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Score a software category

b4_score
Read-only

For one exact category name or id. Example: {"category": "Expense Management", "org": "medium"}. Score a software category using the B4 Index. Provide a known category name to get pre-computed scores, or provide raw dimension scores (1-5 each) for a custom evaluation. 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. Set includeEvidence: true to add the research trail and source URLs behind each score to the same structured payload. 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. [Needs a B4 plan: browse and score come with B4 Web.]

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
scoresNoCustom dimension scores for a tool not in the database
categoryNoName of a known B4 category (e.g., 'Expense Management', 'CRM')
includeEvidenceNoInclude the full evidence trail and source URLs behind each dimension score. Off by default so the initial result stays concise; set true for deep verification.

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. Changed2 schema fields changed
    • changedInput schema / properties / scores / properties / costTrajectory / description
      Previous value: -"1-5: How much is build cost beating vendor cost?"New value: +"Cost Trajectory: 1 build TCO at least vendor cost, stable gap; 2 costly alternative with limited improvement evidence; 3 mixed or modest advantage with material assumptions; 4 substantial and widening TCO advantage; 5 credible 80%+ value for <10% annual cost. Compare equivalent scope and horizons, including transition and operation. Do not supply an invented rating when evidence is missing."
    • changedInput schema / properties / scores / properties / vendorValue / description
      Previous value: -"1-5: How much vendor value are you NOT using? (higher = more waste)"New value: +"1-5: Purchased capability fit; higher means weaker fit. Include essential exceptions and support; utilization is not a spending share."
  2. Changed8 schema fields changed
    • addedInput schema / properties / category / anyOf
      Added value: +[
      +  {
      +    "maxLength": 120,
      +    "minLength": 1,
      +    "type": "string"
      +  },
      +  {
      +    "exclusiveMinimum": 0,
      +    "type": "integer"
      +  }
      +]
    • removedInput schema / properties / category / maxLength
      Removed value: -120
    • removedInput schema / properties / category / type
      Removed value: -"string"
    • changedInput schema / properties / scores / properties / aiFeasibility / type
      Previous value: -"number"New value: +"integer"
    • changedInput schema / properties / scores / properties / costTrajectory / type
      Previous value: -"number"New value: +"integer"
    • changedInput schema / properties / scores / properties / specificity / type
      Previous value: -"number"New value: +"integer"
    • changedInput schema / properties / scores / properties / strategicControl / type
      Previous value: -"number"New value: +"integer"
    • changedInput schema / properties / scores / properties / vendorValue / type
      Previous value: -"number"New value: +"integer"
  3. 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"
      +}
  4. 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"
      +}
  5. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Even though readOnlyHint=true already indicates a safe read operation, the description adds substantial behavioral detail: banded verdicts, ±1 uncertainty bands, confidence word thresholds, tie-breaking order, the strict 3.5 cutoff for high axes, and the org lens being a transient filter rather than a stored profile. It also explicitly disclaims that 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 every section earns its place: example, modes, output contents, methodology constraints, org lens semantics, and routing. It is front-loaded with the core invocation pattern. The density is justified by the tool's complexity, though it is not concise in an absolute sense.

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?

For a complex tool with four parameters and a rich output schema, the description is complete: it covers input modes, output structure, verdict semantics, confidence interpretation, organiational lens behavior, evidence inclusion, and cross-tool routing. The structured output schema already carries return details, so the description does not need to restate them.

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?

Schema coverage is 100%, so the baseline is 3, but the description meaningfully enriches the parameters with a concrete example, clarifies that scores is for custom evaluations, explains what includeEvidence adds to the payload, and stresses that the org lens only shifts the AI-feasibility band center and never changes raw scores. This exceeds the schema's own descriptions.

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 specific verb and resource: score one exact category name or id using the B4 Index. It clearly delineates two modes (pre-computed scores for known categories, custom evaluation via raw dimension scores), and the routing paragraph explicitly distinguishes this tool from b4_audit, b4_recommend, b4_compare, and b4_browse.

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?

Routing guidance is explicit: vendor/product names go to b4_audit, needs/problems to b4_recommend, exact category names/ids to b4_score or b4_compare, and browsing/unknown vocabulary to b4_browse. It also clarifies when to use b4_score vs b4_compare and when to include evidence or set the org lens, leaving no ambiguity about tool selection.

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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