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Understanding Feature Requests

skill-etr-groundwork-understanding-feature-requests · by etr

This skill should be used when clarifying feature requests, gathering requirements, or checking for contradictions in proposed changes

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Install

$ agentstack add skill-etr-groundwork-understanding-feature-requests

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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1mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming — see below.

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About

Understanding Feature Requests

Interactive workflow for clarifying feature requests and ensuring they don't conflict with existing requirements.

Pre-flight: Model Recommendation

Your current effort level is {{effort_level}}.

Skip this step silently if effort is high, xhigh, or max (the scale is low < medium < high < xhigh < max, so xhigh and max are already above high) AND you are Sonnet or Opus. If effort is low or medium (i.e. below high), you MUST show the recommendation prompt — regardless of model. If you are not Sonnet or Opus, you MUST show the recommendation prompt - regardless of effort level.

Otherwise → use AskUserQuestion:

{
  "questions": [{
    "question": "Do you want to switch? Contradiction detection in feature requirements benefits from consistent reasoning.\n\nTo switch: cancel, run `/effort high` (and `/model sonnet` if on Haiku), then re-invoke this skill.",
    "header": "Recommended: Sonnet or Opus at high effort",
    "options": [
      { "label": "Continue" },
      { "label": "Cancel — I'll switch first" }
    ],
    "multiSelect": false
  }]
}

If the user selects "Cancel — I'll switch first": output the switching commands above and stop. Do not proceed with the skill.

Step 1: Clarify the Request

When the user proposes a feature or change, ask clarifying questions to understand:

Core Questions (always ask):

  • What problem does this solve for the user?
  • Who is the target user/persona?
  • What is the expected outcome or behavior?

Exploratory Questions (for open-ended or vague requests):

  • "What inspired this feature idea?"
  • "Have you seen this done well elsewhere? What did you like about it?"
  • "What would make this feature 'delightful' vs just 'adequate'?"
  • "What's the simplest version that would provide value?"
  • "If you had to cut half the scope, what would you keep?"

Conditional Questions (ask as relevant):

  • What triggers this behavior? (for event-driven features)
  • What are the edge cases or error conditions?
  • What is explicitly out of scope?
  • Are there dependencies on other features?
  • What metrics would indicate success?
  • How could this fail? What are the possible risks and dangers?
  • Could we do this in any other way?

Keep questions focused - ask 2-3 at a time, not all at once. Build understanding iteratively.

Question Style:

  • Prefer multiple-choice questions when possible - they're easier to answer and keep conversations focused
  • Explore one topic at a time to avoid overwhelming stakeholders
  • When presenting alternatives, lead with your recommendation

Step 2: Check for Internal Contradictions

Before proceeding with design, review for conflicts within the proposed feature:

  • Conflicting behaviors (e.g., "shall be real-time" AND "shall work offline-first")
  • Incompatible constraints (e.g., "shall complete in <100ms" AND "shall process 10,000 items")
  • Mutually exclusive states

If conflicts found, surface them and resolve before proceeding.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.