「knowledge」の検索結果

Cherry Studio first-party tool and bundled-shell routing for general agents. For straightforward local work in shell-capable sessions, run JS/TS with `bun <file>` and one-off JS tools with `bun x`; run Python with `uv run [--with <pkg>] python` and one-off Python CLIs with `uvx`; search with `rg`. Load this guide before changing project dependencies, deciding whether a tool should be ephemeral or reusable, reading or converting local Office/PDF files, coordinating or delegating across Agent Sessions, or using Cherry-owned web/browser, knowledge, persistent memory, schedules/notifications, IM channels, image generation, artifact reporting, managed CLI, skill, or MCP-server-registration capabilities—even if the user names no tool. Consult it before shell/file workarounds; live tool schemas are authoritative.

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Store team knowledge, project conventions, and learnings from tasks. Use to remember what works and recall context before new tasks. Connects to Hindsight Cloud. (user)

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Store team knowledge, project conventions, and learnings from tasks. Use to remember what works and recall context before new tasks. Connects to a self-hosted Hindsight server. (user)

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 this machine's Hindsight coding-agent memory works — the plugin behind the 🧠 banner. Use when the user says "store/remember this in hindsight", asks what the memory/knowledge pages are, wants to configure per-repo memory (disable, rename banks, git depth), or something memory-related looks broken.

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Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.

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Queries a pinned Precision Medicine Knowledge Graph (PrimeKG) CSV for typed gene, drug, disease, and phenotype nodes, direct associations, disease context, and one- or two-hop paths. Use for PrimeKG reproducibility, biological association lookup, and hypothesis generation with relation and data provenance preserved.

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Queries documented public database APIs with explicit endpoints, filters, pagination, and provenance. Used when a scientific, regulatory, financial, or other database-backed fact must be retrieved reproducibly from a named source rather than inferred from general knowledge.

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Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"

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Use when you need a deep, implementation-ready engineering plan for a code change — built from GitNexus graph intelligence, statement-level PDG analysis, and targeted source verification, compact enough that an implementation agent can start without re-investigating. Also strengthens existing plans via Deepen mode. Examples: "/gitnexus-plan Add retry support to the ingestion pipeline", "/gitnexus-plan deepen docs/plans/<plan>.md", "plan this change using the knowledge graph".

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Ask real executives and domain experts a question through Instant Expert for a written answer or short call: practitioner knowledge, customer discovery. Free test mode; live sends need approval.

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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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Compiled CLI covering all 52 endpoints of the Anytype local API — objects, properties, tags, search, chat, files — one binary, no MCP server needed.

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Modern Angular (v20+) expert with deep knowledge of Signals, Standalone Components, Zoneless applications, SSR/Hydration, and reactive patterns.

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Announcement board: author, category, department, priority, audience, publish and expiry dates, status and acknowledgements, as CSV, SQL, JSON Schema or Notion on request. Use for internal notices.

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A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

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A hybrid memory system that provides persistent, searchable knowledge management for AI agents.

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Configure, manage, and use DeepTutor through its CLI, including capabilities, knowledge bases, partners, memory, sessions, notebooks, providers, skills, and the server or Web app.

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Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.

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Use when maintaining a durable Markdown knowledge store that agents compile from sources, when every number or quote in a wiki page must trace back to an immutable source, or when compiled pages need cheap drift detection against the code they describe. Teaches the raw/wiki/archive layout, per-claim provenance links, and git fingerprints for zero-token staleness checks.

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Courses whose content rests on current, external or real-world facts that must be verified against live sources before being taught — recent events, market or policy data, product and version specifics, scientific developments, named cases. Researches the topic first, keeps a claim-to-source ledger, and grounds the outline and every page in what was actually fetched. Use when the request depends on up-to-date or externally checkable facts; not for timeless textbook topics that stand on established knowledge alone.

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Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.

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Expert on the history, origin, and correct use of the em dash. Use when writing or reviewing code, comments, or data files to avoid em and en dashes, defaulting to never using them and replacing any found with a hyphen (-). Includes strong knowledge of punctuation marks and the proper usage of punctuation characters when writing comments.

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Use Copilot Spaces to provide project-specific context to conversations. Use this skill when users mention a "Copilot space", want to load context from a shared knowledge base, discover available spaces, or ask questions grounded in curated project documentation, code, and instructions.

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Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

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。