Skip to main content
Glama

recommend_improvements

Read-onlyIdempotent

Turn a Fix or Stop verdict into the change plan that could earn a re-score, with pillar targets, named plays, owners, stop conditions, cost of waiting and a deadline. CALL THIS after score_initiative returns Fix or Stop, using the same five context fields and any scores or work-architecture evidence from that call. Do not use it to produce the initial verdict, sequence several initiatives or diagnose measured process waste; use score_initiative, sequence_portfolio or diagnose_process for those jobs. Do not call it for Accelerate unless a specific delivery risk needs testing before commitment. resistance_type selects the will or skill route, risk_type selects the regulatory, reputational or operational route, and omitted diagnostics remain provisional with the next question returned. Lead with binding_constraint, surface honest_stop when present, and use rescore_gate to decide whether this remains Fix or becomes Stop. Pure deterministic calculation, no network, auth or side effects.

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 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.
ai_tierYesAmbition of the AI being deployed: gen1 = automation/RPA, gen2 = GenAI, gen3 = agentic. Interacts with readiness — a more ambitious tier running on lower readiness widens the pace-layer gap, which discounts the modelled EUR value even when the four pillar scores are strong.
functionYesBusiness function where the AI will operate, as one of the accepted enum values — selects which benchmark value drivers and rate ranges apply. Call list_taxonomy for the exact strings if unsure.
industryYesYour industry, as one of the accepted enum values — used to select the benchmark rate multiplier applied to the modelled EUR value. Call list_taxonomy for the exact strings if unsure.
readinessYesOrganisational readiness, honest self-assessment: agile = cross-functional, fast decisions; traditional = functional hierarchy; siloed = rigid, hand-off heavy. Sets the value-capture rate and, paired with ai_tier, the pace-layer drag — lower readiness against a higher tier reduces the captured value. Self-report is gameable: when the user has real process numbers, call infer_readiness first and pass its measured classification here instead.
risk_typeNoOptional. The nature of a high governance-risk score: "regulatory" = statute applies (EU AI Act, GDPR Article 22, DORA), "reputational" = the risk is how failure looks and lands publicly, "operational" = the system failing quietly inside a process. Selects between a regulatory remediation sequence, visible trust guardrails, and a proportionate governance review. If you do not know, omit it: the engine infers (gen3 tier, or a regulated function/industry, infers regulatory) and marks the play provisional.
revenue_eurYesApproximate annual revenue in EUR (must be ≥ 0). Scales the whole output: the disclosed AI BVF planning rates are applied as fractions of this figure, so the modelled EUR value range grows with it. A rough order-of-magnitude estimate is fine.
resistance_typeNoOptional. What sits behind a low change-enablement score: "will" = people do not want the change (power shifts, fear, no case for change), "skill" = people cannot yet do it (capability and capacity gap). Selects between a coalition-building play (Kotter 1-2 + ADKAR Awareness/Desire) and an owner-and-capability play (ADKAR Knowledge/Ability). If you do not know, omit it: the engine infers from readiness (agile infers skill, traditional/siloed infers will) and marks the play provisional. Ask the user "is the resistance about not wanting this, or not being able to do it yet?" and re-call to sharpen.
work_architectureNoOptional 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.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
auditNoReproducibility record: engine version, the rules that fired, and the resolved inputs. Deterministic, no timestamps. If the verdict is challenged months later, the same inputs on the same engine version reproduce it exactly.
notesYesCaveats or context on the recommendation set.
feasibleYesWhether the target is reachable via the listed pillar moves.
feedbackNoOptional 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.
bvf_versionYesAI BVF protocol version used.
change_planNoThe change-leader layer: a specific, sequenced route from Fix or Stop toward Go, aimed at the organisation. Present for Fix/Stop, absent when the initiative is already Accelerate. Present this to the user as the plan, not as raw data.
recommendationsYesPer-pillar improvement actions.
advisory_next_stepNoOptional CTA, present only for Fix/Stop verdicts.
target_classificationYesVerdict the recommendations aim to reach.
current_classificationYesVerdict as the initiative stands today.
projected_decision_confidenceYesConfidence in the verdict if the recommendations land, 0-100.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / properties / revenue_eur / description
      Previous value: -"Approximate annual revenue in EUR (must be ≥ 0). Scales the whole output: the benchmark rates are applied as fractions of this figure, so the modelled EUR value range grows with it. A rough order-of-magnitude estimate is fine."New value: +"Approximate annual revenue in EUR (must be ≥ 0). Scales the whole output: the disclosed AI BVF planning rates are applied as fractions of this figure, so the modelled EUR value range grows with it. A rough order-of-magnitude estimate is fine."
    • 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."
  2. Changed1 schema field changed
    • addedInput schema / description
      Added value: +"Inputs for a change plan after a Fix or Stop verdict. industry, revenue_eur, function, ai_tier and readiness must match the scoring call so the plan is built against the same case. scores and work_architecture may be copied from score_initiative; omitted pillars are estimated and make the plan provisional. resistance_type and risk_type are optional diagnostics that select the play, and omission triggers a named inference plus the next question to ask."
  3. Changed1 schema field changed
    • changedOutput schema / 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."
  4. Changed1 schema field changed
    • changedOutput schema / 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."
  5. Changed1 schema field 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"
      +}
  6. Changed1 schema field changed
    • addedOutput schema / properties / feedback
      Added value: +{
      +  "description": "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.",
      +  "properties": {
      +    "question": {
      +      "type": "string"
      +    },
      +    "url": {
      +      "format": "uri",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "question",
      +    "url"
      +  ],
      +  "type": "object"
      +}
  7. Changed1 schema field changed
    • addedOutput schema / properties / audit
      Added value: +{
      +  "description": "Reproducibility record: engine version, the rules that fired, and the resolved inputs. Deterministic, no timestamps. If the verdict is challenged months later, the same inputs on the same engine version reproduce it exactly.",
      +  "properties": {
      +    "bvf_version": {
      +      "type": "string"
      +    },
      +    "engine": {
      +      "type": "string"
      +    },
      +    "engine_version": {
      +      "type": "string"
      +    },
      +    "inputs_used": {
      +      "description": "The resolved inputs the result was computed on, including estimated pillar values.",
      +      "type": "object"
      +    },
      +    "note": {
      +      "type": "string"
      +    },
      +    "rules_fired": {
      +      "description": "The rules that actually fired, in order: estimation, gates, classification, value arithmetic.",
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "type": "object"
      +}
  8. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses meaningful behavioral internals beyond the annotations: omitted diagnostics remain provisional, missing pillars are estimated and enshrined as marked provisional, a next question is returned, and it is a "pure deterministic calculation, no network, auth or side effects." It also explains treatment of resistance_type and risk_type route selection, and highlights how previously estimated pillars require re-calling.

