“ember”的搜索结果

Create shareable links that open specific Arize resources, including traces, datasets, and evaluators. Use IDs from logs or exported data, with suitable time ranges, to direct teammates to the relevant view.

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• Share a trace with teammates
• Open an Arize view from IDs in logs
• Link directly to a dataset or evaluator

Organize useful findings from a session and save them in the right place: project memory, temporary notes, or lasting documentation. The skill separates reusable facts from working context and flags duplicate, outdated, or conflicting information.

中文简介正在准备中。当前显示英语简介。

• Saving reusable project findings from a session
• Separating temporary notes from lasting knowledge
• Keeping conventions in the appropriate documentation

Set up and harden a Sliver server for authorized security exercises that simulate attackers. Cover multiple communication protocols, intermediary servers, certificate-based access for team members, and test programs that use periodic or interactive connections.

中文简介正在准备中。当前显示英语简介。

• Building a Sliver server for an authorized red-team exercise
• Configuring multiple communication protocols for an exercise
• Managing certificate-based access for multiple operators

Find LinkedIn prospects, candidates, companies, posts, jobs, services, and groups through Curviate CLI, a command-line tool. Guides filter setup and multi-page retrieval so searches use the intended criteria and incomplete results are identified.

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• Find sales prospects and recruiting candidates
• Identify companies by size and search their job postings
• Find relevant posts and service providers

Manage LinkedIn connection requests and follows with the Curviate CLI. Review pending invitations, preview actions, withdraw requests, and list connections or followers, with guidance on duplicate requests and delays before invitations appear.

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• Sending connection requests with a personal note
• Reviewing received invitations
• Withdrawing pending connection requests

Use Curviate CLI to retrieve LinkedIn profiles and company information, update your own profile, inspect company inboxes, and convert search terms into filter IDs. It also covers account connections and choosing stored or live profile data.

中文简介正在准备中。当前显示英语简介。

• Researching LinkedIn profiles and companies
• Updating your own headline and bio
• Finding IDs for location and industry filters

Design memory systems that help AI agents retrieve relevant past information. Choose short-term and long-term memory structures, compare vector storage options, and review document splitting and retrieval strategies for different kinds of knowledge and experience.

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• Design memory for information used across conversations
• Choose storage for experiences, facts, and procedures
• Review retrieval when an agent misses saved information

Build LlamaIndex applications that retrieve relevant material before generating answers, a method called RAG. Connect documents, websites, and databases to support document questions, conversational search, structured summaries, and checks of answer relevance and source consistency.

中文简介正在准备中。当前显示英语简介。

• Building question answering over internal documents
• Creating a chatbot that remembers the conversation
• Searching information across files, websites, and databases

Design AI agents that plan tasks, call tools, and retain useful information. Covers coordination between agents, evaluation, and debugging, with practical patterns for execution limits, error handling, and tracing what an agent does.

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• Designing an agent that plans and executes tasks
• Organizing tool definitions and selection
• Deciding what an agent should remember

Search past conversations to recover decisions, discussions, and context across sessions. Find related ideas by meaning, match exact terms, or locate code identifiers, with options to search only user or assistant messages through local AI Maestro tools.

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• Recalling decisions before resuming work
• Finding discussions with different wording
• Looking up conversations about a function or class

Define custom entities and relationships in cognee, a memory system for AI applications. This skill guides model design, identity matching, searchable fields, and troubleshooting when entities are duplicated or relationships are missing.

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• Designing custom entities and relationships
• Preventing duplicate entities across imports
• Investigating missing search results or relationships

Operate cognee from the terminal to store, retrieve, update, and remove information. Covers dataset and configuration management, ingestion cost estimates, session history access, and commands for inspecting or applying database migrations.

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• Storing documents and asking questions from the terminal
• Estimating token usage and cost before importing data
• Managing datasets and saved configuration

Run cognee in Docker, starting with a prebuilt image for local document ingestion and questions. It also covers Docker Compose profiles for adding the UI, MCP server, Postgres, and Neo4j, plus persistent data storage.

中文简介正在准备中。当前显示英语简介。

• Try cognee locally using a prebuilt Docker image
• Test document ingestion and questions through the API
• Start the UI, MCP server, and databases with Docker Compose

Tune cognee ingestion speed, query response time, and LLM costs by adjusting concurrency, text chunk sizes, request limits, and model choices. Estimate ingestion costs before processing and assess options for background work and deployment scaling.

中文简介正在准备中。当前显示英语简介。

• Estimating costs before importing documents
• Adjusting ingestion speed and request limits
• Reducing query response time

Share a Google Drive folder and its contents with collaborators. Find the folder by name, assign editing or viewing permissions to individual people, and check the resulting permissions after sharing.

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• Share project materials with team members
• Give stakeholders viewing access to a folder
• Check folder permissions after sharing

Turn a repeated manual task into a reusable skill you can call by name or schedule. It separates changing inputs from fixed steps, adds approval checkpoints, and tests the workflow against a known result before registration and team sharing.

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• Turning a weekly routine into a reusable skill
• Capturing a workflow demonstrated in conversation
• Adding approval checkpoints to business tasks

Create a role-specific onboarding plan for a new hire, covering accounts, equipment, a buddy, and the first week's activities. Include key contacts, required tool access, and goals for the first 30, 60, and 90 days.

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• Preparing a checklist before a new hire starts
• Planning Day 1 and the first week
• Setting goals for the first 30, 60, and 90 days

Analyze team workloads, available hours, and upcoming demand to build a resource capacity plan. Identify staffing gaps and bottlenecks, then compare hiring, contracting, reprioritizing, or delaying work within budget and schedule constraints.

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• Quarterly staffing and workload planning
• Checking workload imbalances across team members
• Comparing hiring with project reprioritization

Help Claude interpret workplace shorthand by storing people, acronyms, project names, and preferences in local files. Keep frequent references in CLAUDE.md and detailed context in memory/, so requests can be understood using recorded workplace knowledge.

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• Recording internal acronyms and terminology
• Linking nicknames to people and roles
• Looking up project codenames and background

Write and maintain technical documents for different readers, including READMEs, API references, operational procedures, architecture explanations, and onboarding guides. Organize practical examples, setup steps, design decisions, and recovery instructions around what each audience needs.

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• Create a README with a quick start
• Document API requests and responses
• Write operational and rollback procedures

Prepare a personal knowledge base for team sharing by removing compensation, performance assessments, personal details, and other sensitive content. The skill checks pages and searchable records, verifies the cleaned material, and addresses sensitive Git history with explicit confirmation.

中文简介正在准备中。当前显示英语简介。

• Creating a shared team knowledge base from personal notes
• Auditing an existing shared knowledge base
• Checking sensitive content before onboarding team members

Add persistent memory to NanoClaw agents using the default Claude provider. With mnemon installed in the container, agents retrieve relevant context before responding and save new insights after each turn, retaining memory across container restarts.

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• Recalling earlier conversations in a new session
• Keeping agent memory across container restarts
• Checking memory hooks and storage settings

Save research findings, fixes, and decisions in a shared Markdown notebook on disk. Search and organize notes across sessions, record when they inform actual work, and let unused notes expire automatically.

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• Saving research findings for future sessions
• Reusing fixes for difficult bugs
• Recording design decisions and their reasoning

Migrate TanStack Table from v8 to v9 by auditing API usage, state ownership, features, and TypeScript types. Follow a shared checklist and relevant mappings to preserve existing behavior and verify the updated table.

中文简介正在准备中。当前显示英语简介。

• Planning a TanStack Table v8 to v9 migration
• Updating feature registration and state management
• Resolving TypeScript changes during migration