← Claus Argos Skill OSCONTENT HISTORY

Update to Claus Argos Skill OS

Snapshot Sep 30, 2026 · 23:14 UTC · version 1.16.0

Collection source: not recorded for this historical snapshot.

WHAT CHANGED · RULE-BASED ANALYSIS

First saved snapshot

No earlier snapshot is available to establish a change.

Compare saved observations

Download comparison JSON
Full technical diff · 0 changed fields
Full snapshot data
{
  "name": "optimize-pricing",
  "description": "Design and improve pricing architecture using customer value, willingness to pay, segmentation, packaging, metrics, costs, competition, anchors, discounts, subscriptions, experiments, and guardrails. Use for setting prices, packaging tiers, price increases, monetization, usage-based pricing, or discount strategy.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 214
    }
  ],
  "skill_md_contents": "---\nname: optimize-pricing\ndescription: Design and improve pricing architecture using customer value, willingness to pay, segmentation, packaging, metrics, costs, competition, anchors, discounts, subscriptions, experiments, and guardrails. Use for setting prices, packaging tiers, price increases, monetization, usage-based pricing, or discount strategy.\n---\n# Optimize Pricing\n1. Define customer segments, value created, purchase context, alternatives, costs, capacity, objectives, and constraints.\n2. Research current competitor prices carefully, normalizing currency, tax, billing period, limits, and service level.\n3. Choose value metric, fences, tiers, packaging, anchors, minimums, overages, discounts, and migration policy.\n4. Model revenue, margin, adoption, churn, fairness, complexity, and edge cases across scenarios.\n5. Design research or experiments with guardrail metrics and customer communication.\n6. Return pricing thesis, package table, economics, comparison, experiment, rollout, objection handling, and review triggers.\n"
}

SHA-256: 9676c05492aa045bee1b95be787fe73cbda047ecb1dbae0d6b6949dfbda77932