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

Conciseness5/5

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

Every sentence expands the invocation contract: what it produces, when to call it, when not to call it, interplay between optional diagnostics, and execution nature. It is dense but not inflated; the first sentence states the purpose, and later sentences give operational and exclusion rules without padding.

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?

Given a fully described input schema, an output schema exists, and the description addresses the conditional workflow, the same-case requirement, missing values, and the route selection mechanisms, no critical guidance gap remains for an agent to invoke it correctly after scoring.

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 input schema already covers 100% of parameter semantics in detail, so this could be baseline 3. The description adds value by tying parameters to the orchestration contract: "same five context fields", "scores and work-architecture evidence from that call", and the interaction of optional diagnostics with route selection. It also adds explicit guardrail: omitted diagnostics remain provisional with the next question returned.

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: "Turn a Fix or Stop verdict into the change plan that could earn a re-score," and enumerates concrete outputs (pillar targets, named plays, owners, stop conditions, cost of waiting, deadline). It clearly differentiates from siblings by saying do not use it for initial verdict, sequencing, or process diagnosis jobs that belong to score_initiative, sequence_portfolio, or diagnose_process.

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?

It gives an explicit when-to-use condition — "CALL THIS after score_initiative returns Fix or Stop, using the same five context fields" — and explicit when-not-to-use exclusions with named alternatives. It also warns against calling for Accelerate unless a specific delivery risk needs testing before commitment, which is unique and essential routing guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.