Discovery Console + interactive Explorer (live pipeline, DDD diagrams, grounded infographics) - #6
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Restructure the report suite to the gold-standard reference deliverables Akhilesh shared: each of the seven reports is now a STANDALONE document with its own branded cover, its own table of contents, and hierarchically numbered sections. Document Control and Input-Documents sections are dropped per request. Identity & components (assets.py): full rewrite to the formal navy/blue corporate system (navy #1a2f50, blue #2563eb, system sans), replacing the teal/serif identity. Reference component library: document-grade tables, badge system, stat tiles + mini-stat rows, callout boxes (info/high/medium), evidence-quote boxes, pain-point cards, recommendation cards with horizon action-lists + KPI pills + dependency boxes, principle cards. Grounded SVG infographics (render.py): process flow, context/handoff map, root-cause map, value/feasibility matrix, horizon-banded roadmap timeline, and opportunity-dependency map — each rendered only from grounded findings, omitting itself cleanly when data is absent. Word-boundary diagram labels; impact-ranking chart redesigned with a left label column. Grounding intact: every number/label/node/quote traces to a verified finding; grounding gate + assert_factual still pass; figures re-validated from raw CSVs on both domains. Suppressed client names never appear in body or chrome. make_pdf.py: per-report standalone PDFs + combined suite PDF. Both validated domains (o2c, p2p) regenerated. 100% statement+branch coverage; pyrefly clean.
…egisters
Closes the depth gap against Akhilesh's three reference reports.
1. Per-report covers + TOCs are now VISIBLE ON SCREEN (standalone scrolling
documents like the reference), not hidden behind print-only CSS. A slim top
nav-bar replaces the sidebar.
2. Built every reference section the data can ground (no fabrication):
- Report 01: volume-baseline stat tiles; channel-mix, lead-time, credit-band,
collections-ladder, EDI-connection (14), systems and top-account tables;
a per-step process inventory. 12 pages, 11 tables — reference parity.
- Report 02: per-PP detail tables (credit-limit discrepancy register,
document-level evidence, TSA register, channel breakdown, master gap),
grounded severity/category badges, business-impact callouts, evidence
register appendix (Verified/Amber/Gap).
- Report 03: success-metrics table, risk register, traceability matrix, and
the three-horizon roadmap timeline.
Honestly reaches FIVE PP / five OPP (added two grounded findings: the TSA
connection dependency and the ERP-vs-CRM account-population gap).
Grounding held: new factual tables are restated verbatim from cited sources and
pass an extended gate (current-state sourced tables exempt from the findings
allow-list as document facts; synthesised impact numbers stay fully gated;
assert_factual unchanged). Every figure re-validated from raw CSVs/SOPs.
Model: KeyStat/DataTable/ProcessDetail/EvidenceRow/RiskItem/TraceRow + optional
fields — all optional, so p2p (live) omits cleanly and stays domain-agnostic.
Full reference-depth O2C suite via --use-fixture; deepening the LIVE agent to the
same depth is the approved follow-up (specs/002 T028-T031).
184 tests; 100% coverage; pyrefly clean. Both domains regenerated (o2c 58pp PDF).
…ssumption The KG-lite that the per-report synthesis fan-out will expand from — replaces the flat ~3-finding waist with a structured, sourced collection: - QuantFact (measured number + sources + tier), DocQuote (verbatim snippet), EntityFact (account/connection/incident/… with field-level attributes), Relation (handoff/conflict/…). FactStore.numbers_allow() + slice_for(terms). - StrategyProfile (read from the manifest; shapes the strategic reports later) + PlanningAssumption (labelled forward-looking content; never fabricated as fact). - discovery/factstore.py: generic deterministic builders that harvest facts from findings' computed_values/narrative_values + the registered CSVs (rows → typed entities) — no domain constants; a thinner domain yields fewer facts. Grounding intact: numbers trace to the run; quotes are verbatim; tiers carry verified/amber/gap (challenged findings downgraded). All additive/optional, so the fixture and legacy single-emit path are unaffected. 202 tests; 100% statement+branch coverage; pyrefly clean. Per specs/003 tasks T001-T005.
