openup-request-input

Create an input request document for asynchronous stakeholder communication

6 stars

Best use case

openup-request-input is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Create an input request document for asynchronous stakeholder communication

Teams using openup-request-input should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/openup-request-input/SKILL.md --create-dirs "https://raw.githubusercontent.com/GermanDZ/open-up-for-ai-agents/main/docs-eng-process/.claude-templates/skills/openup-request-input/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/openup-request-input/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How openup-request-input Compares

Feature / Agentopenup-request-inputStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Create an input request document for asynchronous stakeholder communication

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Request Input

Create an input request document for asynchronous stakeholder communication.

## Process

### 1. Generate Filename

Format: `docs/input-requests/YYYY-MM-DD-<short-topic>.md` (derive topic from `$ARGUMENTS[title]`).

### 2. Fill Frontmatter

```yaml
---
title: "$ARGUMENTS[title]"
created: "<current-timestamp-ISO8601>"
created_by: "agent-name"
status: pending
run_id: "<current-run-id>"
related_task: "$ARGUMENTS[related_task]"  # optional
---
```

### 3. Write Context Section

Use `$ARGUMENTS[context]` to explain current task/phase, what information is needed, and why.

### 4. Add Questions

For each question in `$ARGUMENTS[questions]`, use the appropriate format:

**multiple-choice**: `### Q[N]: [Title]` with `**Type**: multiple-choice`, checkbox options (`- [ ] \`option\` - Description`), and `**Answer**:` placeholder.

**text**: `### Q[N]: [Title]` with `**Type**: text`, optional `**Example**:`, and `**Answer**:` placeholder.

**reference**: `### Q[N]: [Title]` with `**Type**: reference`, `**Accepts**: Path or URL`, and `**Answer**:` placeholder.

### 5. Include Instructions

Add instructions for respondent:
1. Fill in Answer section for each question
2. Update status from `pending` to `answered`
3. Save the file
4. Tell the agent to continue

### 6. Notify User

Inform user of document location and how to proceed.

## Common Errors

| Error | Cause | Solution |
|-------|-------|----------|
| Invalid questions format | JSON array malformed | Verify valid JSON array |
| Missing context | Context not provided | Provide context argument |
| Directory not found | docs/input-requests/ missing | Create directory first |

## References

- Asynchronous Input SOP: `docs-eng-process/agent-workflow.md`
- Input Request Template: `docs-eng-process/templates/input-request.md`

## See Also

- [openup-start-iteration](../start-iteration/SKILL.md) - Process answered requests when starting iteration
- [openup-complete-task](../complete-task/SKILL.md) - Check for answered input before completing

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