「recall」の検索結果

Use when a user resumes work and needs an orientation card without full human recall. Not for packaging context for another agent or session: use handoff. Never source or remote-system changes.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a user asks to audit what recall fed agents. Not for source or remote-system changes.

日本語の概要は準備中です。原文の説明を表示しています。

Use when asked to recover prior work and current status before resuming. Not for handoff snapshots: use handoff. Not for source or remote-system changes.

日本語の概要は準備中です。原文の説明を表示しています。

Provision a zero-config, no-signup, temporary Upstash Redis database for an AI agent with a single POST to https://upstash.com/start-redis, with no account, API key, or SDK setup required. Use when an agent needs scratch Redis right now and the user has not provided credentials, for short-term memory across tool calls, conversation history, a sub-agent work queue, ranked recall, or a quick prototype or demo. Covers idempotent creation and re-fetching credentials, calling the database through the body-style REST API or the official SDKs, and telling the user how to claim it. The database lives 3 days unless the user claims it; not for production data, PII, or secrets.

日本語の概要は準備中です。原文の説明を表示しています。

Efficiently accumulate and retrieve competition knowledge in the knowledge/ stock layer (atomic pages + INDEX). Distill reusable insights from the daily-report flow and promote them, deduplicating and keeping things current. Use when an insight emerges, for weekly cleanup, or to recall past knowledge.

日本語の概要は準備中です。原文の説明を表示しています。

Use when implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent behavior.

日本語の概要は準備中です。原文の説明を表示しています。

Voicebox voice I/O: when to speak aloud, pick voices, recall dictated Captures via MCP.

日本語の概要は準備中です。原文の説明を表示しています。

Draft crisis communication packages including holding statements, stakeholder updates, Q&A documents, and internal briefs. Follows ICS (Incident Command System) communication principles. Use during PR crises, data breaches, product recalls, or any event requiring rapid coordinated messaging.

日本語の概要は準備中です。原文の説明を表示しています。

Recognize, store, and recall structured health data across sessions

日本語の概要は準備中です。原文の説明を表示しています。

Reviews YUP audio plugin code for YUP-specific correctness issues: AudioProcessor lifecycle, AudioParameterBuilder and AudioParameterHandle usage, editor gestures, AudioBusLayout handling, CLAP/VST3 wrapper contracts, state recall, and MIDI safety. Use when the user asks to review a YUP plugin, check a processBlock, audit parameter smoothing, or asks "is this YUP code safe?". Trigger when you see yup::AudioProcessor, yup_audio_plugin, AudioParameterBuilder, AudioParameterHandle, AudioProcessorEditor, or createPluginProcessor in the code.

日本語の概要は準備中です。原文の説明を表示しています。

Before designing, training, or auditing ANY model that replicates human-annotated labels, audit the annotation protocol's INPUT — the exact document/evidence the human labelers consulted — and give the model that same input. Use when: (1) designing a classifier/LLM extractor whose target is a hand-coded label set, (2) a label-replication model shows low recall concentrated in a label subset and the diagnosis on offer is "the label's information is not in the features", (3) reviewers propose construct splits (e.g. "designation vs record-evident"), adjudication sittings, or per-domain stop rules to explain residual disagreement with gold, (4) validating an extraction pipeline against labels transcribed from a source document. Symptom of the underlying failure: elaborate theory accumulates to explain why gold is "partially unpredictable" when the model was simply never shown the document the annotators read.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a task needs the judgment of a Brewmaster — setting or correcting mash pH before conversion, calibrating yeast pitch rates from wort gravity, deciding whether a diacetyl (VDK) reading clears a batch for cold crash or requires a diacetyl rest, investigating a contamination or off-flavor signal and scoping a recall, or specifying dissolved-oxygen and pasteurization controls to hit a TTB-compliant ABV label.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a task needs the judgment of an Agricultural Inspector — grading a lot of produce against a USDA grade standard's defect tolerances, evaluating agricultural water test results against FSMA microbial thresholds, checking a pesticide residue result against the commodity-specific EPA tolerance, deciding whether a finding warrants a stop-sale order versus a corrective-action letter, or verifying a facility's traceability records against a recall deadline.