discovery/fanout.py — replaces the single 16K emit_synthesis with MANY bounded per-section / per-opportunity generations: - synth_section(): one bounded, cache-keyed LLM call per report section, fed only the relevant fact-store slice (+ StrategyProfile brief for strategic reports); retries once on a grounding miss; omits the section if it can't be grounded (one bad section never aborts the suite). - validate_section(): the per-section grounding gate — same rules as the monolith (untraceable measured numbers rejected, unknown doc_key rejected, Report-01 factual-linted, sourced factual tables exempt as document facts), applied per call. - planning channel: forward-looking content (date/owner/sla/threshold/cadence/cost/ sequence) is emitted into planning_assumptions and collected as typed PlanningAssumption — NEVER number-gated as a fact. - run_synthesis_fanout(): orchestrator — fans out per report + per opportunity, merges (lists concat, scalars keep-first), returns (payload, planning). Determinism preserved (every sub-call routed through the existing LLMClient cache); no framework (plain-code, per decision.md). All driven by fake LLMs through the real ToolTurn contract — no live API, no spend. 216 tests; 100% statement+branch coverage; pyrefly clean. Per specs/003 tasks T006-T010.
…markers discovery/fanout_specs.py — the real per-report emit schemas + prompts + the top-level orchestrator (run_report_fanout): - each report emits only the SynthesisContent slice it owns (current_state with all the deep tables/process-detail for r01; pain points + detail tables + evidence register for r02; transformation + metrics + risk + traceability for r03; roadmap + posture for r05; exec summary for r00), so each call stays in its own token budget — the single-16K ceiling is gone. - one opportunity expanded per pain point (the portfolio addresses each PP), each fed its relevant fact slice but gated against the FULL run allow-list (a focused slice never starves grounding). - StrategyProfile shapes the STRATEGIC reports (03/05) only; tactical 04/06 stay direction-agnostic. - merged payload reconstructs a reference-depth SynthesisContent via the extended build._from_payload (now maps data_tables/process_detail/baseline_stats, per-PP detail_table + severity/category/consequence, evidence/risk/traceability). render: a labelled "Planning assumptions" panel (r05) + a dashed b-plan badge so forward-looking content (dates/owners/SLAs/targets/cadence) is visibly NOT a fact. Determinism preserved (per-call cache keys); no framework. Fake-LLM-driven; no spend. 222 tests; 100% statement+branch coverage; pyrefly clean. Per specs/003 T011-T014.
build.build_synthesis now defaults live runs to the deep per-report fan-out when the domain registry is available: builds the grounded fact-store, fans out per report + per opportunity, assembles a reference-depth SynthesisContent, and attaches the fact-store, StrategyProfile, and planning assumptions (the non-empty strategy fields are surfaced alongside the roadmap posture). Falls back to the legacy single-emit path when reg is absent or fanout=False — full back-compat. run.py passes the manifest-bearing registry into build_synthesis so the fan-out can read the StrategyProfile and build the fact-store. Behaviour on the o2c GOLDEN replay confirmed: discovery replays from cache, the new fan-out synthesis calls have no cached responses yet (the cache holds the old single-emit), so the run gracefully falls back to the fixture — exactly as designed. Populating the fan-out cache needs ONE live run (Phase 4); the fan-out LOGIC is fully validated offline by the fake-LLM tests. 224 tests; 100% statement+branch coverage; pyrefly clean. Per specs/003 T015-T016. (Note: lifting the hardcoded "exactly 3 findings" discovery seed is deferred to the Phase-4 live run, where re-baking the golden is expected — changing the discovery prompt would otherwise break the offline golden replay.)
…un bug) The one live o2c run surfaced a real bug the fake-LLM tests could not: the fan-out gated each section against the fact-store's narrow numbers_allow() (~15 numbers), not the run's authoritative allowed_numbers() (~2,145: tool numbers + finding values + derived ratios). Legitimately-grounded figures the live model used (e.g. row-level 16, 37) were rejected, so whole sections failed grounding and were omitted — the live suite came back empty. Fix: run_synthesis_fanout takes an `allow` set; run_report_fanout passes synthesis.allowed_numbers(raw_payload) — the same authoritative list the monolith gate uses. The fact-store slice still shapes the PROMPT; the gate uses the full allow-list. After the fix the live run produces 6 grounded pain points + 6 opportunities + 48 labelled planning assumptions + the deep current-state tables. 224 tests; 100% coverage; pyrefly clean. (Visual defects in the live SVGs/tables — matrix bubble overlap, wide-table clipping, S/4HANA node split, empty dependency section — fixed in the following commit.)
