counterpart-eight.vercel.app

{
  "name": "get_model_state",
  "kind": "answer",
  "impl": "imperative",
  "description": "Returns the current financial model: assumptions, computed monthly projections, headline metrics, and any pending proposals. Call this first, before anything else.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }
}

{
  "name": "propose_edit",
  "kind": "act",
  "impl": "imperative",
  "description": "Proposes a change to one assumption. The change is NOT applied — it appears on the page as a pending proposal that Amogh must accept or reject, and the numbers do not move until he accepts. Call get_model_state first to see valid assumption ids and current values. If Amogh's request is ambiguous about which assumption, what unit, or what time period he means (for example \"15% churn\" could be monthly or annual), you MUST call ask_human to resolve it before calling this tool — do not guess and do not state your assumption instead of asking.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "targetId": {
        "type": "string",
        "enum": [
          "startingMRR",
          "newCustomersPerMonth",
          "arpu",
          "monthlyChurnPct",
          "cac",
          "grossMarginPct",
          "monthlyOpex",
          "months"
        ],
        "description": "Which assumption to change."
      },
      "newValue": {
        "type": "number",
        "description": "The proposed new value."
      },
      "rationale": {
        "type": "string",
        "description": "One short sentence on why this change is worth making."
      },
      "agentName": {
        "type": "string",
        "description": "Which agent is proposing this, e.g. \"Growth\" or \"Risk\"."
      }
    },
    "required": [
      "targetId",
      "newValue",
      "rationale",
      "agentName"
    ],
    "additionalProperties": false
  }
}

{
  "name": "rebut_proposal",
  "kind": "act",
  "impl": "imperative",
  "description": "Adds a counterargument beneath an existing proposal without accepting, rejecting, or changing it. Call get_model_state first to find the pending proposal id and read the proposal and any existing rebuttals.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "proposalId": {
        "type": "string",
        "description": "The id of the proposal to rebut, from get_model_state."
      },
      "agentName": {
        "type": "string",
        "description": "Which agent is rebutting, e.g. \"Growth\" or \"Risk\"."
      },
      "rationale": {
        "type": "string",
        "description": "One short sentence stating the counterargument."
      }
    },
    "required": [
      "proposalId",
      "agentName",
      "rationale"
    ],
    "additionalProperties": false
  }
}

{
  "name": "ask_human",
  "kind": "act",
  "impl": "imperative",
  "description": "Asks Amogh a question and waits for his answer, returning the exact option he chose. A card appears on the page with the question and one button per option; this call does not return until he clicks one. Use this whenever his instruction is ambiguous rather than picking an interpretation yourself — units (monthly vs annual, percent vs absolute), which assumption he means, or which of several changes he wants. Asking is cheap and expected; guessing wrong wastes his time.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "question": {
        "type": "string",
        "description": "One short, specific question. Amogh reads this on the page."
      },
      "options": {
        "type": "array",
        "items": {
          "type": "string"
        },
        "minItems": 2,
        "maxItems": 6,
        "description": "Between 2 and 6 distinct answers, each short enough to fit on a button."
      }
    },
    "required": [
      "question",
      "options"
    ],
    "additionalProperties": false
  }
}

{
  "name": "run_scenario",
  "kind": "act",
  "impl": "imperative",
  "description": "Computes headline metrics (arr, ltv, ltvOverCac, runwayMonths) with temporary overrides applied on top of the current assumptions. Nothing on the page changes — this is read-only, for comparing options before calling propose_edit. Call get_model_state first to see valid assumption ids.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "overrides": {
        "type": "object",
        "description": "Assumption id -> temporary value, applied only for this calculation.",
        "additionalProperties": {
          "type": "number"
        }
      }
    },
    "required": [
      "overrides"
    ],
    "additionalProperties": false
  }
}

{
  "name": "annotate",
  "kind": "act",
  "impl": "imperative",
  "description": "Pins a short note next to one assumption row on the page, visible to Amogh. A later call for the same targetId replaces the note rather than adding another. Call get_model_state first to see valid assumption ids.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "targetId": {
        "type": "string",
        "enum": [
          "startingMRR",
          "newCustomersPerMonth",
          "arpu",
          "monthlyChurnPct",
          "cac",
          "grossMarginPct",
          "monthlyOpex",
          "months"
        ],
        "description": "Which assumption row to pin the note next to."
      },
      "text": {
        "type": "string",
        "description": "A short note, one sentence."
      }
    },
    "required": [
      "targetId",
      "text"
    ],
    "additionalProperties": false
  }
}

{
  "name": "add_chart",
  "kind": "act",
  "impl": "imperative",
  "description": "Adds a new line chart below the existing charts, plotting one or more monthly series. Does not replace or change the existing MRR chart. Call get_model_state first if unsure which series are available.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "seriesIds": {
        "type": "array",
        "items": {
          "type": "string",
          "enum": [
            "customers",
            "mrr",
            "arr",
            "grossProfit",
            "burn",
            "cumulativeCash"
          ]
        },
        "minItems": 1,
        "description": "Which monthly series to plot together on this chart."
      },
      "title": {
        "type": "string",
        "description": "Title shown above the chart."
      }
    },
    "required": [
      "seriesIds",
      "title"
    ],
    "additionalProperties": false
  }
}

{
  "name": "highlight",
  "kind": "act",
  "impl": "imperative",
  "description": "Flashes one or more assumption rows on the page for 2 seconds, to draw Amogh's attention to them — for example the row most responsible for a risky scenario. Call get_model_state first to see valid assumption ids.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "targetIds": {
        "type": "array",
        "items": {
          "type": "string",
          "enum": [
            "startingMRR",
            "newCustomersPerMonth",
            "arpu",
            "monthlyChurnPct",
            "cac",
            "grossMarginPct",
            "monthlyOpex",
            "months"
          ]
        },
        "minItems": 1,
        "description": "Which assumption rows to flash."
      }
    },
    "required": [
      "targetIds"
    ],
    "additionalProperties": false
  }
}

{
  "name": "list_scenarios",
  "kind": "answer",
  "impl": "imperative",
  "description": "Lists the saved scenario library (Current Plan and any built-in or human-saved scenarios) with their runway, ARR, LTV/CAC, and burn, and which one is currently active. Read-only — activating a scenario is a human action on the Scenarios tab. Use this to reference a scenario by name before calling run_scenario or propose_edit.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }
}

{
  "name": "generate_board_brief",
  "kind": "act",
  "impl": "imperative",
  "description": "Generates a deterministic, board-ready Markdown update (financial snapshot, key risks, recommended actions, pending/approved decisions, outlook) for a scenario. Read-only — it never changes the live model, matching run_scenario's exploration contract. Defaults to the currently active scenario; call list_scenarios first to find a specific scenarioId.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "scenarioId": {
        "type": "string",
        "description": "Which scenario to report on. Defaults to the currently active scenario."
      }
    },
    "additionalProperties": false
  }
}

{
  "name": "get_decision_log",
  "kind": "answer",
  "impl": "imperative",
  "description": "Returns the human-agent decision timeline (proposals, rebuttals, approvals, rejections, scenario activity, board briefs), most-recent-first and capped at the last 25 events. Read-only. Call this before proposing a change to check whether something similar was already decided.",
  "inputSchema": {
    "type": "object",
    "properties": {},
    "additionalProperties": false
  }
}