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assess_ai_initiative

Read-onlyIdempotent

The front door for one AI investment decision. CALL THIS FIRST when the user describes an AI idea in ordinary language or asks whether it should proceed. It resolves industry, revenue, business function, AI tier and organisational readiness, then returns one clarification covering every unresolved input or an Accelerate, Fix or Stop verdict. Ask that clarification once and call this tool again with the answers in the explicit fields. Use work_architecture to test whether the end-to-end workflow, affected roles, human decision rights and performance measures have been redesigned. A stated gap or missing work architecture evidence blocks Accelerate and stays visible in the audit trail. Pillar scores and work architecture evidence remain optional inputs, but unresolved values are never guessed and cannot unlock Accelerate. Use score_initiative when the canonical fields are already known, score_portfolio for several initiatives, and diagnose_process for measured waste in a running process. Deterministic calculation with no authentication. Anonymous usage telemetry may be sent; set AIBVF_TELEMETRY_DISABLE=1 to opt out.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scoresNoOPTIONAL, and each pillar inside it is optional. The four AI BVF pillars, each an honest 0–100 self-assessment, combining deterministically into the verdict: governance_risk ≥ 70 OR financial_return ≤ 20 returns Stop; strategic_alignment, financial_return and change_enablement all ≥ 60 with governance_risk ≤ 40 returns Accelerate; everything else returns Fix. Pass ONLY the pillars the user has real evidence for — do NOT invent numbers for the rest. Missing pillars are estimated deterministically by the engine from disclosed AI BVF planning assumptions, the response reports which via pillar_basis and scores_used, decision score is haircut by how much was estimated, and a fully-estimated pass can never return Accelerate (it returns Fix pending confirmation). So call immediately with whatever the user gave you, then ask for evidence on the estimated pillars and re-call to firm the verdict up.
ai_tierNoOptional correction or answer: automation/RPA, GenAI/copilot, or agentic/autonomous. Overrides anything inferred from proposal.
functionNoOptional correction or answer in canonical or everyday language, for example customer service, procurement, finance or risk. Overrides anything inferred from proposal.
industryNoOptional correction or answer in canonical or everyday language, for example retail, hospital, bank or public sector. Overrides anything inferred from proposal.
proposalYesThe AI initiative in ordinary business language. Include the organisation, industry, approximate annual revenue, business function, AI ambition and how the organisation works today when known. The resolver extracts what it can and, when several inputs are missing, asks for all of them in one clarification; it never guesses an unresolved taxonomy value.
readinessNoOptional correction or answer: agile, traditional, or siloed, including everyday descriptions such as cross-functional, hierarchical or bureaucratic. Overrides anything inferred from proposal.
revenue_eurNoOptional approximate annual revenue in EUR. Overrides any EUR amount extracted from proposal. No currency conversion is performed.
work_architectureNoEvidence that workflows, roles, decision rights and measures are ready. Pass only what is known. Explicit gaps and omitted checks block Accelerate until all four checks are evidenced.
signal_completenessNoOptional 0 to 1 input-quality factor. The default ranges from 0.5 when all pillars are estimated to 1 when all are supplied. Supplied values still require evidence review. Lower this factor when the supplied pillars rest on weak evidence.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYesneeds_input when one or more required decision inputs remain unresolved; verdict when scoring completed.
verdictNoThe AI BVF score. Present only when status is verdict.
proposalYesThe supplied proposal, returned so the next call can preserve it verbatim.
bvf_versionYes
resolutionsYesEvery deterministic resolution, naming the field, canonical value, source and matched phrase.
suggestionsNoAccepted values for an explicitly supplied field that could not be resolved.
next_questionNoOne clarification covering every unresolved input. Present only when status is needs_input; ask it once, then call the tool again with the answers in the explicit fields.
missing_fieldsYes
resolved_inputsYesCanonical fields resolved so far. Explicit corrections override proposal inference.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed8 schema fields changed
    • changedInput schema / properties / scores / description
      Previous value: -"OPTIONAL, and each pillar inside it is optional. The four AI BVF pillars, each an honest 0–100 self-assessment, combining deterministically into the verdict: governance_risk ≥ 70 OR financial_return ≤ 20 returns Stop; strategic_alignment, financial_return and change_enablement all ≥ 60 with governance_risk ≤ 40 returns Accelerate; everything else returns Fix. Pass ONLY the pillars the user has real evidence for — do NOT invent numbers for the rest. Missing pillars are estimated deterministically by the engine from disclosed AI BVF planning assumptions, the response reports which via pillar_basis and scores_used, decision confidence is haircut by how much was estimated, and a fully-estimated pass can never return Accelerate (it returns Fix pending confirmation). So call immediately with whatever the user gave you, then ask for evidence on the estimated pillars and re-call to firm the verdict up."New value: +"OPTIONAL, and each pillar inside it is optional. The four AI BVF pillars, each an honest 0–100 self-assessment, combining deterministically into the verdict: governance_risk ≥ 70 OR financial_return ≤ 20 returns Stop; strategic_alignment, financial_return and change_enablement all ≥ 60 with governance_risk ≤ 40 returns Accelerate; everything else returns Fix. Pass ONLY the pillars the user has real evidence for — do NOT invent numbers for the rest. Missing pillars are estimated deterministically by the engine from disclosed AI BVF planning assumptions, the response reports which via pillar_basis and scores_used, decision score is haircut by how much was estimated, and a fully-estimated pass can never return Accelerate (it returns Fix pending confirmation). So call immediately with whatever the user gave you, then ask for evidence on the estimated pillars and re-call to firm the verdict up."