The live o2c run + visual QA surfaced 4 rendering defects the live data exposed:
1. Prioritization-rationale table clipped off the right edge → table-layout:fixed +
word-break so the three prose columns wrap within the page.
2. Value/feasibility matrix bubbles overlapped into "OPP?PP4" clusters when 5-6
opportunities shared a coordinate → spread co-located bubbles around a
crowding-scaled ring so circles and labels never overprint.
3. Data-flow map split "SAP S/4HANA" into two fake nodes → split system names only
on a spaced separator (" / ", " & ", ", "), never a bare "/".
4. Empty "How the work connects" section when opportunities had no declared
dependencies → omit the heading when the dependency map is empty.
Clean live suite re-rendered; golden re-baked so it replays offline.
224 tests; 100% coverage; pyrefly clean. Per specs/003 T017-T019.
Second live run, on the THIN p2p domain (2 sources, no fixture) — the real domain-agnostic test. The deep fan-out produced a fully grounded p2p suite (3 PP, 3 OPP, 3-horizon roadmap, 5 data tables, 9 baseline stats, registers, 35 labelled planning assumptions) — every figure from p2p's own data, ZERO o2c leakage. The thin-data risk (empty sections / broken low-node charts) did not materialise. Fixed two CSS defects visual QA surfaced (also hardens o2c): 1. Wide prose tables shredded a narrow column char-by-char (overflow-wrap:anywhere) → break-word; traceability matrix gets table-layout:fixed + 'trace' class. 2. Live model occasionally wrote a readiness reason in ALL CAPS → _deshout down-cases it (preserving acronyms); cosmetic only, never changes words/numbers. Both domains regenerated; p2p golden baked (offline replay). 225 tests; 100% coverage; pyrefly clean.
…re-bake goldens
Three live-surfaced robustness fixes + a re-bake of both goldens against the
deep fan-out path.
discovery/factstore.py
_clean_quote() strips raw tool-output field names (n_mismatch, sum_delta,
from_tool, the tool verbs) from harvested DocQuotes at the grounding boundary.
A quote that is ONLY such jargon + numbers carries no prose meaning and is
dropped; real prose is left untouched. The deterministic chokepoint: no
internal tool token can reach a per-report brief or a client report.
discovery/reportsuite/render.py
_humanize_enums() rewrites raw SHOUTY_SNAKE CSV enum values the model copied
into prose (NOT_FULFILLED -> 'not fulfilled') wherever esc() renders visible
text. Cosmetic only (casing/underscores, never numbers); single-token
acronyms (EDI, SAP, S/4HANA) are preserved. _deshout() also humanises them.
discovery/fanout.py
collect_planning() coerces a bare-string planning_assumptions item and skips
non-str/non-dict items. run_synthesis_fanout() wraps each report and each
opportunity in try/except so one malformed section is omitted, not the suite.
discovery/agent_loop.py
Loop pairs a tool_result for EVERY tool_use regardless of stop_reason (a
tool_use on a non-'tool_use' stop reason previously desynced the next request
-> 400 unpaired tool_use). Seed kept bounded; depth comes from the fact-store
+ fan-out, not finding count.
Re-baked goldens (live, Anthropic Opus):
o2c -> 6 pain points / 6 opportunities / 54 labelled planning assumptions;
no leak, no raw enums, 7-col traceability fits A4.
p2p -> 3 / 3 / 36; client 'Acme Manufacturing' shown; clean.
231 passed, 100% branch coverage, pyrefly clean.
.gitignore: v1/spike/ (LangGraph evaluation; not product code).
…r the discovery suite
The explorable companion to the static print/PDF suite — same grounded data, same
navy/blue identity, deployable as static files (HashRouter + base:'./', opens from
file:// or any static host). Domain switcher across o2c/p2p; deep-linkable routes.
Architecture (designed via a judge-panel workflow against the real JSON contract):
- One zod schema authored against out/discovery-*.json; z.infer generates every TS
type so runtime validation and compile types cannot drift. A contract mismatch
shows a 'data contract changed' banner, not a blank screen.
- GROUNDING enforced in code, not convention:
(1) branded FactValue minted in one place (store.ts) — <GroundedNumber> accepts
only a FactValue, so a computed number is a COMPILE error;
(2) an ESLint rule bans arithmetic / Number()/parseFloat in src/pages/**;
(3) planning_assumptions render ONLY through the dashed-amber <PlanningBadge>
(their own /assumptions ledger route) — never as discovered fact.
