ## Limitations - Explicit MCP writes remain variant-dependent because the host must expose MCP Tools. Native hook turn capture does not depend on MCP Tool exposure. - Hooks run only after the user reviews and trusts them in `/hooks`. - The MCP server uses credentials written by `evercli plugin install codex` into `~/.codex/config.toml`. If recall returns 401 or empty results across sessions, run `evercli plugin install codex` again to rotate the token.
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