Results for “recalls”

Persists and recalls agent knowledge across sessions using four approaches: static KB, company wiki, persistent memory, and session brain.

Computes the Recall metric using torchmetrics, including configuration for binary, multiclass, and multilabel tasks.

Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.

Drafts FDA product recall plans compliant with 21 CFR Part 7, covering Recall Committee governance, health hazard evaluation, recall classification, notification protocols, effectiveness checks, product disposition, and termination procedures. Use when developing recall SOPs, updating recall procedures, drafting recall readiness plans, or preparing FDA-regulated product recall documentation.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Sets one-shot reminders for events, tasks, and deadlines, confirming the time and scheduling delivery when cron is available.

Mines git history and codebase to reconstruct the development lifecycle, identify sequential and parallel patterns, and produce actionable recommendations for future iterations.

Review governed memory proposals, policy tags, tombstones, and effective memory.

Builds a local RAG memory system that indexes session logs and notes into ChromaDB for semantic recall across agent restarts.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Semantic-search personal knowledge (memory, plans, handoffs, skills, Codex rules) via the local RAG index at ~/.claude/rag-index/. Use when a query is fuzzy or cross-file ("how did we fix X", "what did we decide about Y", "which skill handles Z"). Complements grep (exact) and Serena (code symbols). If the user asks a recall question that doesn't map to a specific known file, reach here first.

Apple Reminders via remindctl: add, list, complete.

Composite skill — query, capture, improve, and persist knowledge in one workflow. Chains recall (RAG query) → sync-memories (write durable note) → rag-curate (improve weak retrievals) → handoff (durable snapshot if session-ending). Use when the work involves "what did we decide", "remember this", "save where we are", or any closing checkpoint.

Enhances AI agent memory by injecting large external context, auto-summarizing conversations with tone and intent preservation, compressing multi-turn histories, and verifying facts.

Surface relevant project memory at session start or on demand. Trigger: session start, 'recall', 'remember', 'what do you know', 'context', /recall

Watches conversations continuously and compresses them into prioritized notes, consolidating and recovering missed sessions with multiple redundancy layers.

4-layer recall procedure (durable → semantic → PostgreSQL → daily notes) before claiming "no context". Invoke when user explicitly asks "do you remember", "what did we discuss about X", "search history". NOT a general assistant — only fires when recall is the explicit task. Drop the prior "use proactively" rule. Triggers: "do you remember", "what did we discuss", "when did", "find that conversation about".

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Recover context from local AI conversation history with RecallBase. Use for same-day work summaries, resuming prior AI or coding sessions, or tracing a past decision to its source.

Transforms lessons learned into domain-organized memory instructions that persist across VS Code contexts, with global and workspace scopes.

Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.

Injects up to 1 million tokens of external context into AI agent memory, auto-summarizes conversations with tone and intent preservation, and compresses multi-turn history into dense token sequences.

Save information to persistent memory for cross-session recall. Stores preferences, conventions, decisions, and context.

Resume work from previous session with full context restoration

Pauses mid-conversation to reassess direction, assumptions, and bias, then recommends whether to continue, pivot, or pause.

Trigger or resolve a PagerDuty incident for on-call escalation

Save the current diagnosis state to disk for cross-session recall, including conclusions, rejected directions, and next steps.

List, add, edit, complete, or delete Apple Reminders and reminder lists via remindctl.

Extract cached credentials, password hashes, Kerberos tickets, and authentication tokens from memory dumps using Volatility and Mimikatz for forensic investigation.

`task-agent`/`review-agent`: use when broker delivery, ordering, acknowledgement, DLQ, backpressure, or replay changes; skip synchronous retry without message semantics.

Schedule reminders and recurring tasks that report back to the originating chat or session, with support for one-time, recurring, and timezone-aware jobs.

Execute self-learning system that captures corrections during sessions and syncs them to CLAUDE.md. Use when discussing learnings, corrections, or when the user mentions remembering something. Trigger with phrases like "remember this", "don't forget", "use X not Y", or "actually...".

skill-trigger-reminders

`analysis-agent`/`task-agent`/`review-agent`: use for recurrence guards on known defects, incidents, or escaped failures; skip speculative risk without a prior failure mechanism.