demerzel-bs-decode

name	demerzel-bs-decode
description	Decode BS — run text through structural, content, and rhetorical analysis to produce a FuzzyEnum<BsLevel> score with tetravalent mapping

Demerzel BS Decoder

Analyze text for bullshit density using the BS detection grammar (grammars/gov-bs-generators.ebnf). Produces a quantified BS score, per-test breakdowns, rhetorical device inventory, tetravalent mapping, and a clear-speech rewrite when warranted.

Usage

/demerzel bs-decode [text or URL] /demerzel bs-decode --file [path] — decode a file /demerzel bs-decode --url [url] — fetch and decode a URL /demerzel bs-decode --self [artifact-path] — self-check a Demerzel governance artifact

Pipeline

INPUT
  │
  ▼
STRUCTURAL ANALYSIS
  ├─ Specificity Test    → FuzzyEnum<Low|Medium|High>
  ├─ Falsifiability Test → FuzzyEnum<Zero|Low|Medium|High>
  └─ Commitment Test     → FuzzyEnum<Low|Medium|High>
  │
  ▼
CONTENT ANALYSIS
  ├─ Density Test        → FuzzyEnum<Fluff|Mixed|Substance>
  ├─ Factual Density     → FuzzyEnum<None|Sparse|Dense>
  └─ Actionability Test  → FuzzyEnum<None|Vague|Actionable>
  │
  ▼
RHETORICAL ANALYSIS
  ├─ Device Scan         → List of devices from gov-bs-generators.ebnf §11
  └─ Evasion Scan        → List of tactics from gov-bs-generators.ebnf §12
  │
  ▼
SCORING
  │  Weighted combination of all tests
  │  Weights: specificity 0.20, falsifiability 0.15, commitment 0.20,
  │           content_density 0.15, factual_density 0.15, actionability 0.15
  │
  ▼
CLASSIFICATION → FuzzyEnum<BsLevel>
  │  Clear    (score > 0.8)  — real content
  │  Mild     (score 0.6-0.8) — some fluff, substance present
  │  Moderate (score 0.4-0.6) — more style than substance
  │  Serious  (score 0.2-0.4) — almost entirely empty rhetoric
  │  Pure     (score < 0.2)  — could be randomly generated
  │
  ▼
TETRAVALENT MAPPING
  │  Clear/Mild   → T (verified real content)
  │  Moderate     → U (substance unclear, investigate)
  │  Serious/Pure → C (contradictory — sounds meaningful, says nothing)
  │
  ▼
REWRITE (if score ≤ Moderate)
  │  Generate clear-speech alternative using antidote pattern:
  │  claim + evidence + specifics + commitment
  │
  ▼
OUTPUT

Structural Analysis Details

Specificity Test

Replace the subject with any other subject. If the sentence still makes sense, specificity is LOW.

Result	Criterion
High (1.0)	Statement only applies to the specific subject named
Medium (0.5)	Partially specific — some generic, some concrete
Low (0.0)	Could apply to any company, product, or person

Falsifiability Test

Ask: "What evidence would DISPROVE this claim?" If no evidence could disprove it, falsifiability is ZERO.

Result	Criterion
High (1.0)	Clear criteria for disproof exist
Medium (0.5)	Partially testable — some aspects verifiable
Low (0.2)	Very difficult to test
Zero (0.0)	Unfalsifiable — no evidence could disprove it

Commitment Test

Ask: "WHO will do WHAT by WHEN?" Missing any element reduces the score.

Result	Criterion
High (1.0)	All three present: who, what, when
Medium (0.5)	Two of three present
Low (0.0)	Vague aspiration with no specifics

Content Analysis Details

Density Test

Remove all adjectives, adverbs, and buzzwords. Ratio of remaining content words to total words.

Factual Density

Count verifiable facts per sentence: numbers, dates, names, measurements, citations.

Actionability Test

Could someone act on this statement without asking clarifying questions?

Rhetorical Analysis Details

Scan for devices defined in grammars/gov-bs-generators.ebnf:

Devices (§11): weasel_words, false_precision, appeal_to_authority, false_dichotomy, circular_reasoning, loaded_language, appeal_to_novelty, appeal_to_tradition, bandwagon, thought_terminating_cliche, strategic_ambiguity

Evasion Tactics (§12): deflection, flooding, reframing, credentialism, complexity_shield, future_promise, whataboutism

Report: devices per sentence (rhetorical density) and specific instances found.

