Rem Reflect

Self Learning

Before you use it. Sno Station sets the sharing level when it installs, by mode: full for agent-native and rem-enhanced, metadata-only for local-first; it never overwrites a choice you already made. At full, this tool sends the text of your Claude Code, Codex, Hermes, OpenClaw and Cursor sessions and every installed skill to Sno's cloud. It uses your Claude and Codex login in place and copies only Cursor's login into its isolated home to label sessions. In local-first nothing is sent to Sno, but the text of a few sessions a night still goes to each session's own agent account when this tool asks it for lessons; Hermes and OpenClaw use their own login without a credential copy. "What a run reads, copies and uploads" below lists everything. Turn uploading off at any time with sno station consent off.

Self Learning (rem-reflect) reads this machine's Claude Code, Codex, Hermes, OpenClaw and Cursor sessions once a day. When the Sno Station settings select agent-native or rem-enhanced, each session's own CLI (on the host's default model) conservatively decides keep/drop and labels its outcome. Each completed run is sent through sno rem judge; that command permits session and skill uploads only at full consent. Only rem-enhanced uses the returned judgments, experience pages, skill proposals and lessons in its report and local store. agent-native keeps its local report and saves returned links for delivering later user verdicts. local-first sends nothing: each night it asks the session's own CLI about the few sessions with the most failures and owner corrections, and stores the lessons and at most one skill reminder per harness that it can quote verbatim from the session, for you to accept or reject. Local adoption still waits for the owner (here, you: the person who owns the machine and its skills). When the weekly allowance is used up, Self Learning uses your own agent's model until it resets, even when R5 is off for the upload mode. Its report gives the reset time in your configured time zone and tells an unlinked computer how to link. Session versions already learned locally leave every unanswered cloud request, and later requests leave those versions out; new versions and other sessions remain eligible. Each night tries the cloud first.

What a run reads, copies and uploads. A run reads ~/.claude/projects, ~/.codex/sessions, ~/.cursor/projects/*/agent-transcripts, Hermes's state.db read-only via python3, and OpenClaw's sessions list --json and export-trajectory events (seven days on first run, then continuing; sessions must be quiet for thirty minutes). It skips Hermes's first-user-message [sno-oneshot] marker and OpenClaw's :explicit:sno-oneshot- keys. It reads Claude's history.jsonl, the repository the Sno Cursor hooks recorded for each Cursor conversation (~/.sno/cursor/conversations/; a conversation with no record is kept without a project), each session's git origin, and installed SKILL.md files under ~/.claude/skills, ~/.codex/skills, ~/.hermes/skills and ~/.openclaw/skills; HERMES_HOME and OPENCLAW_STATE_DIR override the new homes. Accepted changes use those same installed roots. Locally redacted copies stay in ~/.sno/experience (or $REM_REFLECT_STORE). Claude and Codex turns run claude -p and codex exec on your existing login in place, with your settings, hooks, plugins and MCP servers left out and no session saved; a Claude or Codex login is never copied, because a copied login that renews signs the original out. Hermes and OpenClaw use their own login and HOME. Their labeling and lesson calls are marked Station one-shots and limited to 280 seconds. For Cursor it copies ~/.config/cursor/auth.json on Linux, or links the login keychains on macOS, into <store>/.loop-home/cursor, which Cursor runs use as their home so none of your Cursor hooks fire. Cursor labeling turns send the rendered session to your own Cursor account. Only agent-native or rem-enhanced at consent full uploads kept session text, tool-call targets/errors, project ids and complete installed skill bodies to Sno. Secret redaction is best effort. off or metadata-only uploads none of it. Installation selects metadata-only for local-first, full otherwise, without overwriting an existing choice; change it with sno station consent off|metadata-only|full.

The program is TypeScript run directly by Node; it needs Node 22.6 or newer on PATH as node, the sno CLI from Sno Station, the session's own Claude Code, Codex, Hermes, OpenClaw or Cursor (cursor-agent) CLI, and python3 for Hermes database reads. The sno heartbeat command, when installed, can schedule the daily run. Without a scheduler the commands still work manually and status reports that the loop is not armed. If node is older, install a current Node and retry; nothing here downloads or bundles a runtime.

Sno GPU attribution

Use the existing sno rem judge, sno rem recall and sno rem verdict path; this skill does not send GPU HTTP requests. The receiving service must supply the GPU headers: its own repository slug as X-Sno-Source, rsi as X-Sno-Workload, and a new UUID v4 as X-Request-ID generated inside each HTTP attempt, including retries, never in static client headers. Keep any existing operation ID's business and billing meaning. Do not add GPU headers to the session JSON or bypass Sno.

The nightly upload already carries run_id and each session's project_id, session_id and user_id; first-message recall carries its actual project_id. Preserve these fields and per-session project boundaries, including batches spanning multiple projects. Verdicts use their existing judgment ID to refer to stored context. The service must associate the project context actually used by each model call with its request ID; this skill cannot claim that GPU headers or logging associations are deployed merely because the upload contains the fields; server integration needs its own verification.

Session user_id is context, not proof of who pays. Verified user/machine identities come from service authentication/admission, never client-supplied identity headers. Do not send directly to Helicone. Local agent-account calls remain on their existing provider path; only actual Sno GPU attempts use the GPU contract. Missing project attribution remains unknown and is reported without disabling otherwise valid work. Any future direct GPU call must satisfy the shared Sno GPU request contract in the skill library's skills/README.md.

