'brain' 검색 결과

Create and manage GitHub issues for the Kilo VS Code extension or JetBrains plugin using gh, GitHub's command-line tool. Guides template selection, clear titles, required project board assignment, and authentication permissions.

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• Reporting a bug in the VS Code extension
• Requesting a feature for the JetBrains plugin
• Filing usage or design questions

Inspect Claude Code execution traces in Braintrust, including tool calls and token usage. The guide explains event hooks, troubleshooting missing records, and matching separate parent and sub-agent traces using timestamps and metadata.

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• Investigating missing execution traces
• Reviewing tool calls and token usage
• Matching parent and sub-agent execution records

Your team's shared, AI-ready knowledge base — people, companies, meetings, SOPs, and decisions structured so an agent can answer on your team's behalf. Team-scope sibling to second-brain. Modes — capture, compile (wiki pages + INDEX.md), query (trust-weighted, saved to outputs/), review (verify / deprecate / supersede stale captures), lint, connect, search. Structured raw dirs (people/, companies/, meetings/, sops/, decisions/, customer-language/, sales-objections/). Every capture stamps author, timestamp, and trust status. Optional sync from call transcripts, Slack/email exports, CRM. Vault at ${COMPANY_BRAIN_VAULT:-$HOME/Documents/CompanyBrain}/. Triggers on "/company-brain," "/cb," "capture this into the team brain," "log this meeting," "save this SOP," "compile the company wiki," "query the team brain," "what does the team know about X," "review the company brain," "lint the company brain," "who's the internal expert on X."

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Set up gbrain for this coding agent: install the CLI, initialize a local PGLite or Supabase brain, register MCP, capture per-remote trust policy. One command from zero to "gbrain is running, and this agent can call it." Use when: "setup gbrain", "connect gbrain", "start gbrain", "install gbrain", "configure gbrain for this machine". (gstack)

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Learn how to author a third-party gbrain skillpack through a reference example. It explains required files, ten validation criteria, tests, and evaluation coverage, helping authors understand what to check before packaging and publishing.

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• Learning the structure of a gbrain skillpack
• Checking requirements before publication
• Understanding test and evaluation files

Restructure raw article text stored in gbrain into summaries, exact quotes, key insights, and links to related pages. Preserve the original text and connect the article's significance to projects and interests already recorded in gbrain.

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• Organizing saved articles into readable notes
• Collecting exact quotes for essays
• Connecting articles to current projects

Turn meeting transcripts into structured GBrain pages with decisions, assigned tasks, and verified quotes. Resolve speakers using evidence, split recordings containing separate meetings, and update related people and companies with links and dated meeting context.

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• Organizing decisions and assigned tasks from a transcript
• Updating people and company records after a meeting
• Splitting a continuous recording into separate meetings

Move notes and structured data from Obsidian, Notion, and other supported sources into GBrain. Preserve the originals, map fields and cross-references, and check imported pages, links, and content after migration.

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• Move an Obsidian vault into GBrain
• Import a Notion export
• Turn CSV rows into knowledge pages

Extract references between imported documents and classify how they relate, such as relying on, extending, or refuting another work. Store these relationships as typed links so explicit graph queries can trace connections through the collection.

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• Tracing which papers extend earlier research
• Checking which decisions overrule or distinguish a case
• Following the documents a brief relies on

Compare saved knowledge with current web sources using Perplexity. This skill produces a cited research page that separates new developments, supporting evidence, and contradictions, with suggested updates to stored information about people, companies, or deals.

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• Updating stored information about people and companies
• Monitoring changes in companies and active deals
• Preparing briefings focused on new developments

Build, run, and debug the Kilo JetBrains plugin using its Gradle workflows. It covers isolated development storage, chat logs, sandbox recovery, and switching between a pinned CLI release and locally built CLI code.

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• Build a versioned plugin ZIP for testing
• Run the plugin in a sandbox or split mode
• Inspect chat logs and session events

Build and review JetBrains plugin interfaces using Swing and IntelliJ Platform components. Follow concrete rules for layouts, theme colors, fonts, spacing, dialogs, and tool windows while keeping shared style values consistent.

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• Building tool windows and settings screens
• Reviewing theme colors, fonts, and spacing
• Choosing components for dialogs and notifications

Review Claude Code sessions using Braintrust traces, records of agent activity. Summarize tool, agent, and skill usage, inspect repeated actions, replay sessions, and track token consumption to understand failures and recurring work patterns.

