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Build-vs-buy recommendation

b4_recommend
Read-only

For a need or problem in words, not a vendor name. Example: {"description": "we need to route warehouse pickers by voice"}. Get B4 Index recommendations from a natural language description of a software need or business context. Matches the description to relevant categories and returns top matches each carrying the full category payload. Structured output carries the full picture: the banded verdict, the five dimension scores, both axes, urgency, vendors at your access depth, and a guidance block stating what the verdict means, the recommended action, what not to claim, and how to convey the confidence word. Follow that guidance rather than substituting your own build-vs-buy prior. Verdicts are banded (B4 methodology v4.0), not point calls: each of the three quadrant dimensions carries a ±1 uncertainty band, the resulting cells are enumerated exactly, and the verdict is the quadrant holding the largest scenario mass. Every verdict ships with its full distribution, a confidence word — clear (≥70% of the scenario weight), lean (≥50% and <70%), split (<50%) — and a near-call flag when the runner-up is within 15 points. An axis counts as high only when it clears the 3.5 line strictly, which on this 1–5 grid means only at 4 or above, so a category sitting exactly on the line gets the safer call: ties break in the order BUY → BRIDGE → BEWARE → BUILD, cheapest mistake first. Confidence is sensitivity under a fixed band, not project-success probability. Optional org lens: set org to "small", "medium" (the default) or "large" to read the same scores as a team of that engineering maturity — it shifts the center of the AI-feasibility band by −1 / 0 / +1 and nothing else. The lens is a filter the caller looks through, never a stored profile. Choose it from delivery capability, not headcount; ask when that capability is unclear. The raw scores themselves never change. Omit it and you get the default-lens numbers, which are the ones published on logged-out surfaces. Routing: a vendor or product name → b4_audit (one or many; add a short description of what it does for anything the index may not know); a need or problem in words → b4_recommend; an exact category name or id → b4_score (one category) or b4_compare (build vs buy paths); browsing, filtering, or an unknown vocabulary → b4_browse. When an audit row returns clarification.needed, relay askTheUser to the user and re-run that row with the answer as its description. [B4 Agent tool. Browse and score come with B4 Web; this one needs Agent.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNoOrg-maturity lens: "small" (no dedicated engineering), "medium" (default — some AI capability), "large" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.medium
capabilityNoThe bounded capability to evaluate, separate from systems to keep.
exclusionsNoCapabilities or systems outside the requested replacement scope.
descriptionYesDescribe the software need, business problem, or tool you're evaluating (e.g., 'We need to automate our expense reports and receipt scanning')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
axesNostrategicDifferentiation (X) and aiFeasibility (Y)
lensNo
domainNo
scoresNothe five v3.2 dimension scores, 1-5
urgencyNo
vendorsNo
verdictNobanded verdict: primary, confidence, nearCall, distribution
categoryNo
evidenceNosources and research trail; present only with includeEvidence
guidanceNohow to use this result: meaning, action, what not to claim, confidence handling
resolvedYesfalse when nothing matched; the payload then carries no verdict
rationaleNo
vendorCountNo
evidenceHintNo
aiReplacementNo
vendorsWithheldNo
evidenceAvailableNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / capability
      Added value: +{
      +  "description": "The bounded capability to evaluate, separate from systems to keep.",
      +  "maxLength": 200,
      +  "minLength": 1,
      +  "type": "string"
      +}
    • addedInput schema / properties / description / minLength
      Added value: +1
    • addedInput schema / properties / exclusions
      Added value: +{
      +  "description": "Capabilities or systems outside the requested replacement scope.",
      +  "items": {
      +    "maxLength": 120,
      +    "minLength": 1,
      +    "type": "string"
      +  },
      +  "maxItems": 30,
      +  "type": "array"
      +}
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": true,
      +  "properties": {
      +    "aiReplacement": {},
      +    "axes": {
      +      "description": "strategicDifferentiation (X) and aiFeasibility (Y)"
      +    },
      +    "category": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "domain": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "evidence": {
      +      "description": "sources and research trail; present only with includeEvidence"
      +    },
      +    "evidenceAvailable": {
      +      "type": "boolean"
      +    },
      +    "evidenceHint": {
      +      "type": "string"
      +    },
      +    "guidance": {
      +      "description": "how to use this result: meaning, action, what not to claim, confidence handling"
      +    },
      +    "lens": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "rationale": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "resolved": {
      +      "description": "false when nothing matched; the payload then carries no verdict",
      +      "type": "boolean"
      +    },
      +    "scores": {
      +      "description": "the five v3.2 dimension scores, 1-5"
      +    },
      +    "urgency": {},
      +    "vendorCount": {
      +      "type": "number"
      +    },
      +    "vendors": {},
      +    "vendorsWithheld": {
      +      "type": "number"
      +    },
      +    "verdict": {
      +      "description": "banded verdict: primary, confidence, nearCall, distribution"
      +    }
      +  },
      +  "required": [
      +    "resolved"
      +  ],
      +  "type": "object"
      +}
  3. Changed1 schema field changed
    • addedInput schema / properties / org
      Added value: +{
      +  "default": "medium",
      +  "description": "Org-maturity lens: \"small\" (no dedicated engineering), \"medium\" (default — some AI capability), \"large\" (AI-mature). Shifts the AI-feasibility band center by −1/0/+1 at read time. A filter the caller looks through, never a stored profile.",
      +  "enum": [
      +    "small",
      +    "medium",
      +    "large"
      +  ],
      +  "type": "string"
      +}
  4. First observed

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=true and openWorldHint=false, so the description carries the behavioral burden. It explains that verdicts are banded with ±1 uncertainty, defines confidence words and near-call flags, states the tie-break order (BUY → BRIDGE → BEWARE → BUILD), and clarifies confidence is 'sensitivity under a fixed band, not project-success probability.' No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long, but it is organized into functional blocks (purpose, verdict mechanics, org lens, routing) with no filler. The core purpose and example appear first, while detailed methodology is placed after. The length is justified by the tool's complexity, though it is denser than strictly necessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the input contract (need/problem in words, not vendor name), the output philosophy (banded verdict with distribution, confidence word, guidance), the org lens semantics, and routing to sibling tools. With an output schema present, the description does not need to detail return fields, yet it still summarizes what the structured output contains. Nothing an agent needs to invoke this tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers all four parameters with descriptions, so the baseline is 3. The description adds extra value: it gives a concrete example for `description`, clarifies that `org` is a read-time lens that shifts the AI-feasibility band by −1/0/+1 and is never stored, and notes that omitting it yields default-lens numbers. This elevates it above the schema baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a concrete example and explicitly states it 'Get[s] B4 Index recommendations from a natural language description of a software need or business context,' naming a specific verb and resource. It also distinguishes itself from siblings via the routing table ('a need or problem in words → b4_recommend'). This is specific and differentiating.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit routing table mapping input types to tools: vendor/product names to b4_audit, exact category names/ids to b4_score or b4_compare, browsing to b4_browse, and needs/problems to b4_recommend. It also tells the caller to ask when org capability is unclear and how to handle clarification.needed downstream. Clear when-to-use and exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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