Skip to content
Automation
Skill

/detect-contradiction

Detect an explicit contradiction in logical derivations, claims, or evidence relations; classify whether it is formal, empirical, scope-dependent, or unresolved.

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

Context preview

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

Detect an explicit contradiction in logical derivations, claims, or evidence relations; classify whether it is formal, empirical, scope-dependent, or unresolved.

SKILL.md

detect-contradiction.SKILL.md
name: detect-contradiction
description: "Detect an explicit contradiction in logical derivations, claims, or evidence relations; classify whether it is formal, empirical, scope-dependent, or unresolved."

detect-contradiction

Purpose

Detect and classify explicit contradictions in derivations, claims, or evidence relations.

Input contract

required: [claims_or_derivation, evidence_relations, scope_context]
optional: [logic_rules, causal_graph, contradiction_taxonomy]
constraints: [distinguish formal, empirical, scope-dependent, and unresolved contradiction; preserve both sides]

Procedure

1. Normalize claims, predicates, scope, and evidence polarity. 2. Compare opposing claims or support/contradict relations under shared scope. 3. Classify the conflict and record the exact conflicting statements. 4. Create a contradiction record and identify the evidence needed for adjudication.

If the contradiction concerns treatment, component, or effect attribution, consider `analyze-intervention` as the next tactic. If the contradiction rests on a shared but untested premise, consider `challenge-assumption` as the next tactic.

Output contract

produces: [contradiction_register, conflicting_relations, classification, adjudication_questions]
delta_fields: [findings, evidence_updates, uncertainties, open_questions]

Quality gates

  • Support and contradict evidence are both recorded; contradiction cannot be hidden by selecting one polarity.
  • Scope mismatch is labeled scope-dependent rather than formal contradiction.
  • Each contradiction includes both endpoints and a reproducible comparison basis.

Parameterization

The caller must provide claim schema, evidence polarity vocabulary, scope rules, logic/causal relation types, and the adjudication status vocabulary.

Failure and counterexamples

Reject conflicts caused only by incomparable metrics, different scopes, or duplicate text; retain them as unresolved comparability issues.

Provenance map

  • resolved: stress-test/contradiction-detection
  • resolved: knowledge-structuring/contradiction-flagging
  • concept: stress-test/detect-contradiction
  • intermediate: Pass3/detect-contradiction
  • intermediate: Pass3/flag-contradictory-evidence

Preserved source criteria ledger

| source | physical line | kind | source criterion | |---|---:|---|---| | knowledge-structuring/contradiction-flagging | 18 | gate | Record simultaneous support and contradict evidence and do not ignore either. |

Read more
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.

Get the whole plugin