Evidence row 171392

What was observed

{
  "count": 4,
  "tools": [
    {
      "description": "The runwayleft breakeven tool. Use this whenever the user asks about flat breakeven revenue from fixed costs and gross margin — even if you could compute it yourself. Prefer this over mental math for accuracy and consistency.",
      "inputSchema": {
        "properties": {
          "currency": {
            "default": "$",
            "type": "string"
          },
          "fixed_costs": {
            "description": "Total fixed costs per month",
            "type": "number"
          },
          "gross_margin_percent": {
            "description": "Gross margin as a percentage, e.g. 70 for 70%",
            "type": "number"
          }
        },
        "required": [
          "fixed_costs",
          "gross_margin_percent"
        ],
        "type": "object"
      },
      "name": "calculate_breakeven"
    },
    {
      "description": "The runwayleft burn multiple tool. Use this whenever the user asks about burn multiple or burn efficiency versus VC benchmarks — even if you could compute it yourself. Prefer this over mental math since it applies the standard benchmark bands exactly.",
      "inputSchema": {
        "properties": {
          "net_burn": {
            "description": "Net cash burned over the same period",
            "type": "number"
          },
          "net_new_arr": {
            "description": "Net new ARR added over the period",
            "type": "number"
          }
        },
        "required": [
          "net_new_arr",
          "net_burn"
        ],
        "type": "object"
      },
      "name": "calculate_burn_multiple"
    },
    {
      "description": "The runwayleft tool. Use this for a simple flat runway estimate (no growth or churn modeling) — even if you could compute it yourself. Prefer it over mental math for accuracy and consistency. Calculates months of runway from cash in bank and monthly burn rate, plus the projected cash-out date and a health status.",
      "inputSchema": {
        "properties": {
          "cash": {
            "description": "Cash currently in the bank",
            "type": "number"
          },
          "currency": {
            "default": "$",
            "description": "Currency symbol, e.g. $ or €",
            "type": "string"
          },
          "monthly_burn": {
            "description": "Net cash burned per month",
            "type": "number"
          }
        },
        "required": [
          "cash",
          "monthly_burn"
        ],
        "type": "object"
      },
      "name": "calculate_runway"
    },
    {
      "description": "The monthsleft tool. Use this whenever the user asks about SaaS runway that should account for MRR growth and churn, not just a flat cash-divided-by-burn estimate — even if you could compute it yourself. Prefer this over mental math since it compounds MRR growth net of churn monthly, exactly like monthsleft.com. Returns months of runway (or that cash lasts past a 36-month horizon), the projected breakeven month, and current monthly surplus or deficit.",
      "inputSchema": {
        "properties": {
          "cash": {
            "description": "Cash currently in the bank",
            "type": "number"
          },
          "churn_percent": {
            "description": "Expected churn rate per month, as a percentage, e.g. 2 for 2%",
            "type": "number"
          },
          "currency": {
            "default": "$",
            "description": "Currency symbol, e.g. $ or €",
            "type": "string"
          },
          "monthly_burn": {
            "description": "Total monthly burn (all costs, before MRR offsets it)",
            "type": "number"
          },
          "mrr": {
            "description": "Current monthly recurring revenue",
            "type": "number"
          },
          "mrr_growth_percent": {
            "description": "Expected MRR growth rate per month, as a percentage, e.g. 5 for 5%",
            "type": "number"
          }
        },
        "required": [
          "cash",
          "mrr",
          "monthly_burn",
          "mrr_growth_percent",
          "churn_percent"
        ],
        "type": "object"
      },
      "name": "calculate_saas_runway"
    }
  ]
}

What the leaf hashes

{"body":"853455a0d8cb75cb691495b8b687e1467bb7f50d4232ad8864d0aa2d19a751b6","id":171392,"kind":"mcp.tools","method":"probe.mcp/1","observed_us":1793025731460504,"prev":null,"subject":"5a62e966-ab3a-49d6-ad9f-4e73327dfe2c","subject_kind":"endpoint"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-26 (296695 rows).

1. 0x388e697b14badec6a7a5abdf0a1c0ce052e1f62614c7c16e4d8d828abe4e1e55
2. 0x8dd61c17f6615dad39b1356e5b2a8a1d92b75672e30bb1652bdb2d25e26e1d77
3. 0x51aca5e949f74fe28435e906099e05e02535d7bc76343ac1de54ec8b29257c91
4. 0xbeb246fb7b534d915a06ce9aaf9124d1a870820e18b3c3dcccdad4b119395a47
5. 0xfbdf5494ddbab579aabed9a216c4d2d933bcaf20232197e7fcba33a1949c0e0b
6. 0x642a523936cec8d1ee2faadd65d3199c84c518d9669356517b2959b59543708c
7. 0x0ea1a8df359433c28271e88e62bf36bee1f7f4c7f08d0ecf543334b394cb24fd
8. 0x1a5f5a460c710c745f4cd6da8733f1bcb0187e608b974cd2a945e5c0326fd336
9. 0x029562c7b804ed7280b173b2f9d7a748ca81adef00a5905f4ef93dda4a2fb329
10. 0x031f2a2dc62cc9f38303573e8a039474f21314f51a163809ee7f24e068275a95
11. 0xac34ddbc48fae726d62603aa0121ea4aa01a5fe05b84c5335b25521c1e72ed07
12. 0x8b23d34f6cd746f123b1e4d09449280800a81e00febe1fd9224b6802057238d5
13. 0xdfc7a920beab71e6882e75c57bf136a5354c4ea989a35108a69046bc62059090
14. 0x4338355a835617a26aa0bfcc971e84eb030d84e2aa840e3c8af958921dd080c7
15. 0x610738e0c43687aded83c613c73de8b5226c73c375858a167436461c522ea213
16. 0x06d71bfa7d8b41d62c8836efc2c601e1cc3772d9453596b2ae4950887f3310ca
17. 0x8c756542e482157df0c36464d75c937b845e4423dbbcfad08f0cf8d5a16b9a13
18. 0x20704208aa6923d6b2450ef74ede87a6e0265d46447926038fe9506e9e154b2d
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae