The Spectral Brand Audit Toolkit
Seven structured prompts that turn any large language model into an SBT analyst. Each module accepts a brand name and produces a standardized YAML report. The full pipeline compresses a multi-week consulting engagement into a single analytical session.
How It Works
Copy a prompt module from GitHub. Paste it into any capable LLM (Claude, GPT-4, Gemini). Specify your brand. The model produces structured YAML output matching the corresponding template. Run all seven modules sequentially for a complete spectral audit.
The pipeline has been demonstrated across five brands (Hermès, Tesla, IKEA, Patagonia, Erewhon) and cross-model replicated with identical structural findings between Claude and Gemini. All five brand profiles pass the mathematical validation layer — no metric violations, no metameric collisions, no trajectory risk flags.
Each complete audit produces two output layers. The L1 spectral profile is the full analytical tensor: eight dimension scores per observer cohort, emission weights, tolerance thresholds, prior states, and cloud formation modes — machine-readable, AI-queryable, lossless. The L2 rendered summaries are human-readable projections: coherence type label, overall grade, narrative diagnosis. The grade reflects disruption resilience architecture, not coherence quality. Run all seven modules sequentially to get both layers.
Seven Modules
Brand Decomposition
Decompose any brand into a structured signal inventory across all eight dimensions. Each signal is typed by emission source, tagged as designed or ambient, and assessed for strength and reach.
Observer Mapping
Define 3-6 observer cohorts with formal spectral profiles: sensitivity spectrum, dimension weights, tolerances, priors, and identity gate configuration. Perceptual groupings, not demographic segments.
Cloud Prediction
Predict how each observer cohort will cluster the brand's signals into perception clouds. Each cloud has a valence (positive, negative, ambivalent), confidence score, and formation mode (standard, mediated, stalled).
Coherence Audit
Score the brand on seven structural metrics: coverage, gate permeability, cloud coherence, signal strength, re-collapse resistance, emission efficiency, and designed/ambient ratio. Produces a coherence type diagnosis.
Emission Strategy
Design a dimensional emission strategy based on audit findings. Prioritize which dimensions to amplify, reduce, or restructure. Includes action plan with timeline and expected cohort response.
Re-collapse Simulation
Stress-test the brand under disruption scenarios: PR crisis, competitor entry, founder controversy, market shift. Model how each cohort's conviction re-collapses and where the structural vulnerabilities lie.
Resource Allocation
Compute optimal dimensional investment allocation based on alignment gap between founder/operator investment profile and target cohort value profile. Diagnoses over-investment, under-investment, and blind spots across all eight dimensions.
Validation Layer
LLM outputs are probabilistic. The validation layer makes them verifiable. A Python module enforces mathematical bounds from the R1-R7 research papers as runtime constraints on every spectral profile the toolkit produces. Seven validators check metric axioms, metamerism conditions, cohort boundaries, channel capacity limits, trajectory convergence (including per-dimension velocity, direction, acceleration, and time-to-absorption estimates with conformal prediction bands providing calibrated uncertainty), diffusion dynamics, and resource allocation optimality. If an analysis violates a proven bound, the validator rejects it with a specific diagnostic — before the output reaches a decision-maker.
Supporting Resources
- Atom Taxonomy — machine-readable 8-dimension taxonomy with sub-types, observer template, encounter bundle types
- Framework Specification — complete SBT v3.1 with all mechanisms, discoveries, and metrics
- Glossary — all SBT terms with definitions, cross-references, and traditional-concept mappings
- Framework Reference — established frameworks used per module (ISO 20671, SWOT, RACE, PESTEL)
- Brand Code — executable brand identity specification: spectral palette, particle system source, AI-readable prompt, structured brand profile
Related
Understand the framework behind the toolkit at the theory page. See results from real brands in the case studies. All terms used in the prompts are defined in the glossary.