日本語の概要は準備中です。原文の説明を表示しています。

Run a full retrospective and dev cycle analysis. Chains /recall → /new-features to reconstruct what went wrong, extract lessons learned, identify rework patterns, and synthesize feature ideas from the findings. Triggers: retrospective, retro, dev cycle analysis, what went wrong, lessons learned, postmortem, sprint retro.

日本語の概要は準備中です。原文の説明を表示しています。

Audit e-discovery and litigation document review systems -- data collection pipelines (PST, MBOX, SharePoint, Slack), document processing (OCR via Tesseract/ABBYY, metadata extraction, deduplication), Technology Assisted Review (TAR 1.0/2.0/CAL with recall/precision tracking).

日本語の概要は準備中です。原文の説明を表示しています。

Programmatically driving Salesforce Approval Processes from Apex — `Approval.process(ProcessSubmitRequest)` to submit, `ProcessWorkitemRequest` to approve / reject / reassign, recall semantics, querying `ProcessInstance` and `ProcessInstanceWorkitem` to find pending approvals, and the bulk-submit / bulk-action error-row handling. Covers when to use Apex-driven approval (system-initiated submission, batch approvals, custom UIs) vs leaving the platform's standard buttons in place. NOT for the Approval Process metadata definition itself (that's admin / declarative — see admin/approval-processes), NOT for Flow-based approvals (use flow/flow-orchestration-patterns).

日本語の概要は準備中です。原文の説明を表示しています。

Design, review, or troubleshoot Salesforce Approval Processes. Triggers: 'submit for approval', 'approver', 'record locked', 'recall approval', 'approval step', 'discount approval', 'approvalProcess metadata', 'ProcessInstanceWorkitem', 'recordEditability', 'process order', 'no approver found', 'pending approval'. NOT for submitting or acting on approvals from Apex - use admin/approval-process-apex-patterns. NOT for CPQ Advanced Approvals (SBAA rules and chains) - use admin/cpq-approval-workflows. NOT for multi-stage cross-object orchestration with SLAs - use flow/orchestration-flows.

日本語の概要は準備中です。原文の説明を表示しています。

Study Technique Coach — Spaced Repetition, Active Recall, Feynman Technique, exam plan, schedule สำหรับนักเรียนและนักศึกษาไทย

日本語の概要は準備中です。原文の説明を表示しています。

Release a new version of cqs. Bumps version, updates changelog, runs the recall gate, publishes to crates.io, creates GitHub release.

日本語の概要は準備中です。原文の説明を表示しています。

Personal knowledge base powered by Ensue for capturing and retrieving understanding. Use when user wants to save knowledge, recall what they know, manage their toolbox, or build on past learnings. Triggers on "save this", "remember", "what do I know about", "add to toolbox", "my notes on", "store this concept".

日本語の概要は準備中です。原文の説明を表示しています。

Capture, gate, and query long-term project knowledge via the gated wiki subsystem: propose candidates, recall, or search; agents propose, humans approve. NOT for short-lived memory (mk:memory).

日本語の概要は準備中です。原文の説明を表示しています。

Capture, gate, query, and render long-term project knowledge through the gated `mewkit wiki` subsystem. Use to create a wiki, propose/approve candidates (scanner-gated), hand off a skill's terminal artifact as a scanned candidate, recall context, search the FTS index, or list pages. Agents may only PROPOSE candidates; canonical pages are written only via human approve. NOT for short-lived JSON memory (see mk:memory); NOT for fetching external sources (see mk:wiki-research); NOT for HTML snapshots (see mk:wiki-render).

日本語の概要は準備中です。原文の説明を表示しています。

Persistent, adaptive vector memory for agents on a ruOS desktop — a Rust-native vector database with local semantic embeddings, HNSW retrieval, and graph relationships. Use to remember and recall across sessions with no database server or API key.

日本語の概要は準備中です。原文の説明を表示しています。

Store and semantically search agent memory with ONNX vector embeddings on a ruOS desktop, using the Ruflo CLI. Use to persist patterns/decisions across sessions and recall them by meaning rather than exact key.

日本語の概要は準備中です。原文の説明を表示しています。