// screens-standards.jsx — Standards (Project Management step, 7/28).
// The published truth behind every diagnosis. Two stacked sections, matching the
// Claude Design layout:
// A. Conversion Rate Standards — the LIVE health_baselines table (22 canonical
// metrics, per project_type) with a visual healthy band (mean ±1σ). Not a
// hand-typed table: if a metric has no baseline the row says so rather than
// inventing a number, because the engine scores it z = 0 either way.
// B. Rule Book — all 27 diagnosis outcomes across the 18 rule slots in
// health-engine.js, each with its literal firing condition, the Action
// Playbook text (live from health_playbook, static Excel text as fallback),
// and a PROPOSED attribution tag awaiting Brian's redline.
// The Excel-vs-Vault derivation redline lives in the audit document, not on this
// page — engine drift is a review artifact, not a published standard.
// Read-only. No writes, no new tables. Reads listHealthBaselines + listHealthPlaybook.
(function () {
const { useState, useEffect, useMemo } = React;
const LINE = "#E4E9F0", MUTE = "#8A97A8", INK = "#22303F";
const MONO = "var(--f-mono, 'IBM Plex Mono', monospace)";
const PANEL = { background: "#fff", border: `1px solid ${LINE}`, borderRadius: 14, padding: 20, marginBottom: 18 };
// App shell wraps screens in an unpadded div, so every screen supplies its own.
// Zero horizontal padding was why this page sat flush against the sidebar.
const PAGE_FRAME = { padding: "26px 30px 80px", boxSizing: "border-box", width: "100%", maxWidth: 1480 };
const KICK = { fontFamily: MONO, fontSize: 11, fontWeight: 600, letterSpacing: ".16em", textTransform: "uppercase", color: "#7C8DA1" };
const TH = { textAlign: "left", padding: "8px 10px", borderBottom: `1px solid ${LINE}`, fontFamily: MONO, fontSize: 10, fontWeight: 600, letterSpacing: ".12em", textTransform: "uppercase", color: "#7C8DA1", whiteSpace: "nowrap" };
const TD = { padding: "9px 10px", borderBottom: "1px solid #F0F3F7", fontSize: 12.5, color: INK, verticalAlign: "top" };
const NUM = { ...TD, fontVariantNumeric: "tabular-nums", textAlign: "right", whiteSpace: "nowrap" };
// ── A. metric dictionary ────────────────────────────────────────────────
// key order == health-engine.js METRIC_KEYS. label/desc/unit are presentation
// only; the numbers all come from the health_baselines rows.
const METRICS = [
["leadRate", "Lead Rate", "leads ÷ approved", "%"],
["approvalRate", "Approval Rate", "approved ÷ targets sent", "%"],
["contactRate", "Contact Rate", "contacted ÷ approved", "%"],
["ccRate", "CC Conversion Rate", "conference calls ÷ leads", "%"],
["visitRate", "Visit Rate", "visits ÷ conference calls", "%"],
["offersRate", "Offers Rate", "offers ÷ visits", "%"],
["callsPerLead", "Calls / Lead", "call effort per lead", ""],
["mailingsPerLead", "Mailings / Lead", "mail effort per lead", ""],
["avgMailPerMo", "Avg Mail / Mo", "mailings ÷ months since anchor", ""],
["pctCallDM1", "% Call by DM1", "calls completed by the module lead", "%"],
["mailingPerApproval", "Mailing / Approval", "mailings ÷ approved", ""],
["callPerApproval", "Call / Approval", "calls ÷ approved", ""],
["broadcastDrag", "Broadcast Drag", "calls/lead − mailings/lead", ""],
["daysSinceApproval", "Days Since Approval", "days since the last list went out", "d"],
["listsPerMo", "Lists / Mo", "research cadence", ""],
["targetsApproved", "Targets Approved", "approved in the window", ""],
["callsPerMailing", "Calls / Mailing", "call-to-mail balance", ""],
["touchesPerLead", "Touches / Lead", "(calls + mailings) ÷ leads", ""],
["obRate", "O&B Rate", "(offers + LOIs + closed) ÷ CCs", "%"],
["approvedPerMo", "Approved / Mo", "approval velocity", ""],
["sentPerMo", "Sent / Mo", "names sent per month", ""],
["avgCallsPerMo", "Avg Calls / Mo", "calls ÷ months since anchor", ""],
];
// ── B. rule book ────────────────────────────────────────────────────────
// slot = the Diagnostics column letter. cond = the literal predicate as ported
// in health-engine.js. attribution is PROPOSED (Excel colour key row 3 only
// separates client-engagement / our-process / healthy; the per-rule mapping is
// mine and is what Brian is redlining).
