conflict-resolver

conflict-resolver is a skill for Claude Code, Codex from khalilbenaz/claude-skills-collection. It costs 99 tokens per session (3,286 once invoked), scanned A, original, MIT.

A guide for resolving disagreements between two or more AI agents whose answers conflict. It covers finding the contradiction, deciding which result is better supported, combining compatible work, and feeding the result back into the process.

In plain words
What is it for?
Handling conflicting answers, calculations, recommendations, classifications, or verification results in multi-agent workflows.
Why use it?
It prevents contradictory agent outputs from being accepted without review. It gives different kinds of conflicts a defined way to be assessed and resolved.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Handling conflicting answers, calculations, recommendations, classifications, or verification results in multi-agent workflows.

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Install with agentmods
npx agentmods add skills/khalilbenaz/claude-skills-collection/conflict-resolver
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add khalilbenaz/claude-skills-collection --skill conflict-resolver
Clone the repo
git clone --depth 1 https://github.com/khalilbenaz/claude-skills-collection

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for conflict-resolver

README.md
[![agentmods](https://agentmods.dev/badge/skills/khalilbenaz/claude-skills-collection/conflict-resolver/github.svg)](https://agentmods.dev/skills/khalilbenaz/claude-skills-collection/conflict-resolver)
Your own site
<a href="https://agentmods.dev/skills/khalilbenaz/claude-skills-collection/conflict-resolver"><img src="https://agentmods.dev/badge/skills/khalilbenaz/claude-skills-collection/conflict-resolver/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for conflict-resolver

Your own site · 80×15
<a href="https://agentmods.dev/skills/khalilbenaz/claude-skills-collection/conflict-resolver"><img src="https://agentmods.dev/badge/skills/khalilbenaz/claude-skills-collection/conflict-resolver.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 99 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,286 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00099 $0.03286
Opus 5 $0.00049 $0.01643
Sonnet 5 $0.00020 $0.00657
Haiku 4.5 $0.00010 $0.00329

Measured 11d ago against content hash 688a5e47d43b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

conflict-resolver scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agent-skills/conflict-resolver/SKILL.md · 305 lines

How it starts

The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Conflict Resolver

Quand utiliser ce skill

Utilise ce skill quand deux agents ou plus ont produit des résultats contradictoires, incompatibles ou mutuellement exclusifs sur la même question ou tâche. Typiquement : pipelines parallèles, validation croisée, ou agent de vérification qui contredit l'agent de production.

Conditions de déclenchement concrètes :

  • Agent A retourne True, agent B retourne False sur le même prédicat
  • Deux agents calculent des montants différents pour la même transaction
  • Deux agents recommandent des actions incompatibles (ex. : "accepter" vs "rejeter")
  • Un agent de vérification invalide le résultat d'un agent de génération
  • N agents en majorité vs minorité sur une classification

Workflow en 10 étapes

1. Détecter le conflit

Implémente une couche de comparaison après chaque gather parallèle. Classe chaque conflit par type et sévérité avant toute action.

Type Exemple Sévérité par défaut
direct_contradiction True vs False critical
numerical_inconsistency 1500€ vs 2300€ (>10%) major
logical_conflict Deux conclusions mutuellement exclusives major
priority_conflict Action X incompatible avec action Y minor → critical selon domaine
from dataclasses import dataclass
from typing import Any

@dataclass
class ConflictDetectionResult:
    has_conflict: bool
    conflict_type: str   # "direct_contradiction" | "numerical_inconsistency" | "logical_conflict" | "priority_conflict"
    severity: str        # "critical" | "major" | "minor"
    agent_a: str
    agent_b: str
    output_a: Any
    output_b: Any
    description: str

def detect_conflict(output_a: Any, agent_a: str, output_b: Any, agent_b: str) -> ConflictDetectionResult:
    # Détection numérique
    if isinstance(output_a, (int, float)) and isinstance(output_b, (int, float)):
        diff_pct = abs(output_a - output_b) / max(abs(output_a), abs(output_b), 1)
        if diff_pct > 0.10:
            return ConflictDetectionResult(
                has_conflict=True, conflict_type="numerical_inconsistency",
                severity="major" if diff_pct > 0.30 else "minor",
                agent_a=agent_a, agent_b=agent_b,
                output_a=output_a, output_b=output_b,
                description=f"Écart de {diff_pct:.1%} entre {agent_a} et {agent_b}"
            )
    # Détection booléenne
    if isinstance(output_a, bool) and isinstance(output_b, bool) and output_a != output_b:
        return ConflictDetectionResult(
            has_conflict=True, conflict_type="direct_contradiction", severity="critical",
            agent_a=agent_a, agent_b=agent_b, output_a=output_a, output_b=output_b,
            description=f"{agent_a} dit {output_a}, {agent_b} dit {output_b}"
        )
    return ConflictDetectionResult(
        has_conflict=False, conflict_type="none", severity="none",
        agent_a=agent_a, agent_b=agent_b, output_a=output_a, output_b=output_b, description=""
    )

Read the full file on GitHub · 305 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 305 lines · 99 tokens per session scan A 688a5e47d43b

Subscribe to this mod's changes

conflict-resolver is a skill published in the GitHub repository khalilbenaz/claude-skills-collection (22 stars, last pushed 17d ago), licensed MIT. It adds 99 tokens to every session and 3,286 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.