    • changedInput schema / properties / signal_completeness / description
      Previous value: -"Optional 0–1. How grounded the four pillar scores are in real evidence versus estimated from context. Defaults to 1 (treated as measured). If the organisation lacks formal change-readiness or risk metadata, estimate the pillars from what you know AND set this lower to say so — decision confidence is reduced proportionally and a caveat is attached, instead of returning a falsely confident verdict on soft inputs."New value: +"Optional 0 to 1 input-quality factor. The default ranges from 0.5 when all pillars are estimated to 1 when all are supplied. Supplied values still require evidence review. Lower this factor when the supplied pillars rest on weak evidence."
    • changedInput schema / properties / work_architecture / description
      Previous value: -"Optional evidence that the work around the AI has been redesigned. Pass only what is known. Any explicit false value blocks Accelerate until the gap is closed; omitted checks remain visible as unknown."New value: +"Evidence that workflows, roles, decision rights and measures are ready. Pass only what is known. Explicit gaps and omitted checks block Accelerate until all four checks are evidenced."
    • changedOutput schema / properties / verdict / properties / applied_modules / description
      Previous value: -"BVF scoring modules that fired for this input."New value: +"Scoring-rule and sector-context labels. Sector labels do not certify clinical validation or regulatory compliance."
    • changedOutput schema / properties / verdict / properties / decision_confidence / description
      Previous value: -"Confidence in the verdict, 0-100."New value: +"Heuristic decision score, 0 to 100, adjusted for input quality. This score has no probability calibration."
    • addedOutput schema / properties / verdict / properties / interpretation
      Added value: +{
      +  "additionalProperties": {
      +    "type": "string"
      +  },
      +  "description": "Meaning and limits of compatibility fields. Present these labels when explaining the result.",
      +  "type": "object"
      +}
    • changedOutput schema / properties / verdict / properties / net_value_eur / description
      Previous value: -"Modelled net value in EUR after capture rate, low/high."New value: +"Readiness-adjusted benefit hypothesis before project build, run and change costs. Replace planning rates with scoped economics before funding."
    • changedOutput schema / properties / verdict / properties / sensitivity / properties / readiness_one_notch_down / type
      Previous value: -"object"New value: +[
      +  "object",
      +  "null"
      +]
  2. Changed2 schema fields changed
    • changedInput schema / properties / proposal / description
      Previous value: -"The AI initiative in ordinary business language. Include the organisation, industry, approximate annual revenue, business function, AI ambition and how the organisation works today when known. The resolver extracts what it can and asks one question for the first missing input; it never guesses an unresolved taxonomy value."New value: +"The AI initiative in ordinary business language. Include the organisation, industry, approximate annual revenue, business function, AI ambition and how the organisation works today when known. The resolver extracts what it can and, when several inputs are missing, asks for all of them in one clarification; it never guesses an unresolved taxonomy value."
    • changedOutput schema / properties / next_question / description
      Previous value: -"The single next question to ask. Present only when status is needs_input."New value: +"One clarification covering every unresolved input. Present only when status is needs_input; ask it once, then call the tool again with the answers in the explicit fields."
  3. Changed3 schema fields changed
    • changedOutput schema / properties / verdict / properties / work_architecture / description
      Previous value: -"The work architecture gate across workflow, roles, human decision rights and performance measures. Any stated gap blocks Accelerate."New value: +"The work architecture gate across workflow, roles, human decision rights and performance measures. A stated gap or missing evidence blocks Accelerate."
    • addedOutput schema / properties / verdict / properties / work_architecture / properties / unknowns
      Added value: +{
      +  "items": {
      +    "type": "string"
      +  },
      +  "type": "array"
      +}
    • changedOutput schema / properties / verdict / properties / work_architecture / required
      Previous value: -[
      -  "status",
      -  "blocks_accelerate",
      -  "checks",
      -  "gaps",
      -  "gate"
      -]New value: +[
      +  "status",
      +  "blocks_accelerate",
      +  "checks",
      +  "gaps",
      +  "unknowns",
      +  "gate"
      +]
  4. Changed3 schema fields changed
    • changedInput schema / properties / scores / description