const A_PROC = "OUR PROCESS", A_CLI = "CLIENT", A_STR = "STRENGTH", A_MIX = "MIXED";
const RULES = [
["Z", "Bad Research", A_PROC,
"Approval Rate z > 1 AND Lead Rate z ≥ −1 AND CC Conversion z < −1",
"Loose list criteria. The client approves plenty and leads arrive, but they do not survive to a conference call — the names are not real fits."],
["AA", "Picky (selective – converts well downstream)", A_CLI,
"CC Conversion z < −1, no approach rule fired, AND (Visit z > 1 OR Offers z > 1)",
"Client takes few calls but the ones they take convert. Selectivity, not disengagement."],
["AA", "Universe is Picked Over", A_CLI,
"CC Conversion z < −1, no approach rule fired, Visit z ≤ 0 AND Offers z ≤ 0, AND Approval z < −1",
"Low conversion with a starved approval rate: the TAM is exhausted."],
["AA", "Low Client Engagement – Harvey process is fine", A_CLI,
"CC Conversion z < −1, no approach rule fired, Visit z ≤ 0 AND Offers z ≤ 0, Approval z ≥ −1",
"Conversion is soft while our mechanics are clean and approvals are normal. The constraint is on the client side."],
["AB", "Review Call Quality / Pitch", A_PROC,
"Lead z < −1 AND Calls/Lead z > 1 AND Calls/Mailing z > 0.75 AND %Call-DM1 z < −0.75",
"Many calls into the same companies, not reaching the decision maker, no leads. Junior or ineffective calling."],
["AC", "Call Coverage (DM1)", A_PROC,
"%Call-DM1 z < −0.75 AND Lead z < −1 AND (Calls/Lead z > 1 OR Call/Approval z > 1) AND Review Call Quality did not fire",
"Decision-maker coverage gap. Suppressed when Review Call Quality already explains it."],
["AD", "Brochure Quality / Pitch", A_PROC,
"Lead z < −1 AND Mailings/Lead z > 1 AND Mailing/Approval z ≤ 1 AND Approval z ≥ −1",
"Mail-heavy and not pulling leads, with a normal approach cycle. The collateral is the suspect."],
["AE", "Process Integrity (Follow-Through) - also Evaluate Brochure/Pitch", A_PROC,
"Mailing/Approval z > 1 AND Calls/Mailing z ≥ −0.5 AND Touches/Lead z > 1",
"Re-mailing before finishing the cycle, at very high total touches per lead. Both process and collateral."],
["AE", "Process Integrity (Follow-Through)", A_PROC,
"Mailing/Approval z > 1 AND Calls/Mailing z ≥ −0.5 AND Touches/Lead z ≤ 1",
"Approach cycles are being restarted before they complete."],
["AE", "Process Integrity (Needs Calls) - High Mailings, Low Calls", A_PROC,
"Mailing/Approval z > 1 AND Calls/Mailing z < −0.5 AND Call/Approval z > 0",
"Mail is going out without the calls that make it work."],
["AE", "Requires Call Attention", A_PROC,
"Mailing/Approval z > 1 AND Calls/Mailing z < −0.5 AND Call/Approval z ≤ 0",
"The approved pool is under-called on every measure."],
["AF", "Over-Working Universe - Needs Research or TAM Expansion", A_PROC,
"Call/Approval z > 1 AND Approved/Mo z < −0.75",
"Squeezing a maxed-out universe. The constraint is the map, not the motion."],
["AF", "Over-Worked Universe (targets receive lots of inquiries) / or calls ineffective", A_MIX,
"Call/Approval z > 1 AND Approved/Mo z ≥ −0.75 AND Calls/Lead z > 1",
"Many calls to reach a target: a saturated or hard-to-reach universe, or an ineffective pitch."],