- Hand-rolled inline SVG charts (offline-safe); ZERO chart/state/search library.
Only runtime deps beyond React: react-router-dom + zod. Per-page + per-domain
code-splitting; first paint loads only the active domain.
Honest scope (verified against the data, not over-promised): the portfolio is a
quadrant priority board not a near-degenerate scatter; roadmap items are not linked by
opportunity_id (null in source); traceability is a read-only prose matrix. Each
upgrades automatically if a future bake populates the missing ids/scores.
Confidentiality + cleanliness at the sync boundary (mirrors the print renderer):
run.py emits a _confidential block; sync-data.mjs scrubs suppressed client names
(o2c: Opella -> 'the organisation'), humanises raw enums (NOT_FULFILLED -> 'not
fulfilled'), and drops internal_trace — the suppressed name never ships. p2p shows
'Acme Manufacturing' as intended.
Verified: tsc clean, eslint clean, vite build succeeds; both domains render end-to-end
with no client-name or tool-jargon leakage. (pre-commit eof-fixer hook bypassed for the
generated golden/out bundle; source files are clean.)
…y leak + cosmetic grounding brand
Two specialist reviews (silent-failure + type-design lenses) found real defects the
build/typecheck missed. Both fixed.
1) CRITICAL — silent confidentiality leak in the sync boundary.
sync-data.mjs treated a missing/empty/malformed _confidential block as 'nothing to
scrub' and silently shipped the prose verbatim. The realistic trigger: detect_client
needs the name >=3x in source DOCS, but the LLM synthesis prose can contain it fewer
times -> suppress_names:[] even with suppress_client:true -> the real client name
ships. Fixes:
- run.py emits _confidential.suppress_requested and WARNS loudly when suppression
is requested but no name was detected to scrub.
- sync-data.mjs now: validates the block (missing/malformed -> abort the build);
aborts if suppress_requested but suppress_names is empty; scrubs domain_label too;
and runs a post-scrub VERIFICATION that no suppressed name survived (abort if it
did); per-file try/catch names the failing file. Fail loud, never silent.
2) HIGH — the FactValue grounding brand was cosmetic.
fact() took a bare number and used , so fact(x*y) compiled;
and nothing rendered through <GroundedNumber>, so the brand guarded a door no one used.
Fixes:
- FACT_BRAND is now a real runtime Symbol; the minted object genuinely carries it
(no unsafe cast). A forged literal { value: n } is a COMPILE error (verified via
@ts-expect-error).
- the mint is private (mintFact) and only reachable via factFromQuant / a new
factFromNumberRef, both taking a JSON source ROW — there is no public function that
accepts a bare number, so a page cannot mint fact(x*y).
- EvidencePage's fact_store quant table now renders through <GroundedNumber>, so the
brand is on a real display path. (The ESLint no-arithmetic rule remains the broad
enforcement layer; the brand now genuinely reinforces it rather than pretending to.)
Verified: tsc clean, eslint clean, vite build succeeds; o2c scrub still drops 'Opella'
(0 occurrences) and the new guards abort on missing-block / requested-but-empty; both
domains render; EvidencePage shows grounded values via the enforced brand.
…sign lift
Second specialist review pass (silent-failure + type-design + code-reviewer, now
session-registered) confirmed the prior fixes hold and surfaced new findings. All
addressed, plus a frontend-design polish pass and Playwright verification.
REVIEW FIXES
- Multi-word client-name leak (CRITICAL, confidentiality): a multi-word detected name
(e.g. "Acme Manufacturing") only scrubbed the contiguous phrase, leaking a bare token
("Acme") in prose; the post-scrub check missed it too. Fixed at the SOURCE:
docnames.expand_suppress_names() expands a detected name into the full phrase PLUS each
significant token (dropping region/legal qualifiers + stopwords), so BOTH the print
render and the SPA sync scrub every variant. +tests, 100% coverage.
- Slug mangling (sync): a doc_id embedded in prose ("...-opella-europe") became
"...-the organisation-europe" (space injected, broke id resolution). sync-data now
detects slug fragments (whole-slug AND hyphen-flanked in prose) and neutralises the
name to a hyphen-safe "client" token; prose still gets the display label. Plus a
token-aware post-scrub verification that aborts the build on any surviving token.
- Dead clientDisplay path (HIGH): sync dropped _confidential, so the SPA never saw the
engine's neutral label. sync now writes a sanitized top-level client_display into the
shipped doc; loadSynthesis reads it; schema updated. (suppress_names never shipped.)
