agentic-workflow-guide
Design, review, and debug agent workflows, and decide when a request should use a prompt, instruction, skill, agent, or hook before escalating to multi-agent design. Use for .agent.md / .instructions.md / .prompt.md / AGENTS.md work, workflow architecture, orchestration planning, scheduled automation model allocation, or when agent workflows may be overkill. Triggers on 'agent workflow', 'create agent', 'automation models', 'ワークフロー設計', 'orchestrator'.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/aktsmm/agent-skills --skill agentic-workflow-guide- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads agentic-workflow-guide automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Agentic Workflow Guide
Design, review, and improve agent workflows based on proven principles.
この SKILL の基本姿勢は、agent を増やすことではなく、必要最小の primitive で解くこと。 context が膨らんだときも、まずは split / compact / reference 化を考え、いきなり multi-agent にしない。
Primitive First
Do not start with multi-agent by default.
- Single focused slash task -> Prompt (Local harness only; prompt files are deprecated for Agent Host sessions, so prefer a Skill for new slash workflows)
- Always-on or file-scoped guidance -> Instruction
- Reusable workflow with bundled assets -> Skill
- Persona, tool restrictions, delegation, or handoffs -> Agent
- Deterministic enforcement -> Hook (Preview; events and config differ by harness)
If the ask does not require an Agent, stop and use the simpler primitive.
Selection details: references/customization-decision.md
When to Use
| Action | Triggers |
|---|---|
| Create | New .agent.md, .instructions.md, .prompt.md, AGENTS.md, or workflow architecture |
| Review | Orchestrator not delegating, design principle check, context overflow |
| Update | Adding Handoffs, improving delegation, tool configuration |
| Debug | Agent not found, subagent not working, picker visibility, access control |
| Decide | Determining whether multi-agent is justified or a simpler primitive is enough |
Core Principles
- Simplicity First: より単純な primitive で解けるなら agent 化しない
- SSOT / SRP: 情報源と責務の分割を守る
- Fail Fast: エラーは早く止める
- Feedback Loop: 各段で検証できるようにする
- Context Discipline: context が膨らんだら compact / split / retrieve を検討する
Principle details: references/design-principles.md
Pattern Selection
Name the pattern explicitly when complexity rises, using the selector in references/workflow-patterns/overview.md. Every loop needs explicit stop conditions.
Design Workflow
- Extract repeated behavior, tool preferences, and workflow shape from the conversation.
- Choose primitive + scope (workspace / profile); ask only about ambiguities that change behavior.
- Escalate only when split / compact / reference-ization cannot solve it, then pick a pattern.
- Implement the smallest version and tighten the weakest parts.
Rule Placement
- 汎用的な workflow 設計原則は、この SKILL と
references/を SSOT にする。 - repo local の
.instructions.mdには workspace 固有の差分だけを残す。差分が無い generic instruction は merge back して削除候補にする。 - IR は原則 in-memory で扱う。validator、script、deterministic handoff が必要な場合だけ中間 file を materialize し、不要になったら片付ける。
- scheduler / service / config など決定論的な state mutation は、AI/UI loop ではなく direct script / API で現状確認 -> 最小変更 -> live read-back まで行う。LLM は scope と整合対象の判断に限定する。
- For model allocation reviews, use scheduled runtime bindings.
Escalation Rules
Prefer the lowest level (L0 prompt → L1 + instructions → L2 single agent → L3 multi-agent) that solves the problem cleanly. Quick signals to split:
- Prompt > 50 lines
- Steps > 5
- "missed" / "overlooked" errorsが続く
- Multiple responsibilities in one agent
- Context > 70%
Threshold details: references/splitting-criteria.md
Review Gates
- Primitive choice is simpler than agent if possible
- Placement is appropriate and always-loaded entry files stay thin (entry boundary smells: review-checklist.md)
- New additions are proposed only after delete / merge / split / move options are checked
- Single responsibility per agent is preserved
- Errors can be detected and stopped early
- Verify actual producer-to-consumer dataflow, not only fixtures injected into a validator; cover empty results and meaningful state transitions. Repeating unchanged input proves idempotency, not the full lifecycle.
- Deterministic parts are offloaded to scripts / IR / hooks, and state changes are confirmed by reading authoritative live state back (not LLM/UI loops)
Full checklist: references/review-checklist.md
Reference Map
Core references: primitive decision, design principles, workflow patterns, splitting criteria, review checklist, and context management.
For scheduled workflows, use scheduled runtime bindings. For delegated evidence and append-only current-state extraction, see orchestrator-workers and IR architecture.
When an orchestrator promises delegation but works directly, make the delegation requirement explicit and verifiable (agent-guide.md). Tool mapping and agent scaffold: agent-template.md.
Done Criteria
- Primitive and scope selected intentionally
- Workflow pattern selected and confirmed with user
- New or updated assets have clear Role/Workflow/Done Criteria where applicable
- Review Gates passed
- Recommendations are classified as delete / merge / split / move / add / keep where applicable
- Always-on instruction boundaries and DRY / SSOT risks are explicitly reviewed when
copilot-instructions.mdorAGENTS.mdare in scope - New agent / workflow assets are registered in the appropriate catalog or docs when needed
-
AGENTS.mdis updated only when shared guardrails or entry behavior need to change - Long-running or ad-hoc terminals/tasks started during the workflow are closed, or remaining terminals are explicitly reported with a reason
- Distinguish configuration saved, code tested, live read verified, action authorized, and recurring cycle completed. Verify authoritative state before claiming completion or unattended readiness; pending safeguards and unobserved cycles retain their blockers and next check conditions.
FAQ
What does the agentic-workflow-guide skill do?
Design, review, and debug agent workflows, and decide when a request should use a prompt, instruction, skill, agent, or hook before escalating to multi-agent design. Use for .agent.md / .instructions.md / .prompt.md / AGENTS.md work, workflow architecture, orchestration planning, scheduled automation model allocation, or when agent workflows may be overkill. Triggers on 'agent workflow', 'create agent', 'automation models', 'ワークフロー設計', 'orchestrator'.
How do I install agentic-workflow-guide?
Run npx skills add https://github.com/aktsmm/agent-skills --skill agentic-workflow-guide in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/agentic-workflow-guide/ (personal) or .claude/skills/agentic-workflow-guide/ (project).
Which AI agents can use agentic-workflow-guide?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is agentic-workflow-guide safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains agentic-workflow-guide?
It is published by aktsmm in aktsmm/agent-skills. It has 113 recorded installs.
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