["AF", "Over-working Universe", A_PROC,
"Call/Approval z > 1 AND Approved/Mo z ≥ −0.75 AND Calls/Lead z ≤ 1",
"Call cadence is heavy against a small approved pool."],
["AG", "Needs Approval List", A_CLI,
"Days Since Approval z > 1",
"The client has not fed the pipeline with new approvals. Supplying the list is our job."],
["AH", "Mid-funnel Disengagement", A_CLI,
"CC Conversion z ≥ −1 AND (Visit z < −1 OR Offers z < −1)",
"The client takes the call and then stalls before a visit or an offer."],
["AI", "Needs Call Love (mail-reliant, add calls)", A_PROC,
"Calls/Lead z < 0 AND Broadcast Drag z < −0.5 AND Lead z ≥ 0 AND CC Conversion z ≥ 0",
"Solid lead and CC performance carried by mail. Adding calls is cheap upside."],
["AJ", "Good Return per Call -- efficient, low effort / lead", A_STR,
"Calls/Lead z < 0.5 AND Mailings/Lead z < 0 AND Avg Mail/Mo z < 0 AND Lead z ≥ 0, no problem rule firing, AND (Needs Approval List silent OR health above cohort average)",
"Leads arrive cheaply. This is the best marginal return on senior time in the book."],
["AK", "Low Health – investigate", A_MIX,
"health z < −1 AND no other rule fired",
"Below-cohort health with no single pattern. Manual review."],
["AL", "Aggressive Client - Invest in Research", A_STR,
"Sent/Mo z < −0.5 AND Approved/Mo z < −0.5 AND CC Conversion z > 0.67 AND Visit z > 0.67",
"Thin supply against strong downstream conversion. Feed it more targets."],
["AM", "Aggressive Client - Improve Contact Rate", A_STR,
"Contact z < −0.5 AND CC Conversion z > 0 AND Offers z > 0 AND Lead z ≥ −1",
"They convert what they touch. Touch more."],
["AR", "Funnel Conversion Soft (strong top-funnel, weak conversion)", A_CLI,
"health z < −1 AND (Contact z ≥ 0 OR Lead z ≥ 0) AND CC Conversion z < 0 AND Visit z < 0 AND Offers z < 0, nothing above fired",
"Good lead generation, weak conversion. Coach the client through CC → visit → offer and revisit the buy-box."],
["AT", "Aggressive Client - high conversion from CC to Offer", A_STR,
"O&B Rate z > 1",
"A strong converter. Protect and scale."],
["AU", "Clean Process", A_STR,
"All eight outreach z within ±1 (Calls/Lead, Mailings/Lead, Avg Mail/Mo, Mailing/Approval, Call/Approval, Broadcast Drag, Calls/Mailing, Touches/Lead) AND raw Broadcast Drag ≥ 0",
"No outreach abnormality anywhere. On track."],
["AU", "Clean Process - potential trend issue", A_STR,
"All eight outreach z within ±1 AND raw Broadcast Drag < 0",
"Healthy now, but the mix is turning mail-heavy. Watch for TAM exhaustion and declining approvals."],
["AX", "High-Volume Project", A_STR,
"Approved/Mo z > 1 AND O&B Rate z > −0.25",
"High-velocity against a fragmented universe. Keep the pedal down."],
["AX", "High-Volume Project - CC to Offer Conversion Low", A_MIX,
"Approved/Mo z > 1 AND O&B Rate z ≤ −0.25",
"Volume is there, conversion is not. Push the client to make offers and weed out window shoppers."],
];
// Excel 'Action Playbook' A2:B28, verbatim — the fallback when health_playbook
// has no row for a diagnosis (and the seed text if that table is ever empty).
