The 6D Foraging Methodology applied to the system it built. 200 cases across 148 sectors — from SVB ($209B collapse) to bakeries ($500K revenue), bee colonies (100 million years of evolution) to AI-generated code. 681 cross-references. 50+ FETCH twins across unrelated domains. A structured evidence base where cross-reference density increased from 0.0 to 4.5 per case as the library compounded. The framework examines itself with the same rigor it applies to everything else.
A case library is a database at one case. It is a reference at ten cases. At 200 cases across 148 sectors, it becomes something else: a compound intelligence system where each new case activates connections the previous 199 did not contain. The cross-references are not links. They are structural evidence that the same six dimensions produce consistent, scorable cascades whether the entity is a $209 billion bank, a coral reef, or an AI coding tool.[1]
The evidence for this claim is the library itself — fully auditable. Every dimension score is traceable to cited sources. Every FETCH score is calculated from a published formula. Every cascade chain maps a verifiable propagation path. The structured index (index.json) contains all 200 cases with their scores, chains, sectors, and cross-references in machine-readable format, enabling the kind of analysis this case performs.[2]
UC-038 analysed a novel phenomenon: a framework examining itself. FETCH 2,405. Methodology was young. Cross-references were sparse.
The phenomenon is no longer novel. The system has matured. 681 cross-references. 148 sectors. Calibration improving with volume. The compound effect is the story.
The structural proof of compound intelligence is measurable. Early cases (UC-002 through UC-050) carry an average of 0.0 cross-references each. Later cases (UC-150 through UC-199) carry 4.5. The library is not growing linearly. It is growing connectively — each new case discovers structural relationships to cases already published, relationships that no single analysis planned for.[2]
The library begins with a single diagnostic case. Single-file HTML. Inline CSS. Cloudflare Workers deploy pipeline. The format that will scale to 200 is established on day one.
D6 Infrastructure EstablishedFirst month of production. Banking, tech, macro, retail, automotive, healthcare. Six sectors in the first 23 cases. The FETCH formula is being calibrated with each new case.
D5 Calibration PhaseThe framework examines itself for the first time at 37 cases. FETCH 2,405. A novel analytical event: a methodology scoring its own compound effects. Amplifying (green). This case is its structural successor.
D5 Meta-Analysis CapabilityThe Escape Hatch introduces forward-looking analysis with WATCH triggers and SURFACE review dates. Fourth case type added. The framework gains temporal depth — it can now look forward, not just backward.
D5 Temporal ExtensionThe library crosses triple digits. FETCH twins begin appearing — cases in unrelated sectors scoring within 2–5 points of each other, confirming calibration consistency. The index transitions from HTML to structured JSON.
D5 + D6 Scale MilestoneSMB AI adoption case becomes a cross-reference anchor for the software engineering cluster (UC-082, UC-083, UC-084) and later for the vibe coding pair (UC-198, UC-199). Cases published weeks apart discover structural connections.
Cross-Reference DensificationSix cases in one day. Bee colony collapse, wolf reintroduction, coral bleaching, salmon nutrient cycles, leafcutter ants, keystone species. The same six dimensions that scored SVB now score ecosystems 100 million years old. Scale independence proven.
D5 Scale IndependenceThe Vibe Coding Cascade (diagnostic, FETCH 2,860) and The Human in the Loop (amplifying, FETCH 2,234). Same data, two sides. The library’s first deliberate complementary pair heading into UC-200.
Structural Complement200 cases. 148 sectors. 681 cross-references. The framework examines the compound system it built. Same six dimensions. Same scoring. Same rigor.
D5 + D6 Compound MilestoneThe library’s structural properties are auditable from index.json. These are not interpretive claims. They are measurements of the system as it exists at 200 cases.
Unique sectors from banking and macro to ecology, pro athletes, SMB operations, AI safety, trades, and weather data. No sector represented more than 6 times. The framework is domain-agnostic by evidence, not assertion.
66 diagnostic (33%), 60 at-risk (30%), 43 amplifying (22%), 29 prognostic (15%). The library is not skewed toward negative analysis. Amplifying and prognostic cases represent 37% of the total.
Mean 1,847. Distribution: 23 cases below 1,000 (QUEUE band), 68 in the 1,000–1,499 band, 24 in 1,500–1,999, 31 in 2,000–2,499, 24 in 2,500–2,999, 21 above 3,000. A bell curve centred on the EXECUTE threshold.
161 of 198 cases activate all six dimensions. 20 activate five. The full cascade — where an event propagates across every dimension — is the norm, not the exception. This validates the premise that cascades are multi-dimensional by nature.
Pairs of cases in unrelated sectors scoring within 5 points: UC-104 Intel (3,210) and UC-111 Deere (3,212). UC-192 Colony Collapse (1,811) and UC-045 (1,812). Structural dynamics match across domains the author did not plan.
Origin dimension frequency: D3 (62), D6 (45), D5 (44), D2 (42), D4 (38), D1 (36). No single dimension dominates as cascade origin. The framework is not biased toward financial, operational, or quality analysis.
180 unique cascade chains across 198 cases. Almost every case has a distinct propagation path — the same six dimensions, the same scoring rubrics, producing structural fingerprints as unique as the entities they analyse.