      Previous value: -"OPTIONAL, and each pillar inside it is optional. The four AI BVF pillars, each an honest 0–100 self-assessment, combining deterministically into the verdict: governance_risk ≥ 70 OR financial_return ≤ 20 returns Stop; strategic_alignment, financial_return and change_enablement all ≥ 60 with governance_risk ≤ 40 returns Accelerate; everything else returns Fix. Pass ONLY the pillars the user has real evidence for — do NOT invent numbers for the rest. Missing pillars are estimated deterministically by the engine (from readiness, tier, function and published benchmarks), the response reports which via pillar_basis and scores_used, decision confidence is haircut by how much was estimated, and a fully-estimated pass can never return Accelerate (it returns Fix pending confirmation). So call immediately with whatever the user gave you, then ask for evidence on the estimated pillars and re-call to firm the verdict up."New value: +"OPTIONAL, and each pillar inside it is optional. The four AI BVF pillars, each an honest 0–100 self-assessment, combining deterministically into the verdict: governance_risk ≥ 70 OR financial_return ≤ 20 returns Stop; strategic_alignment, financial_return and change_enablement all ≥ 60 with governance_risk ≤ 40 returns Accelerate; everything else returns Fix. Pass ONLY the pillars the user has real evidence for — do NOT invent numbers for the rest. Missing pillars are estimated deterministically by the engine from disclosed AI BVF planning assumptions, the response reports which via pillar_basis and scores_used, decision confidence is haircut by how much was estimated, and a fully-estimated pass can never return Accelerate (it returns Fix pending confirmation). So call immediately with whatever the user gave you, then ask for evidence on the estimated pillars and re-call to firm the verdict up."
    • changedInput schema / properties / scores / properties / financial_return / description
      Previous value: -"Optional; when omitted, estimated from the published benchmark upside for the function (40–52, never enough to clear 60 unmodelled, never low enough to force a Stop). Strength of the modelled return (0–100, higher is better). A value ≤ 20 forces a Stop on its own; ≥ 60 is one of the four conditions required for Accelerate."New value: +"Optional; when omitted, estimated from the disclosed AI BVF planning range for the function (40–52, never enough to clear 60 unmodelled, never low enough to force a Stop). Strength of the modelled return (0–100, higher is better). A value ≤ 20 forces a Stop on its own; ≥ 60 is one of the four conditions required for Accelerate."
    • changedOutput schema / properties / verdict / properties / benchmark_source / description
      Previous value: -"Citation for the benchmark rates applied."New value: +"Provenance and evidence status for the AI BVF planning rates applied."
  5. Changed1 schema field changed
    • changedOutput schema / properties / verdict / properties / feedback / description
      Previous value: -"Optional three-question feedback route, present only for Fix/Stop verdicts. The link opens a prefilled email; no assessment data is added and no response is recorded unless the user chooses to send it."New value: +"Optional three-question feedback route, present only for Fix/Stop verdicts. The page records the response anonymously only when the user chooses an answer; no assessment data is attached."
  6. Changed1 schema field changed
    • changedOutput schema / properties / verdict / properties / feedback / description
      Previous value: -"Optional one-question feedback route, present only for Fix/Stop verdicts. The link opens a prefilled email; no response is recorded unless the user chooses to send it."New value: +"Optional three-question feedback route, present only for Fix/Stop verdicts. The link opens a prefilled email; no assessment data is added and no response is recorded unless the user chooses to send it."
  7. Changed3 schema fields changed
    • addedInput schema / properties / work_architecture
      Added value: +{
      +  "description": "Optional evidence that the work around the AI has been redesigned. Pass only what is known. Any explicit false value blocks Accelerate until the gap is closed; omitted checks remain visible as unknown.",
      +  "properties": {
      +    "decision_rights_defined": {
      +      "description": "True only when decision, override and escalation rights have named human owners, false when authority remains unclear.",
      +      "type": "boolean"
      +    },
      +    "measures_updated": {
      +      "description": "True only when performance measures and incentives reflect the redesigned work, false when the old measures remain.",
      +      "type": "boolean"
      +    },
      +    "roles_redesigned": {
      +      "description": "True only when affected roles, accountabilities and capability expectations have been rewritten, false when roles remain unchanged.",
      +      "type": "boolean"
      +    },
      +    "workflow_redesigned": {
      +      "description": "True only when the end-to-end workflow has been redesigned around the AI and retained human judgement, false when the existing workflow remains.",
      +      "type": "boolean"
      +    }
      +  },
      +  "type": "object"
      +}
    • addedOutput schema / properties / verdict / properties / work_architecture
      Added value: +{
      +  "description": "The work architecture gate across workflow, roles, human decision rights and performance measures. Any stated gap blocks Accelerate.",
      +  "properties": {
      +    "blocks_accelerate": {
      +      "type": "boolean"
      +    },
      +    "checks": {
      +      "items": {
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "gaps": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "gate": {
      +      "type": "string"
      +    },
      +    "next_question": {
      +      "type": "string"
      +    },
      +    "status": {
      +      "enum": [
      +        "unknown",
      +        "partial",
      +        "gap",
      +        "ready"
      +      ],
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "status",
      +    "blocks_accelerate",
      +    "checks",
      +    "gaps",
      +    "gate"
      +  ],
      +  "type": "object"
      +}
    • changedOutput schema / properties / verdict / required
      Previous value: -[
      -  "bvf_version",
      -  "classification",
      -  "reason",
      -  "net_value_eur",
      -  "gross_value_eur",
      -  "decision_confidence",
      -  "multipliers",
      -  "drivers",
      -  "benchmark_source",
      -  "applied_modules"
      -]New value: +[
      +  "bvf_version",
      +  "classification",
      +  "reason",
      +  "net_value_eur",
      +  "gross_value_eur",
      +  "decision_confidence",
      +  "multipliers",
      +  "drivers",
      +  "benchmark_source",
      +  "applied_modules",
      +  "work_architecture"
      +]
  8. Added

