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/adjust-abstraction-scope

Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system boundary) until the representation has useful explanatory and experimental leverage.

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de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill adjust-abstraction-scope --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/adjust-abstraction-scope

Context preview

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

Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system boundary) until the representation has useful explanatory and experimental leverage.

SKILL.md

adjust-abstraction-scope.SKILL.md
name: adjust-abstraction-scope
description: "Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system boundary) until the representation has useful explanatory and experimental leverage."

adjust-abstraction-scope

Purpose

Move a scientific object up or down in abstraction, or narrow/broaden scope dimensions, until explanatory and experimental leverage improve.

Input contract

required: [research_object, current_scope, leverage_failure]
optional: [candidate_levels, context_constraints, target_use]
constraints: [retain object identity; change representation or declared scope explicitly]

Procedure

1. Record object, current level, and scope dimensions (population, mechanism, context, outcome, timeframe, boundary). 2. Generate at least one upward and one downward abstraction candidate when leverage is unclear. 3. For each candidate, state what is gained, lost, and newly testable. 4. Select the narrowest or broadest level that supports the caller's stated use and record rationale.

Output contract

produces: [scoped_representations, selected_scope, leverage_rationale]
delta_fields: [findings, decisions, uncertainties]

Quality gates

  • Object identity is invariant across representations.
  • Every changed dimension is named with before/after values.
  • Selected scope has an explicit explanatory or experimental leverage claim.

Parameterization

Caller supplies object schema, allowed abstraction dimensions, admissible scope bounds, target use, and selection rule.

Failure and counterexamples

Reject a level that changes the object while appearing to change only scope; reject scope changes with no stated leverage test.

Provenance map

  • resolved: abstraction-laddering
  • resolved: scope-assessment
  • resolved: question-reformulation
  • resolved: scope-calibration
  • intermediate: Pass8/shift-abstraction-level
  • intermediate: Pass8/adjust-question-scope

Preserved source criteria ledger

| source | criterion | |---|---| | scope-assessment | Input must contain at least 1 fully stated research question. | | scope-assessment | Too broad requires a book/multiple papers; appropriate is answerable by one paper; too narrow is self-evident or lacks contribution. |

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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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Python
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Apache-2.0
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53m ago
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7mo ago
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Repo: yogsoth-ai/de-anthropocentric-research-engine