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• Reviewing a completed Claude Code session
• Investigating failures and repeated tool calls
• Checking weekly agent and skill usage

Turn incoming SMS, meeting events, and social mentions into cited pages in GBrain, a knowledge store. The workflow extracts people and other entities, updates timelines, sanitizes content, and preserves failed payloads for retry.

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• Save SMS events to a sender’s timeline
• Route completed meetings to meeting ingestion
• Record social mentions with source links

Create skills that follow GBrain’s required structure, including workflow steps, expected output, and failure handling. Check for overlapping triggers, update the skill registry and routing guide, and verify the result with conformance tests.

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• Create a skill for an uncovered user request
• Check for overlap with existing skill triggers
• Update skill registration and routing

Answer questions from saved gbrain knowledge using keyword, meaning-based, and relationship searches. The skill combines relevant evidence with page citations and highlights missing information, conflicting sources, or potentially outdated results.

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• Find saved notes on a topic
• Look up connections between people and companies
• Trace events and changes through timelines

Investigate slow jobs, stale data, and timeout alerts by timing the specific operation and comparing monitoring thresholds. Produce an evidence-based verdict that distinguishes insufficient time, stalled work, and false alerts before proposing changes.

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• Investigate repeated timeout alerts
• Check whether stale-data warnings reflect actual lag
• Compare monitor thresholds with gbrain doctor

Save shared articles, posts, and ideas to GBrain with analysis connected to existing knowledge and active projects. Preserve source material, credit authors, cite factual claims, and link related pages while updating existing entries for duplicate URLs.

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• Saving an article with analysis tied to an active project
• Keeping an entire tweet thread as one reference
• Recording sources and authors alongside saved ideas

Organize the outputs of a substantial work session into linked knowledge pages with sources. A seven-phase review checks classification rules, identifies reusable workflows, audits overlapping skills, and verifies that saved pages and skills can be found.

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• Saving the findings from a completed research session
• Organizing outputs from a development session
• Finding workflows worth turning into reusable skills

Manage shell commands and AI agent tasks through a shared gbrain job queue. Track progress, steer agents, pause or resume work, and coordinate parallel tasks, with guidance for long operations, completion reporting, and reusable stage checkpoints.

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• Run scripts as monitored background jobs
• Coordinate parallel research by AI agents
• Redirect, pause, or resume an agent task

Helps developers update the JetBrains chat session interface, including transcript cards, theme styling, and session state. Provides guidance for reusing UI components and testing controller behavior, streamed updates, and resource cleanup.

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• Updating transcript cards and expandable content
• Adjusting chat surfaces for editor themes
• Adding session state and events

When you want to capture into, compile, query, lint, or connect your personal Second Brain. Wraps the Karpathy LLM Wiki schema (Obsidian or any markdown vault) — raw/ (unprocessed sources), wiki/ (AI-compiled interlinked topic pages), outputs/ (generated artifacts). Tool-agnostic in design but defaults to a vault at ${SECOND_BRAIN_VAULT:-$HOME/Documents/SecondBrain}/. Six modes — capture (drop something into raw/), compile (process unprocessed raw files into wiki pages, update INDEX.md), query (answer a question from the wiki, save to outputs/), lint (orphans / contradictions / stale / unprocessed raw / topic gaps), connect (suggest new wikilinks between pages), search (quick lookup). Triggers on "/second-brain," "/sb," "capture this," "save this to my brain," "compile the wiki," "process raw notes," "query my wiki," "ask my brain," "lint the wiki," "find connections," "search my notes." Complements deep-research (external corpus) — this is the internal corpus.

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Generate a personalized Second Brain PRD from a completed requirements template. Use when the user has filled out my-second-brain-requirements.md and wants to generate their build plan. Triggers on "create my second brain PRD", "generate my PRD", "build my second brain plan", "/create-second-brain-prd", or after completing the requirements template.

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Kotlin과 JetBrains Exposed로 데이터베이스 조회와 추가·수정·삭제를 구현하는 패턴을 제공합니다. 연결 재사용, 구조 변경, 트랜잭션과 테스트도 다룹니다.

• 데이터베이스 조회와 수정 구현
• 데이터베이스 연결 재사용 설정
• 데이터베이스 구조 변경 관리