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.
npx skills add idoforgod/Dissertation-Simulator-AgenticWorkflow --skill workflow-generatorgit clone --depth 1 https://github.com/idoforgod/Dissertation-Simulator-AgenticWorkflowWrote 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/skills/idoforgod/dissertation-simulator-agenticworkflow/workflow-generator)<a href="https://agentmods.dev/skills/idoforgod/dissertation-simulator-agenticworkflow/workflow-generator"><img src="https://agentmods.dev/badge/skills/idoforgod/dissertation-simulator-agenticworkflow/workflow-generator/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/skills/idoforgod/dissertation-simulator-agenticworkflow/workflow-generator"><img src="https://agentmods.dev/badge/skills/idoforgod/dissertation-simulator-agenticworkflow/workflow-generator.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 | $0.00042 | $0.06349 |
| Opus 5.5 | $0.00017 | $0.02540 |
| Sonnet 5.5 | $0.00008 | $0.01270 |
| Haiku 4.5 | $0.00004 | $0.00635 |
Grade A, and why
workflow-generator 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 2mo 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 — 390 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Generator
Inherited DNA
This skill inherits the AgenticWorkflow genome.
| DNA Component | Expression |
|---|---|
| Absolute Criteria 1 | Quality of generated workflow is the sole criterion; speed/token cost ignored |
| Absolute Criteria 2 | Reads SOT for context; writes workflow.md and supporting files |
| English-First | All workflow definitions in English; Korean documentation via @translator if needed |
Claude Code용 워크플로우 정의 파일(workflow.md)을 설계하고 생성하는 스킬.
사용 케이스 판별
먼저 사용자의 상황 파악:
| 조건 | 케이스 | 진행 방식 |
|---|---|---|
| PDF/문서 첨부됨 | Case 2 | 문서 분석 우선 → 확인 대화 |
| 아이디어만 언급 | Case 1 | 대화형 질문으로 요구사항 수집 |
Case 1: 아이디어만 있는 경우
사용자가 막연한 아이디어만 가지고 있을 때.
Step 1: 목적 파악
다음 질문으로 워크플로우 목적 도출:
- "어떤 결과물(output)을 만들고 싶으신가요?"
- "이 워크플로우가 해결해야 할 문제는 무엇인가요?"
- "주요 입력(input) 소스는 무엇인가요?"
Step 2: 단계 정의
각 Phase별 구체적 단계 도출:
- "Research 단계에서 어떤 정보를 수집해야 하나요?"
- "Planning 단계에서 어떤 검토/승인이 필요한가요?"
- "최종 산출물의 형태와 품질 기준은 무엇인가요?"
Step 3: 휴먼-인-더-루프 식별
- "어느 단계에서 사람의 검토/승인이 필요한가요?"
- "자동화해도 되는 단계와 반드시 확인이 필요한 단계를 구분해주세요."
Step 4: 구현 설계 → 생성
요구사항 수집 완료 후 workflow.md 생성.
Case 2: 설명 문서가 있는 경우
사용자가 PDF 등 구체적인 설명 문서를 첨부했을 때.
Step 1: 문서 심층 분석
반드시 문서를 먼저 꼼꼼히 읽고 다음을 추출:
1. 핵심 목적: 이 워크플로우가 달성하려는 최종 목표
2. 주요 단계: 문서에서 언급된 프로세스/단계들
3. 입출력 정의: 각 단계의 input/output
4. 기술적 요구사항: 필요한 도구, API, 데이터 소스
5. 제약 조건: 품질 기준, 시간 제한, 의존성
6. 휴먼-인-더-루프: 사람 개입이 필요한 지점
Step 2: 분석 결과 공유
문서 분석 후 사용자에게 이해한 내용 요약 제시:
## 문서 분석 결과
**워크플로우 목적**: [추출한 목적]
**파악된 주요 단계**:
1. [단계1]: [설명]
2. [단계2]: [설명]
...
**식별된 휴먼-인-더-루프 지점**:
- [지점1]: [이유]
**기술적 구현 방향**:
- Sub-agents: [에이전트 목록 — 단일 세션 내 위임]
- Agent Team: [팀 구성 — 독립 세션 간 병렬 협업이 필요한 경우]
- Hooks: [자동화 트리거 — 품질 게이트, 포맷팅, 검증]
- 필요 도구: [도구/MCP 목록]
**확인이 필요한 사항**:
1. [질문1]
2. [질문2]
Step 3: 확인 대화
분석 결과를 바탕으로 짧은 확인 질문:
- "제가 파악한 내용이 맞나요?"
- "추가하거나 수정할 부분이 있으신가요?"
- "[불명확한 부분]에 대해 좀 더 설명해주시겠어요?"
Step 4: 생성
확인 완료 후 workflow.md 생성.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 390 lines · 42 tokens per session scan A 2d465664ad65
workflow-generator is a skill published in the GitHub repository idoforgod/Dissertation-Simulator-AgenticWorkflow (108 stars, last pushed 5mo ago), licensed MIT. It adds 42 tokens to every session and 6,349 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.
workflow-generator compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| workflow-generatoridoforgod/Dissertation-Simulator-AgenticWorkflow | Skill | 108 | 5mo ago | MIT | A | 42 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 2d ago | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 315k | 5d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |