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Automation
Skill

/define-objective

Formalize objectives, constraints, and tradeoff preferences for optimization.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill define-objective --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/define-objective

Context preview

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

Formalize objectives, constraints, and tradeoff preferences for optimization.

SKILL.md

define-objective.SKILL.md
name: define-objective
description: "Formalize objectives, constraints, and tradeoff preferences for optimization."

define-objective

Purpose

Formalize objectives, constraints, and tradeoff preferences before an optimization or selection decision.

Input contract

required: [decision_context, candidate_set, stakeholder_preferences]
optional: [hard_constraints, utility_scale, priority_weights]
constraints: [objectives are measurable or operationalized; tradeoffs and constraint direction are explicit]

Procedure

1. Elicit the desired outcome, affected scope, stakeholders, and time horizon. 2. Separate objectives from constraints and preferences, then define each objective's direction and measurement. 3. Record conflicts, permissible tradeoffs, and any weights or lexicographic priorities with their rationale. 4. Emit an objective schema suitable for comparison, optimization, and later audit.

Output contract

produces: [objective_schema, constraint_schema, tradeoff_policy, unresolved_preferences]
delta_fields: [findings, assumption_updates, uncertainties, decisions, open_questions]

Quality gates

  • A-class gate: declared universe = all stakeholder objectives and hard constraints in scope; numerator = items operationalized with direction, measurement, and source; batch increment = one objective or constraint formalized; stopping reason = all items formalized or unresolved conflicts are explicit; source references = stakeholder, requirement, and decision IDs; direction/threshold reason = an objective enters optimization only when its direction and acceptable tradeoff boundary are explicit.
  • At least two distinct objectives and one constraint are required unless the decision record justifies a narrower scope.

Failure and counterexamples

Do not encode a preferred solution as an objective. If two stakeholders use the same word for different outcomes, preserve separate definitions.

Provenance map

  • resolved: objective-definition
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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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