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Automation
Skill

/calibrate-adversarial-confidence

Track confidence in competing claims/roles across adversarial rounds and update confidence only when evidence or argument quality warrants it.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill calibrate-adversarial-confidence --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/calibrate-adversarial-confidence

Context preview

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

Track confidence in competing claims/roles across adversarial rounds and update confidence only when evidence or argument quality warrants it.

SKILL.md

calibrate-adversarial-confidence.SKILL.md
name: calibrate-adversarial-confidence
description: "Track confidence in competing claims/roles across adversarial rounds and update confidence only when evidence or argument quality warrants it."

calibrate-adversarial-confidence

Purpose

Track confidence in competing claims or roles across adversarial rounds and update only when evidence or argument quality warrants it.

Input contract

required: [round_records, competing_claims, update_rule]
optional: [prior_confidence, calibration_history]
constraints: [every update cites evidence or argument-quality change]

Procedure

1. Record each round's claims, arguments, and evidence. 2. Apply the declared update rule and preserve dissent. 3. Mark escalation, continuation, termination, or saturation with rationale.

Output contract

produces: [confidence_trace, update_rationale, round_status, unresolved_dissent]
delta_fields: [findings, evidence_updates, uncertainties, decisions]

Quality gates

  • A-class calibration: declared universe = all completed debate rounds; numerator = rounds with evidence-linked updates; batch increment = one round; stopping reason = confidence stabilizes or unresolved dissent is explicit; source references = round/evidence IDs; direction/threshold reason = update only toward claims supported by new evidence or stronger argument.

Failure and counterexamples

Do not update confidence for rhetoric, repetition, or role status alone.

Provenance map

  • resolved: adversarial-escalation
  • concept: confidence-escalation [sop]
  • resolved: confidence-calibration
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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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4h ago
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7mo ago
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Repo: yogsoth-ai/de-anthropocentric-research-engine