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Automation
Skill

/decompose-and-or-goal

Recursively decompose a goal into an AND/OR DAG whose leaves are executable or testable subgoals.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill decompose-and-or-goal --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/decompose-and-or-goal

Context preview

The summary Claude sees to decide when to auto-load this skill.

Recursively decompose a goal into an AND/OR DAG whose leaves are executable or testable subgoals.

SKILL.md

decompose-and-or-goal.SKILL.md
name: decompose-and-or-goal
description: "Recursively decompose a goal into an AND/OR DAG whose leaves are executable or testable subgoals."

decompose-and-or-goal

Purpose

Recursively decompose a goal into an AND/OR DAG whose leaves are executable or testable subgoals.

Input contract

required: [top_goal, constraints]
optional: [actor_profile, obstacle_report, existing_subgoals]
constraints: [branch semantics, dependencies, and leaf criteria must be explicit]

Procedure

1. Split the goal into necessary AND conditions and alternative OR paths. 2. Recurse until each leaf has an observable result or executable action. 3. Attach actors, dependencies, constraints, and unresolved feasibility to each branch. 4. Preserve shared subgoals as DAG nodes rather than duplicating them.

If the AND/OR decomposition is complete enough to test necessity and coverage, consider `validate-goal-tree` as the next tactic.

Output contract

produces: [goal_dag, branch_semantics, executable_leaves, dependency_edges, feasibility_questions]
delta_fields: [findings, hypothesis_updates, uncertainties, open_questions]

Quality gates

  • Every leaf traces to the top goal.
  • AND/OR labels and dependency directions are unambiguous.
  • Cycles and duplicate shared nodes are flagged.

Failure and counterexamples

Do not split prose into labels without changing testability, and do not treat alternatives as simultaneous requirements.

Provenance map

  • `resolved: north-star-crystallization-and-or-decompose`
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Ships withde-anthropocentric-research-engine

The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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