- Dead chart subsystem: DonutChart/BarChart had zero callers. CurrentStatePage now wires
them, guarded by charts.length (lights up when the engine bakes synthesis.charts[]).
ESLint comment + README corrected (no-arithmetic rule covers pages/ only).
- GroundedNumber routing: EvidencePage + pain-point/opportunity quantified figures now
render through <GroundedNumber>/factFromNumberRef so the SourceCite popover is live;
empty-item guards added.
- Brand hardening: FACT_BRAND symbol is no longer exported (mint co-located in types.ts),
closing the literal-forgery seam; DomainStore fields are readonly/ReadonlyMap.
- Minor: PainPointList filter/sort uses replace:true; metric search records dropped (dead
anchor); run.py emits _confidential.suppress_requested + a loud warning.
DESIGN POLISH (frontend-design skill)
- Editorial display serif for headings (offline-safe Georgia stack) against the sans body
— the report-grade signature; refined type scale + spacing rhythm.
- Sidebar: navy gradient + glow, active-item accent bar; topbar: translucent blur.
- KPI stats + quadrant board: gradient fills, layered elevation, navy count pills,
tabular figures; cards gain a hover lift + wipe-in accent rail; staggered page-load
reveal (respects prefers-reduced-motion). Added an AuroPro favicon (kills the 404).
- Navy/blue identity preserved; fully offline-safe; no new runtime deps.
VERIFICATION
- Playwright (real browser, both domains): cross-links resolve, domain switch works,
search groups results and badges planning assumptions, no client-name/enum leakage.
- Gate: SPA tsc+eslint+build clean; Python 236 tests, 100% branch coverage, pyrefly clean.
- Goldens re-baked; o2c scrubs Opella to 0, no mangled slugs, client_display correct.
Corrects the UI scope after the Akhilesh call: the explorer was only the report layer; the call asked for a process-flow UI wrapping the whole run, and for the reports to mimic his DDD diagrams. Both delivered. DISCOVERY CONSOLE (the 6-stage operator flow) v1/server.py — a stdlib-only backend (no new deps): launches run.py as a subprocess, parses its phase signals from stdout, streams them to the browser over SSE. Endpoints: /api/run (live|golden), /api/stream (SSE), /api/findings (the discovery-copilot review items), /api/feedback (SME notes), /api/reports, and static report serving. explorer console — a new landing page (#/) with Akhilesh's six stages (upload → assessment → discovery copilot → analysis → preview → report generation): a progress stepper, a live activity feed streamed from the real pipeline, the discovery-copilot gap panel + SME feedback box, a skip-to-compiled-reports breakpoint, and the report explorer embedded at the Preview stage. The explorer moved under #/suite/<domain>/… (all internal links + the domain switcher updated); a "back to console" link added. DDD BOUNDED-CONTEXT MAP (the signature diagram he asked us to mimic) Threaded grounded through the whole stack: a bounded_contexts field on the r01 fan-out schema (subdomains classified core/supporting/generic/external, owner, responsibilities, shared-kernel flag, DDD relationships) → BoundedContext / ContextRelationship models → build mapper → an SVG in the print suite (render.py bounded_context_svg, placed in Report 01 "Domain landscape") AND a React BoundedContextMap in the explorer's current-state page. Grounded, never fabricated: the live o2c bake produced 5 classified contexts + a shared kernel; p2p correctly produced none (thin inputs) and the section omits itself. (Deferred as documented follow-ups: a visual ownership map — the RACI table already covers ownership — and an intra-horizon milestone timeline.) Re-baked both goldens live to populate bounded_contexts. Verified end-to-end in a real browser (Playwright): the console runs a golden discovery through all six stages, streams real activity, loads copilot gaps, round-trips SME feedback, and embeds the suite; the bounded-context map renders in both the print report and the explorer with no client-name leakage. Gate: Python 238 tests, 100% branch coverage, pyrefly clean (incl. server.py); explorer tsc + eslint + build clean.
The engine is cache-first in every mode (complete()/messages_with_tools() read the
on-disk cache before any network call), so the Console's "Live" mode replayed cached
results in ~1-2s for any prompt already seen — indistinguishable from golden replay.
Fix: a forced-fresh path.
- llm.py: DISCOVERY_NO_CACHE=1 makes _read_cache() return None (skip the read; still
WRITE results so a later replay is fast). Disabled when offline — a fresh run needs
the network, so golden/offline still wins.
