菜单
Structured checkpoint format for requesting human input. When an agent needs a decision, it must stop, present context, show options, and wait. Activate when delegating to subagents, running background tasks, or hitting any decision point that requires human judgment.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/majiayu000/claude-skill-registry --skill user-input-protocol命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | user-input-protocol |
| description | Structured checkpoint format for requesting human input. When an agent needs a decision, it must stop, present context, show options, and wait. Activate when delegating to subagents, running background tasks, or hitting any decision point that requires human judgment. |
| license | CC0-1.0 |
| metadata | {"author":"jwilger","version":"1.0","requires":[],"context":[],"phase":"build","standalone":true} |
Value: Respect -- the developer's judgment governs all consequential decisions. The agent never assumes when it should ask.
Defines a structured format for agents to request human input at decision points. Prevents agents from making assumptions on the developer's behalf, ensures questions include enough context for informed decisions, and provides a pause-and-resume pattern for subagents that cannot directly prompt the user.
When you encounter a decision that requires human judgment, stop working immediately. Do not guess. Do not pick the "most likely" option. Present the decision clearly and wait.
Decisions that require human input:
Decisions that do NOT require human input:
When you need input, output this structured checkpoint:
AWAITING_USER_INPUT
---
Context: [Why you are asking -- what you were doing and what you found]
Decision needed: [The specific question, one sentence]
Options:
A) [Label] -- [What this means and its implications]
B) [Label] -- [What this means and its implications]
C) [Label] -- [What this means and its implications]
Recommendation: [Which option you suggest and why, or "No recommendation"]
---
Rules for the checkpoint:
Example:
AWAITING_USER_INPUT
---
Context: While implementing the login endpoint, I found two email validation
patterns in the codebase. auth/validate.rs uses strict RFC 5322 parsing.
signup/forms.rs uses a simple regex check. These produce different results
for edge cases like "user+tag@example.com".
Decision needed: Which email validation approach should be the project standard?
Options:
A) Strict RFC 5322 -- rejects fewer valid addresses, more complex to maintain
B) Simple regex -- faster, but may accept malformed addresses
C) Context-dependent -- strict for auth, lenient for forms
Recommendation: A) Strict RFC 5322, applied everywhere for consistency
---
Subagents and background tasks typically cannot prompt the user directly. When a subagent needs input, it must save its progress before pausing so work can resume without starting over.
State to save before pausing:
Where to save state depends on your harness:
After saving state, output the AWAITING_USER_INPUT checkpoint and stop. The orchestrator or main conversation detects the pause, presents the question to the user, and resumes the subagent with the answer.
When resumed with the user's answer:
Do not re-analyze files you already analyzed. Do not re-read context you already saved. The purpose of state preservation is to make resumption instant.
Do:
Do not:
When multiple related decisions are needed, group them in one checkpoint rather than pausing repeatedly. Number each question.
AWAITING_USER_INPUT
---
Context: Setting up the test infrastructure for the new auth module.
Decisions needed:
1. Test framework?
A) Jest -- already used in 3 other modules
B) Vitest -- faster, but would introduce a second test runner
Recommendation: A) Jest for consistency
2. Test file location?
A) Colocated (auth/__tests__/) -- matches signup module pattern
B) Top-level (tests/auth/) -- matches API module pattern
Recommendation: A) Colocated, to match the newer module convention
---
This skill is advisory. It instructs agents to pause at decision points and use structured checkpoints. On harnesses with plugin support, enforcement hooks can detect when an agent makes assumptions without pausing. On harnesses without enforcement, the agent follows these practices by convention. If you observe the agent making decisions it should have asked about, point it out. For available enforcement plugins, see the Harness Plugin Availability table.
After applying this skill, verify:
This skill works standalone. For enhanced workflows, it integrates with:
Missing a dependency? Install with:
npx skills add jwilger/agent-skills --skill orchestration