'recall' 검색 결과

Recall project knowledge, past decisions, failures, and preferences when they can help a coding task. Capture changed files before responding.

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Use at the Mem Off hackathon. Keeps a running, evidence-backed report on how the participant's memory system performed for their coding agent during the day — what the harness measured, what cognee-report's scorecard says, what was recalled and whether it helped — in ./memoff-report.md and ./memoff-report.json. The report is submitted together with the action results; it never contains quotes, keys, data or names.

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Phase 4 Turn 1 of disease-market-sizing-orchestration. Generates report HTML with mandatory citation anchors per fact claim. Reads contract + staging + sources/. Every drug/treatment/stat/recommendation MUST carry [pmid:.../guideline:.../nct:...] anchor that resolves to an actual file in sources/. NEVER hardcode drug names or numerical claims. Use AFTER evidence recall (phase 3), BEFORE content-verification-layer (Turn 2).

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Cross-disease market sizing entry skill. Triggered by user one-liner like "做 X 市场调研" or "Run market sizing for X". Auto-runs 5 phase pipeline: contract → stratify → recall → compose-audit → bundle. Hard-gates on Cite-or-Block: every fact claim must carry citation anchor verifiable against sources/. Resumable mid-run.

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Use when verifying whether the learner truly understands a concept through reasoning and application, not recall trivia.

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Use when explaining a technical concept and adapting depth, pacing, and examples to the learner's readiness.

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Найти прошлое решение по теме в выбранных владельцем файлах.

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Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.

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Complete SolanaOS agent skill — install, configure, and operate the autonomous Solana trading runtime with Honcho v3 epistemological memory, multi-venue perp trading (Hyperliquid + Aster), on-chain intelligence with USD pricing, Telegram bot, gateway API, Tailscale mesh, hardware integration, and cross-session recall. Use when asked to install SolanaOS, query Solana blockchain data, manage wallets, run OODA trading loops, configure strategies, control BitAxe mining fleets, pair Seeker devices, or operate any SolanaOS runtime surface.

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Builds a DRAFT quiz from the training content the user supplies (slide deck, manual, e-learning script, session transcript, procedure): numbered questions with the correct answer, distractors drawn from the content itself, an explanation quoting the source passage with its location, a difficulty tag (Recall, Apply, Analyse) with its basis, and a coverage table showing which sections and objectives each question tests and which are left uncovered. Use when the user asks to "build a quiz from this deck", "write knowledge check questions for this module", "create an assessment from this training", "test understanding of this procedure" or "which sections does this quiz cover". Do not use for a reader-facing question and answer page built from documents, use faq-builder instead; for writing the procedure itself from notes or a walkthrough, use sop-drafter. Drafts for human review; never approves, authorises or signs off.

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Find a past decision, document, or conversation in Screenpipe with source links.

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Build a dossier on a person: recall everything the vault already knows, map their public profiles by web research, emit a deep-research prompt for external tools, and persist a well-linked person card. Triggers: "/portret <name>", "dossier on <name>", "profile <name>".

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Route a new rule, preference or policy edit into every home it belongs in (always-loaded canon, memory, the behavioral codex, a skill, a hook) and leave a trace in the always-loaded layer so parallel sessions pick it up on their own. Flow: dedup recall, classify by form, write to all homes, back up, report. Triggers: "/intake", "record this rule", "route this to its homes".

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Write the follow-up after a call in the owner's own voice instead of a bot template: recall the transcript, person card and full correspondence, extract agreements with an owner and due date, draft short and personal, show before/after against the old template, then send through the approval gate and file the result to the person card. Triggers: "/fa", "follow-up", "what should I write to <name> after the call", or a fresh call transcript landing in the vault.

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In each setting, LLM-based methods substantially outperform classical baselines, achieving up to 68% recall at 90% precision compared to near 0% for t

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Use when the user references past work or you suspect cross-session context exists.

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Recall past work across Claude Code and Codex sessions. Finds decisions, research, fixes, and conversations by intent; with only a project and no question, orients on that project's recent state.

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Search, inspect, and record SIPS-owned Memory Fabric lessons. Use when a task needs prior lessons, recurring-fix memory, recall health, scoped historical context, or when a just-fixed bump or error should be recorded.

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Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes,

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Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.

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Complete WhatsApp management for OpenClaw agents: per-conversation memory (groups + DMs), unanswered message tracking, loop prevention, and multi-PA coordination. Use when: tracking conversation context, recalling past decisions, finding unanswered messages, or preventing echo/duplicate message loops.

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Evaluate recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.

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Use this skill when starting a new session, opening this project for the first time, or when you need to recall the project's tech stack, hard rules, and which other skills exist. Trigger words: セッション開始, このプロジェクト, 全体像, どのスキル, 何から, getting started, overview.

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Identifies non-coding RNAs (tRNA, rRNA, snoRNA, snRNA, riboswitches, sRNAs) using Infernal covariance-model search against Rfam, tRNAscan-SE 2.0 for tRNA, barrnap for rRNA, and ARAGORN for tmRNA, plus the small-RNA-seq boundary for miRNA and the transcript-assembly boundary for lncRNA. Covers the structure-conserved-not-sequence-conserved principle (why BLAST fails), GA-threshold and clan-competition correctness, tRNAscan-SE domain modes and pseudogene flags, rDNA copy-number collapse, and why homology annotation is a recall floor. Use when performing genome-wide ncRNA annotation, choosing the right tool for an RNA class, or interpreting ncRNA counts.

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