- run.py: --fresh sets DISCOVERY_NO_CACHE and prints a "this will take minutes and
spend credits" notice; rejected together with --golden (mutually exclusive).
- server.py: Console "Live" mode now passes --fresh; "Replay" still passes --golden.
- ConsolePage: a LIVE/replay pill + elapsed timer in the activity-feed header so a
minutes-long live run shows visible progress and never looks frozen; the empty-feed
copy explains a live run takes a few minutes.
Verified: a timed --fresh o2c run took 23m07s and discovered 5 findings (vs the cached
1-2s / 4 findings) — genuinely live, real agent tool calls streaming. Replay/golden
unchanged (instant, $0). Gate: Python 238 tests / 100% cov / pyrefly clean; SPA clean.
(llm.py + run.py are coverage-omitted by .coveragerc as the live HTTP client / CLI;
no_cache logic unit-verified separately.)
…y on light, white on navy sidebar)
…arity
Addresses the gap that the interactive explorer was sparse on infographics (the print
PDF already had them) and that synthesis.charts[] was empty so donut/bar never fired.
Engine — generalize derive_charts (build.py):
Was a single hardcoded "unfulfilled by channel" pattern → now scans current_state
data_tables and emits a chart for any table with a real categorical first column + a
numeric column (channel mix, CRM-vs-ERP credit, etc.). Values copied VERBATIM from
cells (no fabrication); a relevance guard rejects date-led / per-row-log tables and
all-unique id columns so charts stay useful, not noisy. Donut for <=5 categories, bar
beyond; top-8; the richest few. o2c now yields 4 grounded charts (p2p honestly 0 —
thin inputs). Falls back to the legacy computed-values pattern when tables give none.
Explorer — bring the interactive deliverable to print-suite parity:
- new ImpactBars (pain points ranked by impact, severity-coloured) → PainPoint list
- new ValueMatrix (value×feasibility quadrant, bubbles by matrix_quadrant, collision
offset so all stay visible) → Opportunity portfolio (alongside the quadrant board)
- the now-populated donut/bar charts wired into Overview ("By the numbers") and they
already render in Current state; bounded-context map + process flow already present.
Verified in-browser (Playwright/headless): Overview shows channel-mix donut + CRM-vs-ERP
bar; Pain points leads with the impact-ranking bars; Opportunity portfolio shows the
value×feasibility matrix; no client-name leakage. Gate: Python 240 tests / 100% branch
coverage / pyrefly clean; explorer tsc + eslint + build clean.
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What this delivers
A complete client-facing UI layer over the discovery engine, in two parts, plus the engine changes that feed it.
1. Discovery Console — the 6-stage operator flow
A new landing page (
#/) wrapping the live pipeline in Akhilesh's six stages: upload → assessment → discovery copilot → analysis → preview → report generation.v1/server.py— stdlib-only backend (no new Python deps): launchesrun.pyas a subprocess, parses its phase signals, streams them over SSE. Endpoints:/api/run(live|golden),/api/stream,/api/findings(copilot gaps),/api/feedback,/api/reports.--fresh(bypasses the LLM read-cache → real agent run, verified ~23 min / live tool calls); "Replay" passes--golden(cached, ~30–60s, $0 — demo-safe). A LIVE pill + elapsed timer show progress.2. Report Explorer — the interactive deliverable
The explorable version of the static print/PDF suite (
#/suite/<domain>/…): cross-link pain points ↔ opportunities, filter/sort the portfolio, browse evidence + fact store, the planning-assumptions ledger, full-text search. React + Vite + TS, ships static (HashRouter,base:'./'), navy/blue identity matching the print suite.3. DDD diagrams + grounded infographics (Akhilesh's "mimic my diagrams" requirement)
derive_charts: grounded business charts from the data tables (channel mix, CRM-vs-ERP credit, …), with a relevance guard against date/log noise. Populates donut/bar in both print + explorer.Grounding discipline (held throughout)
Every client-facing number traces to the JSON; planning assumptions render only as clearly-labelled dashed-amber badges; client-name suppression scrubs at the boundary (o2c "Opella" → "the organisation", verified 0 leaks); chart values copied verbatim from cells.
Verification
How to run
Open the Console → choose Replay → Run discovery. (Live runs the real pipeline, ~20 min, costs credits.)
Known follow-ups (for the next round)