본문으로 건너뛰기
cccskills
무료GitHub에 공개

context-budget

Use when a coding session is burning context fast, output is drowning in noise, the model keeps forgetting earlier decisions, or the user asks to reduce tokens, stop the verbose narration, work in a huge repo, or make a long session survive. Covers what to read, what to summarize, what to write to disk, and when to start fresh.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(1)

  • SKILL.md3.7 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Context Budget

Context is the scarcest resource in a long session. It gets spent on three things: files you read, output you generate, and narration nobody asked for. Only the first one is usually worth it.

Core Behavior

Treat the context window like a budget with a balance. Before any expensive action — reading a big file, running a chatty command, dumping a directory tree — ask what the cheapest way to get the same answer is.

Spend Rules

Read narrowly. sed -n '120,190p' file.ts beats reading a 2,000-line file to see one function. Grep for the symbol, then read the 40 lines around it. Read a whole file only when you are about to restructure it.

Search before reading. grep -rn "symbolName" --include="*.ts" costs a few hundred tokens and tells you which of forty files matters.

Silence the noisy commands. Pipe installs, builds, and test runs through a filter instead of dumping them whole:

npm test 2>&1 | tail -30
npm run build 2>&1 | grep -E "error|Error|warning" | head -20
npm install --silent 2>&1 | tail -5
git diff --stat            # not git diff, unless you need the hunks

A passing test suite needs one line of proof, not 400.

Write instead of remembering. Anything that must survive — a plan, a decision, a list of files to touch — goes in a file on disk. Files are re-readable at a cost you choose; context is not.

Do not re-read what you just wrote. If an edit succeeded, it succeeded. Re-reading to "verify" is pure spend.

Cut the narration. No preamble, no recap of what was just shown, no bulleted summary of a diff the user can see. Say what changed and what is next, in a line or two.

Where the Budget Actually Goes

When a session bloats, it is almost always one of these:

LeakFix
Whole-file reads for one functiongrep, then a line-ranged read
Full npm install / build logs| tail -n or grep for errors
Directory listings of node_modules, dist, .nextprune them in the find/ls
Re-reading files after editingtrust the edit result
Long explanations of finished workone line
Pasting a file back to show a small changeshow the diff hunk only
Repeating the plan every turnplan lives in a file

Compaction Points

When roughly two-thirds of the window is gone, stop adding and start consolidating:

  1. Write the current state to a plan or handoff file on disk.
  2. State the single next action.
  3. Tell the user a fresh session will be faster and more accurate than continuing.

A fresh session that reads a good plan file outperforms a stuffed session every time. Do not treat starting over as failure — it is the intended move.

Large Repos

  • Map before you dig: directory names and entry points first, implementation later.
  • Follow imports from the entry point rather than crawling folders alphabetically.
  • One subsystem at a time. Finish it, write down what you learned, move on.
  • Generated code, lockfiles, and snapshots are never worth reading. Exclude them by default.

What Not to Cut

Economy has a floor. Never skip:

  • Reading the actual code before changing it.
  • The error output when something failed — that is the one long dump worth having.
  • The user's own requirements, quoted.

Being cheap about the wrong thing produces confident, wrong work. The goal is fewer tokens, not less evidence.

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

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OneWave-AI/claude-skills3682026년 10월 20일 업데이트

OneWave-AI의 스킬 모두 보기

이 스킬의 문제 신고