— Structural analysis, uc-000/index.json[2]
The library is the entity. The cascade originates from Quality (D5) and Operational (D6) simultaneously — the methodology itself and the infrastructure that deploys it. These flow through Revenue (D3, compound strategic value), Customer (D1, discoverability and evidence access), Employee (D2, reusable analytical framework), and Regulatory (D4, auditable transparency).
| Dimension | Score | Amplifying Evidence |
|---|---|---|
| Quality (D5)Origin — 68 | The same six dimensions, same scoring rubrics, same FETCH formula produce consistent results from banking to ecology. 50+ FETCH twins confirm calibration. 180 unique cascade chains emerge from 6 dimensions. Chirp range 21.2–79.3, confidence range 0.33–0.95 — both appropriately distributed. The alignment pass (formula recalculation across all cases) is evidence of auditable, self-correcting methodology.[1][2] Methodology Consistency | |
| Operational (D6)Origin — 65 | Single-file HTML with inline CSS. Cloudflare Workers with KV routing. deploy-case.sh one-command deployment. Structured index.json enabling machine-readable access. 23 cases in February, 175 in March — the pipeline scaled without architectural changes. The format decision on day one (UC-002) held through UC-200.[2]Infrastructure Velocity | |
| Revenue (D3)L1 — 52 | 52 | Compound strategic value. 681 cross-references create connections no single case contains. Each new case enriches existing cases by activating new structural relationships. Cross-reference density increased from 0.0 to 4.5 per case — the library is compounding, not just accumulating. The network effect is measurable: later cases are structurally richer than earlier ones.[2] Compound Intelligence |
| Customer (D1)L1 — 48 | 48 | Machine-readable structured index enables AI discoverability and programmatic access. Each case is a standalone HTML page with no external dependencies — viewable, shareable, archivable. The structured data layer (index.json) sits alongside the human-readable layer (HTML pages), serving both audiences simultaneously.[2] Dual-Layer Access |
| Employee (D2)L2 — 45 | 45 | The framework is a reusable analytical instrument. The same skill file, reference document, and scoring rubrics that produced UC-002 produced UC-200. The methodology transfers across analysts, contexts, and AI tools. Production evidence: cases generated through Claude Desktop, Claude Code, and Claude.ai with consistent structural output.[1] Transferable Framework |
| Regulatory (D4)L2 — 40 | 40 | Every score is traceable to cited sources. Every FETCH is calculated from a published formula. The alignment pass recalculated all scores against the formula, correcting drift. The methodology publishes its own scoring rubrics, thresholds, and decision logic. Transparency is structural, not performative.[1][3] Auditable Transparency |
-- The Library: Methodology Amplifying (Meta-Case)
-- Sense -> Analyze -> Measure -> Decide -> Act
FORAGE compound_case_library
WHERE cases_published >= 200
AND unique_sectors >= 140
AND cross_reference_count > 600
AND fetch_twin_count > 40
AND structured_index_available = true
AND methodology_consistency_across_domains = true
ACROSS D5, D6, D3, D1, D2, D4
DEPTH 3
SURFACE the_library
DIVE INTO compound_intelligence
WHEN cross_ref_density_increasing = true -- 0.0 early, 4.5 late
AND fetch_twins_emerging = true -- 50+ pairs across unrelated sectors
AND cascade_chains_unique > 170 -- 180 distinct propagation paths
AND scale_independence_proven = true -- SVB to bee colonies to bakeries
TRACE the_library -- D5+D6 -> D3+D1 -> D2+D4
EMIT compound_system_analysis
DRIFT the_library
METHODOLOGY 85 -- structured scoring, consistent formatting, machine-readable index
PERFORMANCE 35 -- not every case achieves its ceiling; early cases lack cross-refs
FETCH the_library
THRESHOLD 1000
ON EXECUTE CHIRP critical "6/6 dimensions, compound intelligence system, framework examining itself"
SURFACE analysis AS jsonRuntime: @stratiqx/cal-runtime · Spec: cal.cormorantforaging.dev · DOI: 10.5281/zenodo.18905193
The same six dimensions score a $209 billion bank failure (UC-039), a $500K bakery (UC-125), a 100-million-year-old bee colony (UC-192), and an AI-generated code vulnerability wave (UC-198). The scoring rubrics do not change. The formula does not change. The dimensions do not change. The cascade maps are unique, but the instrument is constant. 148 sectors is the proof that the framework is domain-agnostic by evidence, not by assertion.
50+ case pairs across unrelated sectors score within 5 points of each other. UC-104 (Intel, semiconductor) at 3,210 and UC-111 (Deere, agriculture-industrial) at 3,212. UC-192 (Colony Collapse, ecology) at 1,811 and UC-045 (1,812). These are not planned calibrations. They are structural fingerprints — evidence that entities facing comparable cascade dynamics produce comparable scores, regardless of sector. The twins validate the formula more rigorously than any single case could.
681 cross-references across 200 cases, increasing from 0.0 per case (early) to 4.5 per case (later). Each cross-reference is a structural claim: “this cascade shares a mechanism with that cascade.” When UC-198 (Vibe Coding Cascade) references UC-082 (Guardrail Gap), it is not a hyperlink. It is a structural assertion that the same D5 origin produces the same propagation pattern three weeks later with more evidence. The network of references contains analytical intelligence that no individual case holds.
UC-200 applies the same scoring, the same formula, the same editorial standards as every other case. The library is the entity. It gets the same treatment as SVB, the NFL, or coral reefs. No softer, no harder. The FETCH score (2,252) sits correctly below UC-038 (2,405) because maturity is less volatile than novelty. A framework that applies its own rigor to itself — and accepts the result — is a framework that earns structural trust.
One conversation. We’ll tell you if the six-dimensional view adds something new — or confirm your current tools have it covered.