arrecall
AgentRecall on-demand recall — surface past fixes, decisions, and patterns mid-session…
AgentRecall consolidation & reflection — periodic triage of recurring corrections; proposes rule changes, never applies them without the owner.
$ npx -y skills add Goldentrii/AgentRecall-X --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
/arreflectContext preview
What this command does when you run it.
AgentRecall consolidation & reflection — periodic triage of recurring corrections; proposes rule changes, never applies them without the owner.
description: "AgentRecall consolidation & reflection — periodic triage of recurring corrections; proposes rule changes, never applies them without the owner."
Run periodically (every 5-10 sessions, or whenever things feel like they're repeating). Purpose: catch corrections that keep recurring despite already being "known," and turn them into durable rules — with the human approving every rule change.
ar stats # corrections, feedback, insights, graph edges — health snapshot ar corrections rejected --stats # survivorship-bias probe: what the capture gate discarded ar mirror # first-person, citation-backed self-model from real corrections/insights
Read the output. Note which corrections keep showing up, and whether `ar mirror` reflects a pattern the human hasn't seen named yet.
For each correction pattern that appears more than once:
does an existing rule (CLAUDE.md / rules/*.md) already cover this?
IF yes AND the violation happened AFTER the rule was written:
the rule exists but didn't take — flag for re-abstraction (Step 4)
IF yes AND the violation happened BEFORE the rule was written:
already covered — no action needed
IF no:
new, unclassified pattern — cluster it (Step 3)Group semantically-similar uncovered corrections into candidate "error classes" (e.g. "forgets to gate destructive git ops," "assumes global binaries exist"). For each cluster of 2 or more items, draft:
Present clusters to the human. Don't invent a class for a single one-off correction.
ar consolidate # surfaces decay report + crystallization candidates + draft skill proposals ar consolidate --safety # login-free, LLM-free safety pass: decay, prune, graduate
For each recurring class from Step 2, draft a **broader rule** — not a patch to the existing one, but a sentence that would have caught the recurring violations too. Present the draft alongside the specific violations it's meant to cover.
PRESENT to owner: - the class / pattern - the specific violations (evidence) - the proposed new or reworded rule text - which file it would go in (CLAUDE.md or rules/<file>.md) IF owner approves: the owner applies the edit, or explicitly asks you to IF owner rejects: record the rejection reason, move on
**Rule edits are owner-gated, full stop.** This command proposes; it never edits CLAUDE.md or rules/ files on its own initiative.
session_end({
summary: "<what changed this reflection: N patterns confirmed, M new classes, K re-abstractions proposed/approved>",
insights: [{
title: "<the re-abstracted rule or confirmed pattern>",
evidence: "<the violations that triggered it>",
applies_when: ["<keyword1>", "<keyword2>"],
severity: "important"
}]
})---
Family: `/arstart` · `/arsave` · `/arrecall` · `/arreflect` — the four memory verbs (open · save · search · consolidate).
Correction-first persistent memory for AI agents. MCP server + SDK + CLI. Compounds across sessions.
Repo: Goldentrii/AgentRecall-X
AgentRecall on-demand recall — surface past fixes, decisions, and patterns mid-session…
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