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/no-open-world annotations, it discloses deterministic calculation, no authentication requirement, telemetry with an opt-out env var, that unresolved values are never guessed, that stated gaps block Accelerate and stay in the audit trail, and that a fully-estimated pass cannot return Accelerate. That is substantive process and side-effect context the annotations do not carry.

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?

Front-loaded with the trigger and verdict semantics, and almost every sentence earns its place. It is quite long and repeats the 'never guesses unresolved values' point, but the density is justified by the tool's complexity.

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?

An output schema exists, so return values need not be described, and the description still covers what matters: blocking conditions, estimation fallbacks, sibling routing, auth and telemetry. Complete for a 9-parameter tool with nested objects and verdict logic.

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 adds cross-parameter behavior: pass only evidence-backed pillars, missing pillars are estimated and reported via pillar_basis/scores_used, decision score is haircut by estimation, and the intended call-then-re-call cadence. It does not restate every field, which is appropriate given the schema already documents them.

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?

States a specific verb+resource ('assess an AI initiative', 'front door for one AI investment decision') and specifies what it resolves (industry, revenue, function, AI tier, readiness) and what it returns (one clarification or an Accelerate/Fix/Stop verdict). It explicitly distinguishes itself from score_initiative, score_portfolio, diagnose_process and work_architecture.

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?

Gives an explicit trigger ('CALL THIS FIRST when the user describes an AI idea in ordinary language'), the re-call workflow once the clarification is answered, and routes each alternative by condition: score_initiative for known canonical fields, score_portfolio for several initiatives, diagnose_process for measured waste, work_architecture for redesign evidence. When-to-use and when-not-to-use are both covered.

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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