Commands

• sno rem-reflect run — harvest recent session versions and, in agent-native or rem-enhanced, persist one conservative local decision per session and send the completed run through sno rem judge. That command rejects session and skill uploads unless consent is full. Only rem-enhanced writes returned cited pages, eligible lessons and warranted skill proposals into the local store and uses their judgments in the report. agent-native keeps the local report. local-first uploads nothing; for up to three sessions per harness a night it asks that session's own CLI for one lesson and stores each answer whose quotes occur verbatim in the session as a page, a listed lesson and, for a lapse in using an installed skill it read, one staged reminder proposal; the report lists them with their accept commands, and each session version is asked about once; a session that grows can be asked again. A missing settings file finishes a no-upload day naming the reason. An allowance refusal runs Self Learning on your own agent's model; the night fails if every selected session's CLI is unavailable. Other failed or rejected sends are logged with the run id and leave the local day successful; the saved request can be sent on the next daily run. Held human verdicts are retried at the next entry even when today's reflection already succeeded.
• sno rem-reflect run --trigger timer|manual — records what started the run; the scheduled daily job passes timer (see Owner actions), a hand-typed run defaults to manual.
• sno rem-reflect run --now <timestamp> — use a specified timestamp for a directly invoked acceptance run; the scheduled command remains sno rem-reflect run --trigger timer.
• sno rem-reflect accept|reject|tbd <id> — apply the owner's decision locally to a staged skill proposal (<run-id>/<harness>) or listed lesson (L-<page-id>), then send its linked cloud judgment verdict in agent-native and rem-enhanced through sno rem verdict, whose full-consent check may reject it. local-first sends nothing. A failed send is logged with the judgment id and remains pending without changing the local verdict or its successful result.
• sno rem-reflect accept <lesson-id> --all-projects or --this-project — the owner's override of the layer the cloud gave a lesson: all of the owner's projects, or only the project it was learned in. A plain accept keeps the cloud's user-wide or project layer; a skill lesson changes SKILL.md only when promoted to all projects.
• sno rem-reflect recall --agent <kind> — run by the harness session-start hook; prints, for each recallable lesson of the session's project plus user-wide lessons, its trigger and advice, independent of agent kind, and one line naming how to read one in full. With --agent cursor it reads Cursor's hook input and answers in Cursor's form ({"additional_context": …}, or {}). The project is the git root of the first workspace folder, so in a window with several folders all work is filed under the first one. Cursor's first chat in a new window has no session start, so its first-prompt hook brings this index instead. A lesson is recallable when the owner accepted it, or when it is listed and its cloud verification accepted it; a rejected lesson never is.
• sno rem-reflect recall --agent <kind> --first-message — run by the harness prompt hook on a session's first prompt only; asks the cloud which one recallable lesson fits that message and prints its trigger and advice. It sends the message only when the first-message setting is on and consent is full, and never blocks the prompt.
• sno rem-reflect lesson <lesson-id> --session <id> --agent <kind> --cwd <dir> — print one recallable lesson in full.
• sno rem-reflect status — print the last run's status, whether the daily job is armed, and the lesson counts; exits non-zero when the job is stale, failed, or not armed.
• sno rem-reflect install-hooks --print — print the session-start and first-prompt hook entries for the owner to install, including Hermes's pre_llm_call shell hook; OpenClaw lessons come from the Sno memory plugin (the program never writes those files itself).

How proposals are classified

The cloud puts each finding in one of two classes. SKILL_DEFECT means the skill's own text is wrong or missing something, so the proposal patches the body of that SKILL.md. EXECUTION_LAPSE means the skill was right and the agent did not follow it, so the proposal adds one short line to the skill's reminders block: the region between <!-- reminders:start --> and <!-- reminders:end --> at the end of a SKILL.md, which is empty until such a line is accepted and has a size cap.

Owner actions

Set these up once. The program never edits these files itself, except ~/.cursor/hooks.json (below).

• Arm the daily run. Register the once-a-day job with sno heartbeat:

  Copy code
  sno heartbeat --interval 24h --max-hours 0 --label rem-reflect -- sno rem-reflect run --trigger timer
  

• Install the session-start and first-prompt hooks. Run sno rem-reflect install-hooks --print and merge the Claude fragment into ~/.claude/settings.json and the Codex fragment into ~/.codex/hooks.json. Codex runs its SessionStart hook only after approval; merge the Hermes fragment into ~/.hermes/config.yaml (or $HERMES_HOME/config.yaml) and approve its shell hook. It returns JSON context only on is_first_turn; OpenClaw uses the Sno memory plugin. For Cursor, sno rem-reflect recall install writes the two entries into ~/.cursor/hooks.json itself; it replaces its own earlier entries and keeps every other one.

• Allow the recall detail command. Permit sno rem-reflect lesson in the harness so a session can read a listed lesson in full from the recall index.

• Check the Sno Station settings. sno setup writes ~/.sno/settings.json (or $SNO_PROFILE_DIR/settings.json). Its current mode controls daily sharing. The modelCalls rows select local labeling and first-prompt lookup. R5 runs Local First lesson generation on the host and is off in the other modes, except when the weekly allowance is used up; the published older table without R5 uses that same default. Its prompt is served by sno skills rem-reflect-local-writer from the CLI binary, not a public skill file: R2 labels sessions on each session's own CLI with the host's default model, R3 names the nightly upload and R4 the first-prompt lookup. Daily runs and verdicts share by mode: both agent-native and rem-enhanced call the Sno cloud through sno rem; those commands enforce full consent. Only rem-enhanced uses the cloud judgments. R4 still needs its cell to be sno-gpu and consent full. With R2 off, sessions upload with an unknown local outcome. A missing settings file sends nothing and names the file; there is no default mode.

• Control upload. sno station consent shows the local choice. Only full permits session/skill uploads, the first-prompt lookup and held verdicts; installation never overwrites an existing choice.