본문으로 건너뛰기
cccskills
무료GitHub에 공개

paced-explanation

Use when asked to explain or teach a subsystem, module, pattern, or change in progressive layers from purpose to code depth. Not for design rationale: use why. Not for source or remote-system changes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(2)

  • SKILL.md3.7 KB
  • agents/openai.yaml195 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Paced explanation

Contract

FieldBound contract
TriggerUser asks to teach or explain a subsystem, module, pattern, or change.
AuthorityRead-only. No file, VCS, credential, paid, published, deployed, or remote mutation.
Side effectChat output only; inline diagrams on request.
DoneFour layers delivered in sequence (purpose, structure, behavior, code), each grounded in concrete file paths, line ranges, or symbols from the resolved target; the explanation progresses purpose → structure → behavior → code without skipping a layer; deeper layers offered after each. The explanation may stop after any delivered layer that was followed by a deeper offer.

Inputs

  • Target (required): the subsystem, module, pattern, or change to explain. Supplied as an argument, a file path, or the current conversation context.
  • Depth (optional): explicit depth ceiling or focus area. Absent means begin at the purpose layer (Layer 1) and offer deeper.

Procedure

  1. Identify the target. Resolve the target to concrete code: file paths, line ranges, and key symbols. Use grep, glob, read, or LSP tools. If the target cannot be resolved after one read of the conversation, stop and ask one clarifying question naming what to explain. Done when: the target is resolved to concrete file paths, line ranges, and key symbols, or one clarifying question is asked.
  2. Map the scope. Identify the entry point, internal structure, and external interfaces of the target. Build a lightweight mental map: what the subsystem owns, what it delegates, and how it is named in the codebase. Done when: the entry point, internal structure, and external interfaces are identified.
  3. Explain in progressive layers. Deliver the explanation as a flat sequence from surface to depth, with each layer building on the previous:
    • Layer 1: Purpose: what the target does and why it exists in one sentence.
    • Layer 2: Structure: how the target is organized and what the main components are.
    • Layer 3: Behavior: how the components interact and what the key inputs and outputs are.
    • Layer 4: Code: the key symbols, line ranges, and the logic they encode. Done when: all four layers are delivered in sequence from purpose to code.
  4. Offer deeper layers. After each layer, invite the user to request more depth. Accept a focus area or continue layer by layer. Stop when the user stops. Done when: an explicit invitation to go deeper follows each delivered layer, and no layer is delivered without the offer that follows it.
  5. Render diagrams on request. If the user asks for a diagram, render an inline diagram (ASCII, Mermaid, or HTML) showing the structure or flow. No external diagram tool required. Done when: the requested diagram is rendered inline.

Failure and recovery

  • Unresolvable target: the target cannot be identified from argument, path, or conversation context. Stop. Ask one question naming what to explain. Do not invent a target.
  • Partial code context: the target resolves to a partial view of the codebase. Explain what is visible. Mark where the picture is incomplete. Do not claim the explanation is complete when it is not.
  • No rollback required: this skill is read-only. No file, state, or remote resource is modified.

Output

A single plain explanation in layered prose, starting from purpose and progressing to code depth on request. Diagrams rendered inline on explicit request. No persistent workspace, no session state, no multi-turn follow-up required.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Use when explaining System V AMD64, ARM AAPCS, RISC-V psABI, stack frames, variadic calls, or FFI register rules. Not for the Rust FFI binding layer: use rust-ffi.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OutlineDriven/odin-claude-plugin372026년 9월 29일 업데이트

Use when configuring ADC sampling time, DMA-driven ADC, calibration, or DAC channel setup on bare-metal MCUs. Not for the DMA stream itself: use dma-baremetal.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OutlineDriven/odin-claude-plugin372026년 9월 29일 업데이트

af-xdp

무료

Use when creating AF_XDP sockets, configuring UMEM and XSK rings, writing an XDP redirect program, or choosing copy versus zero-copy mode. Not for full kernel bypass: use dpdk.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OutlineDriven/odin-claude-plugin372026년 9월 29일 업데이트

Use when a completed session needs an agent-environment retrospective. Not for an engineering retrospective from telemetry: use engineering-retrospective.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OutlineDriven/odin-claude-plugin372026년 9월 29일 업데이트

Use when a redacted, trimmed agent transcript must be appended to a GitHub PR or issue body, with human approval and preview. Not for automated or model-initiated insertion.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OutlineDriven/odin-claude-plugin372026년 9월 29일 업데이트

agents-md

무료

Use when a repo needs agent setup, AGENTS.md added or made lean, CLAUDE.md audited, or agent instructions scored or pruned. Not for remote, credential, publish, deploy, or irreversible changes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OutlineDriven/odin-claude-plugin372026년 9월 29일 업데이트

OutlineDriven의 스킬 모두 보기

이 스킬의 문제 신고