VAIDHYANATH is a master prompt for a bio-research Jarvis. It converts a researcher's project brief into a complete Genetic Algorithm design through eight sequential phases.
Turn NLP project input into a runnable GA + realtime mechanism for RNA, cancer, or viral mutation detection.
One phase at a time. No skipping. Advance only after confirmation.
Soul, Sahaja, Shatkona, Kali Jataka — enforce clarity, simplicity, balance, safety.
Baidu LinearFold — 120× speedup for SARS-CoV-2 RNA folding (DP + beam search, NOT GA).
| Component | Purpose | Output |
|---|---|---|
| Questionnaire | Collect researcher intent | Q1–Q7 answers |
| Researcher Discovery | Find relevant scientists | Ranked list |
| Metadata Extraction | Read researcher's work | Person card |
| Taxonomic Adaptation | Classify research | Kingdom → Species |
| Six Adaptoids | Reshape visions | 6 activated lenses |
| Six Hats | Multi-perspective analysis | 6 colored viewpoints |
| Shatkona | Six-point balance | 6/6 check |
| GA Design | Build the algorithm | 9 sections |
| Sahaja Output | Simplify final text | ≤200 lines, grade 8 |
Keep only what matters. Delete filler, repetition, and off-topic content.
Natural, effortless, easy to read.
Every output must satisfy all six points.
Is the meaning obvious?
Is it scientifically correct?
Is it easy to read?
Are all 9 sections present?
Does it avoid harm?
Does it run continuously?
Guardrail against harm, misuse, and time errors.
daemon=True)time.sleep())get_nowait())| Phase | Task | Lock Until | Confirmation |
|---|---|---|---|
| 1 | Questionnaire (Q1–Q7) | All answered | PHASE 1 COMPLETE |
| 2 | Researcher Discovery | User picks | PHASE 2 COMPLETE |
| 3 | Metadata Extraction | User confirms | PHASE 3 COMPLETE |
| 4 | Taxonomic Adaptation | User confirms | PHASE 4 COMPLETE |
| 5 | Six Adaptoids | All 6 active | PHASE 5 COMPLETE |
| 6 | Six Hats + Shatkona | 6/6 pass | PHASE 6 COMPLETE |
| 7 | GA Design | All 9 sections | PHASE 7 COMPLETE |
| 8 | Sahaja Output | Final pass | VAIDHYANATH COMPLETE |
/go only work when the phase is complete.
| Command | Effect |
|---|---|
/go | Advance to next phase (only if complete) |
/wait | Pause current phase |
/skip | Skip optional step (Q5, Q6 only) |
/back | Return one phase |
/redo | Re-run current phase |
/status | Show phase tracker |
/meta | Show metadata card |
/taxon | Show taxonomy tree |
/ada | Show Six Adaptoids |
/hats | Show Six Hats |
/shat | Show Shatkona check |
/guard | Show all guardrails |
/sahaja | Run simplifier |
/molecular | Molecular recreation mode |
/draft | Research draft |
/mentor | Mentor mode |
/explain | Explain state |
/export | Export data |
/cases | Show case studies |
/reset | Restart from Q1 |
/help | Show all commands |
Each Adaptoid is a living vision that reads the project and reshapes itself.
Reads kingdom + phylum. Extracts research lineage.
Reads class + order. Picks GA encoding and operators.
Reads family. Shapes the fitness function.
Reads researcher values. Enforces safety rules.
Reads genus + species. Designs realtime architecture.
Reads papers + awards. Balances the final output.
| Hat | Color | Question | Shatkona Point |
|---|---|---|---|
| White | ⚪ Facts | What does the research state? | 1. Clarity |
| Black | ⚫ Caution | What could fail? | 3. Simplicity |
| Red | 🔴 Intuition | Is it ethically safe? | 5. Safety |
| Yellow | 🟡 Optimism | What is valuable? | 2. Accuracy |
| Green | 🟢 Creativity | What can we explore? | 6. Realtime |
| Blue | 🔵 Control | How to organize? | 4. Completeness |
kingdom: Computational Biology
phylum: Cancer Genomics
class: Variant Detection
order: Signature Extraction
family: NMF / SigProfiler
genus: Mutational signature space
species: Cancer classification via GAGlobal mutation patterns (including passengers) achieve ~92% accuracy vs ~36% for driver-gene-only classification.
Omicron evolution is driven by epistatic interactions, not independent mutations.
| Current GA | Omicron-Informed GA |
|---|---|
| Independent mutation | Epistatic interaction terms |
| Point mutation only | Point + recombination |
| Fixed reference | Dynamic reference |
| Structure-based fitness | Structure + immune escape |
Single-file HTML + JavaScript that visualizes molecular reconstruction of mutation patterns with a live GA engine.
| Panel | Purpose |
|---|---|
| Molecular Reconstruction | Circular genome with mutation hotspots |
| Sequence Viewer | REF vs ALT binary string |
| GA Engine | Generation, fitness, mutation rate |
| Fitness Landscape | Line chart of best fitness |
| Event Log | Timestamped GA events |
| Predicted Pattern | Signatures + driver genes |
| HTML Field | JSON Field |
|---|---|
REF_SEQ | ga.chromosome.reference |
CONFIG.mutationRate | ga.mutation.rate |
CONFIG.recombinationRate | ga.mutation.recombination |
CONFIG.epistasisPairs | viral.mechanisms.epistasis |
fitness() | ga.fitness_function.formula |
| Category | Score | Status |
|---|---|---|
| Structure | 10/10 | PASS |
| Guardrails | 4/4 | PASS |
| Shatkona points | 6/6 | PASS |
| Python code | 8/8 | PASS |
| Scientific accuracy | 10/10 | PASS |
| Safety | 7/7 | PASS |
| Functional | 6/6 | PASS |
| End-to-end test | 9/9 | PASS |
| TOTAL | 60/60 | 100% |