const PLAYBOOK_FALLBACK = {
"Bad Research": "Tighten research criteria; refine target profile / buy-box with client",
"Picky (selective – converts well downstream)": "Pre-qualify conference calls harder; focus on best-fit targets only",
"Universe is Picked Over": "Expand TAM / commission new research; level-set expectations with client",
"Low Client Engagement – Harvey process is fine": "Re-engage client; revisit fit & buy-box — not a process problem",
"Review Call Quality / Pitch": "Coach callers; review call script / pitch; consider ways to bolster the message; new hook; check DM1 reach",
"Call Coverage (DM1)": "Improve decision-maker coverage; prioritize outreach from DM1",
"Brochure Quality / Pitch": "Revise brochure; test new messaging; improve hook - may be specific to the industry dynamic",
"Process Integrity (Follow-Through) - also Evaluate Brochure/Pitch": "Finish approach cycles before re-mailing; also review collateral (very high touch volume)",
"Process Integrity (Follow-Through)": "Enforce approach-cycle follow-through; stop premature re-mailing; consider adding RA/Analyst call resources to C2/3s",
"Process Integrity (Needs Calls) - High Mailings, Low Calls": "Add calls to mailed targets; don't re-mail without calling",
"Requires Call Attention": "Increase calling effort; targets are under-called",
"Over-Working Universe - Needs Research or TAM Expansion": "Expand TAM / commission research; or level-set expectations (limited universe)",
"Over-Worked Universe (targets receive lots of inquiries) / or calls ineffective": "Saturated / hard-to-reach universe; assess call / pitch effectiveness; consider easing cadence",
"Over-working Universe": "Review call cadence — risk of over-contacting a small approved universe",
"Needs Approval List": "Send a fresh approval list; current list has gone stale",
"Mid-funnel Disengagement": "Client has trouble engaging - diagnose drop-off after the conference call; tighten conference call to visit/offer conversion",
"Needs Call Love (mail-reliant, add calls)": "Shift outreach mix toward calling; currently mail-reliant",
"Good Return per Call -- efficient, low effort / lead": "Efficient account — invest more senior deal-maker time; scale up",
"Low Health – investigate": "Manual review — sporadic out-of-the-norm stats with no single pattern; investigate holistically",
"Aggressive Client - Invest in Research": "Client pushing hard with thin supply; invest in research / expanding the TAM",
"Aggressive Client - Improve Contact Rate": "Lift contact rate; client wants more activity and they convert",
"Aggressive Client - high conversion from CC to Offer": "Strong converter — feed more volume; protect and scale",
"Funnel Conversion Soft (strong top-funnel, weak conversion)": "Good lead-gen, weak conversion — coach client on CC→visit→offer; reassess buy-box",
"Clean Process": "On track — maintain current approach",
"Clean Process - potential trend issue": "Healthy now, but outreach turning mail-heavy — watch for TAM exhaustion / declining approvals and reduced lead flow",
"High-Volume Project": "Keep the pedal down; focus DT on lead conversion and client on offer conversion",
"High-Volume Project - CC to Offer Conversion Low": "Encourage client to make offers and weed out the window shoppers",
};
const ATTR = {
[A_PROC]: { bg: "#FBF3E3", fg: "#8A5B08", bd: "#F0DCB4", dot: "#C9901C" },
[A_CLI]: { bg: "#F1EDFB", fg: "#5C43A8", bd: "#DDD3F4", dot: "#7A5BD0" },
[A_STR]: { bg: "#EAF6EF", fg: "#1B7A46", bd: "#CBE8D6", dot: "#2F9E58" },
[A_MIX]: { bg: "#F4F7FB", fg: "#5B6A7A", bd: "#DEE5EE", dot: "#8A97A8" },
};
// value formatting: baselines are stored in the metric's own native units, so
// ratio-style metrics are shown as percentages and the rest as plain numbers.
