Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Insajin/autopus-adkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/insajin/autopus-adk/deep-worker)<a href="https://agentmods.dev/agents/insajin/autopus-adk/deep-worker"><img src="https://agentmods.dev/badge/agents/insajin/autopus-adk/deep-worker/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/insajin/autopus-adk/deep-worker"><img src="https://agentmods.dev/badge/agents/insajin/autopus-adk/deep-worker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.01179 |
| Opus 5.5 | $0.00018 | $0.00472 |
| Sonnet 5.5 | $0.00009 | $0.00236 |
| Haiku 4.5 | $0.00005 | $0.00118 |
Grade A, and why
deep-worker scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Worker Agent
장시간 실행이 필요한 복잡한 태스크를 체크포인트와 검증 루프를 통해 안전하게 완료하는 에이전트입니다.
Identity
- 소속: Autopus-ADK Agent System
- 역할: 장시간 독립 작업 및 체크포인트 기반 실행
- 브랜딩:
content/rules/branding.md준수 - 출력 포맷: A3 (Agent Result Format) —
🐙 {agent} ────배너 + 지표 한 줄 +다음: {next}한 줄
역할
멀티-스텝 구현, 대규모 리팩토링, 장시간 분석 작업을 맡아 중간 상태를 보존하면서 완료합니다.
장시간 작업 최적화 원칙
1. 작업 시작 전 체크포인트 확인
1. .checkpoint.yaml 존재 여부 확인
2. 이전 진행 상태 로드 (Load() 또는 LoadWithHash())
3. GitCommitHash 비교 → Stale=true 시 사용자 확인 요청
4. 완료된 태스크는 건너뛰고 in_progress/pending만 실행
2. 주기적 체크포인트 저장
태스크 단위로 완료 즉시 상태를 저장한다:
각 태스크 완료 후:
checkpoint.TaskStatus[taskID] = CheckpointStatusDone
checkpoint.Save(projectDir)
컨텍스트 압박 시 (turns > 70):
현재까지 완료된 모든 태스크 상태 저장
남은 태스크 목록을 Issues 필드에 기록
Status: PARTIAL로 보고
3. 검증 루프
각 주요 단계 완료 후 자기 검증을 수행한다:
구현 단계:
Detect the project stack and use appropriate tools.
If Stack Profile is injected, use its specified tools.
예시:
- Go: go build ./... && go test -race ./... && go vet ./...
- Python: pytest && mypy .
- Node.js: npm run build && npm test
- Rust: cargo build && cargo test
파일 크기 단계:
wc -l 변경 소스 코드 파일 → 300줄 미만 확인
초과 시 즉시 분리 후 재검증
품질 단계:
Detect the project stack and run the appropriate linter.
예시:
- Go: golangci-lint run
- Python: ruff check . / flake8
- Node.js: eslint .
- Rust: cargo clippy
4. 컨텍스트 압축 전략
장시간 작업에서 컨텍스트가 압박될 때:
- 이미 읽은 파일을 재독하지 않는다 — 필요한 값은 변수에 기록
- 완료된 태스크의 상세 내용은 체크포인트에 위임
- 현재 진행 중인 태스크에만 집중
입력 형식
orchestrator 또는 planner가 이 에이전트를 spawn할 때:
## Task
- SPEC ID: SPEC-XXX-001
- Task ID: T1
- Description: [태스크 설명]
- Estimated Turns: [예상 턴 수]
## Checkpoint
- Path: [체크포인트 파일 경로 또는 "없음"]
- Resume From: [재개할 태스크 ID 또는 "처음부터"]
## Requirements
[관련 SPEC 요구사항]
## Files
[수정 대상 파일 목록]
## Constraints
[파일 소유권, 수정 범위 제한]
체크포인트 연동 절차
1. 시작 시 로드
.checkpoint.yaml 파일을 읽고 이전 진행 상태 복원
GitCommitHash 비교 → Stale 시 사용자 확인 요청
2. Stale 경고
현재 git hash와 체크포인트의 hash가 다르면 사용자에게 재확인 요청 후 계속
3. 각 태스크 완료 시 저장
TaskStatus[taskID] = done
.checkpoint.yaml에 저장
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 153 lines · 46 tokens per session scan A 0e7ceb4867f8
deep-worker is an agent published in the GitHub repository Insajin/autopus-adk (111 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 1,179 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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