'completion' 검색 결과

Check generated PDFs with PyPDF2 before reporting completion. A Python script verifies that each file can be opened and has the expected page count, helping identify outputs that need regeneration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking a generated one-page summary
• Verifying page counts across multiple PDFs
• Checking PDFs before reporting completion

Define when a file creation task is complete: the deliverable is saved, contains the required content, and uses the correct format and location. Verify those conditions, then report completion without searching for an unnecessary submission tool.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finish a document creation task after verifying the saved file
• Confirm completion of generated code files
• Check the format and location of a data export

Guides task delegation to Worker agents, completion handling, and recurring task management. It explains how to register assignments, synchronize task files and results, and choose the relevant procedure when checking worker availability or updating task state.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Selecting an available Worker for a task
• Registering and delegating a one-off task
• Retrieving results after a completion report

Manage an assigned Worker task from acceptance through delivery using taskflow. Keep work and optional progress notes in the task directory, submit structured results with deliverable paths, and report completion or blockers to the coordinator.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Accept an assigned task and read its requirements
• Organize deliverables and progress notes by task
• Submit results with completion or revision status

Use this skill when the user is doing hands-on DOCA RDMI (RDMA Initiator) programming — picking doca-rdmi vs doca-rdma for an accelerator-initiated one-sided RDMA flow, standing up a doca_rdmi_connection or doca_rdmi_poster, attaching a doca_dpa_completion or doca_verbs_cq before doca_ctx_start(), retrieving the DPA-side handle for a DPA kernel, auditing whether a doca_rdmi_* symbol is EXPERIMENTAL on this DOCA, or debugging DOCA_ERROR_* returns from RDMI calls. Trigger even when the user does not say "DOCA RDMI" or "initiator" — implicit phrasings include "my DPA kernel needs to post RDMA writes to a remote responder", "DPA kernel sees no completions", "function not found on doca_rdmi_* at link time", "DOCA_ERROR_BAD_STATE from completion attach", or "the DPA posted but the work request never arrived". Refuse and route elsewhere for two-sided or host-CPU RDMA, the DPA programming model, GPU-side RDMA initiation, or general RDMA/IB/RoCE concepts — those belong to other skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert collection-loop systems for collectible IDs, scavenger hunts, completion archives, nearest-item compass UI, hidden spawners, and persistent find-all-X progress. Use when implementing collectibles, scavenger hunts, completion% archives, or compass-guided item hunts. Keywords: collectible_id, scavenger_hunt, collection_manager, collection_compass, completion_archive, hidden_item_spawner, find_all, collectible_item.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert collection-loop systems for collectible IDs, scavenger hunts, completion archives, nearest-item compass UI, hidden spawners, and persistent find-all-X progress. Use when implementing collectibles, scavenger hunts, completion% archives, or compass-guided item hunts. Keywords: collectible_id, scavenger_hunt, collection_manager, collection_compass, completion_archive, hidden_item_spawner, find_all, collectible_item.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Plan, implement, or review verification before completion work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests verification before completion work.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when work produces a deliverable, factual claim, dataset, code change, decision, publication, deployment, automation, or irreversible action whose failure would matter; when the user asks for a quality gate, acceptance criteria, QA, completeness, validation, audit, evidence, preflight, release readiness, or a definition of done; or before claiming completion on medium- or high-risk work. Automatically decide whether a formal gate is warranted, derive task-specific pass/fail criteria, gather evidence, and block unsupported completion. Make sure to use this skill even when the user does not say "quality gate" if consequential work needs acceptance criteria or completion evidence. Skip formal gating for trivial, reversible, low-impact requests.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

tmux에서 실행 중인 대화형 명령줄 프로그램의 화면을 확인하고 문자와 키를 보냅니다. 세션 목록, 출력 기록 조회, 입력 대기와 처리 완료 감시에 활용합니다.

• 대화형 프로그램의 출력 확인
• 실행 중인 세션에 문자와 키 전송
• 입력 대기와 처리 완료 감시

작업 완료나 오류 수정 성공을 보고하기 전에 테스트와 빌드를 실행하고 결과를 확인합니다. 커밋이나 풀 리퀘스트 생성 전에도 실제 출력을 근거로 현재 상태를 전달합니다.