function fmtVal(v, unit) {
if (v == null || isNaN(Number(v))) return "—";
const n = Number(v);
if (unit === "%") return (n * 100).toFixed(n * 100 >= 10 ? 0 : 1) + "%";
if (unit === "d") return Math.round(n) + "d";
return Math.abs(n) >= 100 ? Math.round(n).toLocaleString() : n.toFixed(Math.abs(n) >= 10 ? 1 : 2);
}
function Tag({ spec, children }) {
return (
{spec.dot && }
{children}
);
}
function StandardsScreen({ user }) {
const [baselines, setBaselines] = useState(null);
const [playbook, setPlaybook] = useState([]);
const [err, setErr] = useState(null);
const [cohort, setCohort] = useState("Add-on");
const [openRule, setOpenRule] = useState(0);
useEffect(() => {
let live = true;
Promise.all([
window.VaultAPI.listHealthBaselines().catch(() => []),
window.VaultAPI.listHealthPlaybook ? window.VaultAPI.listHealthPlaybook().catch(() => []) : Promise.resolve([]),
]).then(([b, p]) => { if (!live) return; setBaselines(b || []); setPlaybook(p || []); })
.catch(e => { if (live) setErr(String(e && e.message || e)); });
return () => { live = false; };
}, []);
// playbook rows keyed by diagnosis, falling back to the Excel text
const actionFor = useMemo(() => {
const m = new Map();
(playbook || []).forEach(r => {
const k = r.diagnosis || r.rule || r.name;
const v = r.action || r.recommended_action || r.text;
if (k && v) m.set(String(k).trim(), String(v));
});
return name => m.get(name) || PLAYBOOK_FALLBACK[name] || "—";
}, [playbook]);
const cohorts = useMemo(() => {
const s = new Set((baselines || []).map(b => b.project_type).filter(Boolean));
const list = Array.from(s);
return list.length ? list : ["Add-on", "Platform"];
}, [baselines]);
const rows = useMemo(() => {
const byMetric = new Map();
(baselines || []).filter(b => b.project_type === cohort)
.forEach(b => byMetric.set(b.metric, b));
return METRICS.map(([key, label, desc, unit]) => {
const b = byMetric.get(key);
const avg = b ? Number(b.avg) : null, sd = b ? Number(b.sd) : null;
const has = b && avg != null && !isNaN(avg) && sd != null && !isNaN(sd);
return {
key, label, desc, unit, has,
n: b && b.n != null ? Number(b.n) : null,
avg, sd, lo: has ? avg - sd : null, hi: has ? avg + sd : null,
// geometry for the healthy-band bar: axis runs 0 .. mean + 2.2σ so the
// ±1σ band sits visually centred with headroom on both sides.
bar: has && (avg + 2.2 * sd) > 0 ? (() => {
const max = avg + 2.2 * sd, lo = Math.max(0, avg - sd), hi = avg + sd;
return { left: (lo / max) * 100, width: ((hi - lo) / max) * 100, mean: (avg / max) * 100 };
})() : null,
thin: b && b.n != null && Number(b.n) < 10,
flat: has && sd === 0,
};
});
}, [baselines, cohort]);
const stamp = useMemo(() => {
const ts = (baselines || []).map(b => b.computed_at).filter(Boolean).sort().pop();
if (!ts) return null;
const who = ((baselines || []).find(b => b.computed_at === ts) || {}).computed_by;
return String(ts).slice(0, 10) + (who ? " · " + who : "");
}, [baselines]);
const missing = rows.filter(r => !r.has).length;
return (
{stamp && (
BASELINES COMPUTED {stamp}
)}
{err && (
Could not load baselines: {err}
)}
{/* A */}
{(
A · Conversion Rate Standards
Live from health_baselines. Healthy = mean ±1σ; every z-score in the rule book is measured against these exact numbers.
{cohorts.map(c => (
))}
{baselines && missing > 0 && (
{missing} of {METRICS.length} metrics have no stored baseline for {cohort}. Those rows show a dash rather than a
guess — any rule that reads them scores z = 0 and stays silent. Run Recompute Baseline to fill them.
Cohort scope is the Scott module, split by project type, over a trailing 12-month window. The workbook this engine
was ported from used a single blended cohort of 52 retainer clients over client lifetime, so figures here are not
directly comparable to that workbook. A metric with N under 10 or an SD of 0 cannot produce a meaningful z-score.
)}
{/* B */}
{(
B · Rule Book
{RULES.length} diagnosis outcomes across {new Set(RULES.map(r => r[0])).size} rule slots in health-engine.js.
Conditions are the literal ported predicates. Attribution tags are proposed and awaiting your redline.