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Openplan align

Skill BANANASJIM/openplan-skill/skills/openplan-align

Portable OpenPlan-style Agent Skills for Codex and Claude Code: intent alignment, docs governance, review, handoff, and safe auto workflows.

Install
npx -y skills add BANANASJIM/openplan-skill --skill openplan-align

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Clarify and structure ambiguous OpenPlan-style requests before research, design, implementation, or review. Use with OpenPlan philosophy when a user request is underspecified, strategically risky, solution-first, missing success criteria, or needs blind-spot analysis, advisor-style questions, route selection, or a needs-snapshot-style summary. This skill does not implement or review changes directly.

SKILL.md

2.3 KB, as published. Nobody here has run it

OpenPlan Align

Use this after $openplan-core when the next safe action depends on understanding the goal/intent.

Alignment Flow

  1. Restate the user's request in one paragraph.
  2. Separate facts from assumptions.
  3. Walk the 7-layer funnel only as far as needed.
  4. Identify blind spots and human decisions.
  5. Recommend the next route: ask via the human-facing coordinator, research, design, implement, review, or stop.

7-Layer Funnel

LayerQuestionEnough When
L1 WHYWhy does this need to exist?Job-to-be-done is explicit
L2 WHO/WHEREWho uses it and in what constraints?Context and stakeholders are clear
L3 WHATWhat is in and out of scope?Boundaries are explicit
L4 HOW macroWhat modules or artifacts are involved?Interfaces and ownership are named
L5 RISKWhat might fail or be unknown?Risks have a research or mitigation path
L6 VERIFYHow will success be checked?Testable criteria exist
L7 DETAILWhat exact implementation detail matters?Work is actionable

Do not force all seven layers for a small request. Use the smallest depth that prevents a wrong next action.

Output

For lightweight alignment:

Goal/Intent:
Known facts:
Assumptions:
Blind spots:
Human decisions:
Recommended next route:

For formal alignment, use references/alignment-contract.md.

Rules

  • When the user gives a solution, identify what problem it solves unless already clear.
  • Ask at most 1-3 questions only if this agent is the human-facing coordinator; otherwise list Human decisions required.
  • Do not make the human's tradeoff decision.
  • If enough is clear, proceed with a stated assumption instead of blocking.
  • If evidence is missing, recommend research rather than inventing facts.

For Claude Code, use assets/claude-code-command.md as a slash command or prompt seed.

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