Update to MUSITU Axiom

{
  "description": "Perform quantitative M&A, partnership, vendor, and investment due diligence using MUSITU Axiom.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 249
    },
    {
      "relative_path": "references/COMMERCIAL.md",
      "size_in_bytes": 751
    },
    {
      "relative_path": "references/PROOF.md",
      "size_in_bytes": 537
    },
    {
      "relative_path": "references/QUALITY.md",
      "size_in_bytes": 2262
    },
    {
      "relative_path": "references/ROUTING.md",
      "size_in_bytes": 504
    },
    {
      "relative_path": "scripts/proof_envelope.py",
      "size_in_bytes": 1023
    },
    {
      "relative_path": "scripts/scenario_grid.py",
      "size_in_bytes": 691
    }
  ],
  "name": "musitu-ma-diligence",
  "skill_md_contents": "---\nname: musitu-ma-diligence\ndescription: \"Perform quantitative M&A, partnership, vendor, and investment due diligence using MUSITU Axiom.\"\n---\n# MUSITU M&A Due Diligence\nRead `references/QUALITY.md` and `references/PROOF.md` for material deal conclusions.\n\n## Workflow\n1. Separate management/seller claims, observed evidence and buyer assumptions.\n2. Normalize financial and operating baseline.\n3. Quantify concentration and quality issues.\n4. Model purchase economics and requested valuation metrics.\n5. Treat synergies probabilistically with timing and cost.\n6. Run downside scenarios.\n7. Rank diligence gaps by value at risk, probability and reversibility.\n8. Return decision triggers and unresolved questions.\n\nDo not present legal conclusions as legal advice.\n"
}