buildvsbuy-ai.vercel.app WebMCP Tools, Schemas & Agent Capabilities

buildvsbuy-ai.vercel.app

live Unverified (seed import) Productivity & Business 9 tools imperative implementation

BuildVsBuy.ai — a WebMCP decision canvas. Humans and browser-integrated agents co-manipulate one structured build-vs-buy model (Auth or AI Web Scraping) via typed tools, not DOM scraping.

First seen 2026-11-05 · Last seen 2026-11-05 · Source: webmcp.com

Answer 1 · Act 8 · Transact 0 · Score: Not yet scored

Tool inspector

add_option

act imperative

Add a candidate option (Build, Buy, Adopt/open_source, or Hybrid). Use only on a custom (blank) decision — not after auth/scraping presets already seeded 4 options (those calls are REFUSED). All numeric metrics are required. Set estimate=true when inventing numbers for custom dilemmas — the UI will badge them until the human confirms. Marks ranking stale; call rerank_decision_options after adding options. For vibe-coding / speed on a seeded demo: set_priority_weight(time_to_prototype, 9 or 10) then rerank — do not invent cards.

Input schema

Property	Type	Required	Description
`id`	string	yes	Stable option id (e.g. build, buy, adopt, hybrid).
`name`	string	yes	Human-readable option label.
`type`	string	yes	build \| buy \| open_source (Adopt) \| hybrid.
`prototype_time_hours`	number	yes	Hours to functional v1 (TTP).
`monthly_cash_cost`	number	yes	Recurring cash per month (USD).
`monthly_maintenance_hours`	number	yes	Expected monthly engineering hours (MDO).
`customization_score`	number	yes	CTL 1–10, higher = more control.
`security_risk_score`	number	yes	SCR 1–10, higher = more risk.
`learning_value_score`	number	yes	LSM 1–10, higher = more moat value.
`vendor_lockin_score`	number	yes	VLR 1–10, higher = more lock-in.
`estimate`	boolean	no	True if metrics are agent-invented until human confirms.
`sources`	array	no	Short assumption/source lines shown on the option card (optional).

Raw JSON schema

{
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Stable option id (e.g. build, buy, adopt, hybrid)."
    },
    "name": {
      "type": "string",
      "description": "Human-readable option label."
    },
    "type": {
      "type": "string",
      "enum": [
        "build",
        "buy",
        "open_source",
        "hybrid"
      ],
      "description": "build | buy | open_source (Adopt) | hybrid."
    },
    "prototype_time_hours": {
      "type": "number",
      "minimum": 0,
      "description": "Hours to functional v1 (TTP)."
    },
    "monthly_cash_cost": {
      "type": "number",
      "minimum": 0,
      "description": "Recurring cash per month (USD)."
    },
    "monthly_maintenance_hours": {
      "type": "number",
      "minimum": 0,
      "description": "Expected monthly engineering hours (MDO)."
    },
    "customization_score": {
      "type": "number",
      "minimum": 1,
      "maximum": 10,
      "description": "CTL 1–10, higher = more control."
    },
    "security_risk_score": {
      "type": "number",
      "minimum": 1,
      "maximum": 10,
      "description": "SCR 1–10, higher = more risk."
    },
    "learning_value_score": {
      "type": "number",
      "minimum": 1,
      "maximum": 10,
      "description": "LSM 1–10, higher = more moat value."
    },
    "vendor_lockin_score": {
      "type": "number",
      "minimum": 1,
      "maximum": 10,
      "description": "VLR 1–10, higher = more lock-in."
    },
    "estimate": {
      "type": "boolean",
      "description": "True if metrics are agent-invented until human confirms."
    },
    "sources": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Short assumption/source lines shown on the option card (optional)."
    }
  },
  "required": [
    "id",
    "name",
    "type",
    "prototype_time_hours",
    "monthly_cash_cost",
    "monthly_maintenance_hours",
    "customization_score",
    "security_risk_score",
    "learning_value_score",
    "vendor_lockin_score"
  ],
  "additionalProperties": false
}

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