Domain Detection

Match input against BS domain productions in the grammar:

Domain	Grammar Section
Consulting	§1: consulting_bs
AI/Tech	§2: ai_bs
Academic	§3: academic_bs
Motivational	§4: motivational_bs
Governance	§5: governance_bs
Corporate	§6: corporate_bs
Startup/VC	§7: startup_bs
Political	§8: political_bs
HR/People	§9: hr_bs
Marketing	§10: marketing_bs

Self-Check Mode

/demerzel bs-decode --self runs the decoder against Demerzel's own governance artifacts. This is critical — the grammar itself warns:

Self-check: Is Demerzel creating governance artifacts to govern governance artifacts that govern governance? If yes, this IS the BS.

FuzzyEnum Output

All test results are FuzzyEnum values, not discrete. A statement might be:

specificity: { High: 0.3, Medium: 0.6, Low: 0.1 }

This means 60% medium specificity, 30% high, 10% low. The weighted combination produces a FuzzyEnum with membership across all five levels.

Example Output

{
  "input": "We are leveraging our next-generation AI platform to deliver unprecedented insights and drive transformative outcomes across the enterprise.",
  "domain_match": "ai_bs (§2), corporate_bs (§6)",
  "structural_analysis": {
    "specificity": {
      "result": { "Low": 0.85, "Medium": 0.15 },
      "reasoning": "Replace 'our platform' with any company — sentence unchanged"
    },
    "falsifiability": {
      "result": { "Zero": 0.7, "Low": 0.3 },
      "reasoning": "No criteria for 'unprecedented' or 'transformative' — unfalsifiable"
    },
    "commitment": {
      "result": { "Low": 0.9, "Medium": 0.1 },
      "reasoning": "No who, no what specifically, no when"
    }
  },
  "content_analysis": {
    "density": {
      "result": { "Fluff": 0.8, "Mixed": 0.2 },
      "reasoning": "Remove 'next-generation', 'unprecedented', 'transformative', 'across the enterprise' — almost nothing remains"
    },
    "factual_density": {
      "result": { "None": 0.95, "Sparse": 0.05 },
      "reasoning": "Zero numbers, dates, names, or verifiable facts"
    },
    "actionability": {
      "result": { "None": 0.9, "Vague": 0.1 },
      "reasoning": "No one could act on this statement"
    }
  },
  "rhetorical_analysis": {
    "devices_found": [
      { "type": "loaded_language", "instances": ["next-generation", "unprecedented", "transformative"] },
      { "type": "strategic_ambiguity", "instances": ["across the enterprise"] },
      { "type": "weasel_words", "instances": ["drive...outcomes"] }
    ],
    "evasion_tactics_found": [],
    "rhetorical_density": 3.0
  },
  "bs_score": {
    "weighted_raw": 0.12,
    "classification": {
      "Pure": 0.65,
      "Serious": 0.30,
      "Moderate": 0.05
    },
    "dominant": "Pure"
  },
  "tetravalent_mapping": "C",
  "tetravalent_reasoning": "Statement sounds meaningful but conveys zero information — contradictory signal",
  "rewrite": "We built [product name]. It [does X] for [Y users]. [Metric] improved by [N%]. Limitations: [list].",
  "clear_speech_template": "claim + evidence + specifics + commitment"
}

Process

1. Receive input — text, URL, or file path
2. Detect domain — match against 10 BS domain grammars
3. Run structural analysis — specificity, falsifiability, commitment (3 FuzzyEnum results)
4. Run content analysis — density, factual density, actionability (3 FuzzyEnum results)
5. Run rhetorical analysis — device scan, evasion scan (counts + instances)
6. Compute weighted score — combine 6 test scores using defined weights
7. Classify — map score to FuzzyEnum
8. Map to tetravalent — Clear/Mild→T, Moderate→U, Serious/Pure→C
9. Rewrite if needed — if score ≤ Moderate, generate clear-speech alternative
10. Output — structured JSON with all results

Governance

• Article 1 (Truthfulness) — the decoder exists to distinguish truth from rhetoric; it must itself be truthful about what it finds
• Article 5 (Non-Deception) — BS is institutionalized deception; detecting it upholds non-deception
• Article 2 (Transparency) — all scoring weights, test criteria, and reasoning are exposed; the decoder is fully transparent about how it reaches its conclusion
• Governance self-check — the decoder can and should be run against Demerzel's own artifacts (governance BS detection, §5)

Source

grammars/gov-bs-generators.ebnf (Universal BS Generator & Detector Grammar v2), policies/scientific-objectivity-policy.yaml, constitutions/default.constitution.md Articles 1, 2, 5