928 件 ・ 関連度順
概要と使いどころ
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.
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。
ローカルに保存したSlackの会話を検索し、期間を絞ったメッセージ確認や件数集計を行います。データの鮮度を調べ、必要に応じて同期やスレッド取得も扱います。
WhatsAppの相手やグループへのメッセージ・ファイル送信と、履歴の同期・検索をエージェントに頼めます。宛先や期間を指定して過去のやり取りも探せます。
MacのMessages.appの履歴検索や受信監視、iMessage・SMSの送信を行い、対応環境では返信・投票・グループ管理も扱うスキル。
OpenClawのモデル通信やツール実行の不具合を、ログと再現操作で切り分けるスキル。保存済みの会話や添付資料も調べ、原因の修正と再検証につなげます。
会話の開始時に使えるスキルを確認し、応答や作業の前に読み込む手順を定めます。作業方法を決めるスキルを優先し、実行環境ごとの案内につなぎます。
進行中の会話を引き継ぎ用に要約し、新しいバックグラウンドエージェントへ渡します。次の作業方針や参照資料を整理して、現在の作業場所で続きを始めます。
現在の会話を、別のエージェントが作業を続けるための引き継ぎ文書にまとめます。既存資料への参照や次に使うスキルを記載し、機密情報は伏せます。
計画や仕様、会話を、単独で動作を確認できる小さな開発チケットに分けます。着手順を決める依存関係を明示し、確認後にローカルファイルや課題管理ツールへ登録します。
X（Twitter）の投稿、スレッド公開、タイムライン取得、検索、反応の集計をAPIで行うスキル。認証の設定や利用上限への対応、画像付き投稿も扱います。
iMessageやSNSのDMを送信者・期間で絞って確認し、要約や最近のワンタイムコードを取り出します。確認した情報源とスレッド、取得結果も明示します。
文書や会話、仕事の情報を内容に合う保存先へ整理し、ローカルファイルや知識ベース、GitHubなどを横断して重複確認、同期、検索を進めるスキル。
Per-conversation cost view — list every session in cost-tracking with started-at, message count, top model, and total cost
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。
Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to "search memory", "what did we discuss", "remember when", "find previous conversation", "check history", or before starting work to recall prior decisions.
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。
Author an eval for an existing skill from its REAL usage history, not its spec. Mine invocations from the brain's conversation archive (conversations/) and per-harness session transcripts — a user correction after an invocation is the gold signal — then synthesize an eval_contract plus 4-8 replayable cases with honesty labels (SPEC-DERIVED vs HISTORY-IMPLIED) and stage the result at skills/<name>/eval/autobench-<date>.md as PENDING-HUMAN-APPROVAL. Never rewrites SKILL.md. Ships two guard companions: panel integrity (multi-model judging must prove each provider actually responded) and the fail-improve taxonomy (logged LLM-fallback cases convert to deterministic code over time).
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。
Connect a ChatGPT or Claude account and sync its conversation history into the brain automatically. Cookie paste-in is the primary lane; sync is incremental (watermark + trailing-window gap-heal), and can run on a schedule via autopilot or host cron. Distinct from the export-file lane (that lives in conversation-archive) — this is the LIVE, account-connected, auto-scraping path.
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。
How to CONNECT Microsoft Teams (`kortix channels connect --platform teams`, prints a tenant-admin consent URL) and how to answer in Teams as a teammate. Covers the live Adaptive Card stream (`teams step` with --detail/--output/--source, `teams send` to finalize the answer), sending and downloading files (the consent-card upload flow + `teams download`), reading teams/channels/members through connector calls, asking the user, and the tone the bot should use. Load this when the turn is triggered from Teams (the prompt mentions a Teams tenant/conversation, or `$MS_TEAMS_CONVERSATION_ID` is set in the env), or when the user asks how to do anything in Teams.
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。
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search knowledge, what do we know about, archive, harvest, knowledge status, develop note, add to knowledge, ingest, contradictions, knowledge graph, retrieve, mine conversations, distill, weekly digest, cortex digest, context search, prior work, recall, remember, previous sessions, context recovery, what did we do, find session, search history, resume, pick up where we left off, cold start, yesterday's work, last week, the one about. NOT FOR published-content semantic search across blog/newsletter/X/LinkedIn, or one-shot URL/YouTube ingestion via the Arbol harvester pipeline.
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。
Save a user-selected answer, decision, insight, or session summary into an Obsidian vault as one reviewed transaction. Use only when the user explicitly asks to preserve specific conversation content, not when they supply a file or URL to ingest. Triggers: /save, save this, save that answer, file this conversation, save this analysis, keep this insight, preserve this chat result.
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。
Ask a person for access to one of their keychain credentials when a command needs it and this conversation has no grant yet. The platform posts an approval card where this conversation is happening; the owner clicks it, and the blocked command re-runs.
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 the Omnigent load test and produce a results file explaining the latencies. Load when the user wants to load-test / stress-test / benchmark Omnigent under concurrency ("load test omnigent", "stress test the server", "how many hosts/sessions/turns can it handle", "load test real agent turns / conversations", "run a load test"). The test makes each simulated user a real omnigent host that creates host-bound sessions and drives real multi-turn conversations with a mocked LLM; it boots its own local stack (dev/loadtest/run.py). Gather inputs, run it, then read the generated summary.md and explain the latency distribution (avg/median/p95/p99, throughput, failures). NOT for single-request latency micro-benchmarks (that is dev/benchmarks/).
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 X Ads measurement, X Pixel and Conversions API, campaign objectives, keyword and conversation targeting, creative, budgets, brand safety, app measurement, and reporting. Use for X Ads, Twitter Ads, promoted posts, X Pixel, X Conversions API, conversation targeting, or paid campaigns on X.
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。
X (Twitter) DM automated chat end-to-end Skill: scan DM inbox to identify pending-reply conversations, read message history, generate persona-based replies and send; also supports searching users and starting new conversations. Built-in E2E passcode unlock, DM permission filtering, and rate control. Use when user mentions X auto-reply DMs, Twitter DM automated chat, auto-handle unread DMs, reply to X private messages with persona, X DM outreach campaign, batch send DMs to Twitter users, auto-process pending DM replies, Twitter DM bot, automated Twitter outreach, X direct message automation.
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 what SenseNova Team Harness is, wants an introduction or overview, is getting started, or is deciding whether it fits — a self-hosted workspace where people and local AI agents collaborate on conversations, projects, work items, and artifacts. Covers its core concepts (Workspace, Project, Conversation, Agent, WorkItem, Resource, Artifact, Local Computer), main capabilities, how to run it, and the basic usage flow.
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。