• 완료 보고 전 결과 확인
• 오류 수정 여부 검증
• 커밋이나 풀 리퀘스트 생성 전 검증

AI 에이전트가 읽는 스킬과 지침 문서를 작성하고 편집하도록 돕습니다. 절차, 참고 정보, 완료 조건을 정리하고 자료를 읽을 조건과 중복 내용을 검토합니다.

• 스킬 문서 작성과 편집
• AGENTS.md와 CLAUDE.md 정리
• 참고 자료를 읽을 조건 명확화

AI에 보낼 요청의 목표와 부족한 정보를 정리하고 작업에 맞는 ECC 명령과 스킬을 제안합니다. 진단과 수정 이유를 덧붙여 바로 붙여 넣을 요청문으로 다듬습니다.

• 모호한 개발 요청 구체화
• 완료 조건과 검증 절차 추가
• 작업에 맞는 ECC 구성 선택

Claude Code가 작업을 마칠 때 학습 기록 수정 시각과 디스크 여유 공간을 확인해 조건에 따라 완료를 막습니다. 대화에서 절차 생략을 암시하는 표현도 경고합니다.

• 복잡한 편집 후 학습 기록을 확인할 때
• 디스크 공간 부족 시 완료를 막을 때
• 확인 생략을 암시하는 표현 탐지

NVIDIA GPU에서 대규모 언어 모델의 응답 생성을 가속하고 API로 제공하도록 설정을 돕습니다. 양자화, 일괄 처리, 여러 GPU로의 분산도 다룹니다.

• 언어 모델을 채팅 API로 제공
• 많은 프롬프트를 일괄 처리
• 양자화로 메모리 사용량 감소

Handle tasks managed by Paperclip by reading their context, saving documents and deliverable files, updating progress and blockers, and coordinating delegated work. The skill provides procedures for short agent runs, approvals, and traceable task updates.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming assigned work with its latest task context
• Delivering documents and downloadable files on a task
• Recording completion, dependencies, or pending questions

Generate music through Venice.ai, handling queued requests, completion, and result retrieval. Use it to create short jingles, repeating background music, or provisional scores for prototypes as part of an agent-assisted music workflow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a short jingle
• Generating a repeating background music loop
• Making provisional music for a prototype

Organize new features, complex implementations, and architecture changes into the SPARC stages: specification, pseudocode, architecture, refinement, and completion. Define requirements and acceptance criteria, consult existing patterns, and record lessons for future work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Defining requirements for a new feature
• Organizing a complex implementation
• Planning an architecture change

Send proofs, planning questions, or difficult debugging tasks to DeepSeek's reasoning model. Receive the final answer and model-provided reasoning text in separate fields, with token usage reported for reviewing responses and costs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Requesting a mathematical proof
• Planning work that requires several reasoning steps
• Investigating root causes of difficult bugs

Send a single request to DeepSeek for summarization, information extraction, or simple classification. Receive the response and token usage as JSON for further processing, with structured status information when the API is unavailable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Summarizing text in a single request
• Extracting information from text
• Classifying text into simple categories

Track objectives across multiple conversations by defining milestones, saving progress and findings, and planning each session. Review completion criteria and flag schedule risks, scope changes, or dependencies that may require a different approach.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Track progress on a feature spanning several weeks
• Carry research findings into the next session
• Review delays and scope changes in a migration project

Choose the next task using patterns learned from completed work and current progress. The skill acts on confident predictions, falls back to task priorities when confidence is low, and updates its learning after completion.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing the next task from current progress
• Guiding repeated work within a /loop
• Finding relevant examples in past completions

Breaks long-running goals into small, verifiable steps, tracks progress, and records evidence from actual operation. Checkpoints preserve what has been proven so work can resume after interruptions and continue toward explicit completion criteria.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Managing a long-running development goal
• Resuming work after an interruption
• Recording evidence for completion criteria

Work through project decisions one question at a time, with a recommended answer and a short explanation. Record settled choices in project documentation, including scope, completion criteria, constraints, risks, and unresolved questions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clarify project goals through a decision interview
• Agree on deliverables and completion criteria
• Record settled decisions in project documentation