100 domains / 1,000 workstreams / 10,000 atomic task nodes
Built by Srihari Muralikrishnan with ChatGPT for Kalaris Labs
npx kalaris-myriad statsMYRIAD 1.2.0
100 domains / 1,000 workstreams / 10,000 tasks / 10 batches
Maturity: taxonomy-defined; full seed skills: 3
Search the graph:
npx kalaris-myriad search "variant-aware off-target" --limit 5Inspect a node:
npx kalaris-myriad show MYR-D051-T041Export a domain:
npx kalaris-myriad export \
--domain 21 \
--format md \
--output protein-structure-prediction.mdMYRIAD is a release-engineered, machine-readable map of work across biotechnology and pharmaceutical development.
It turns broad fields such as genome assembly, protein engineering, drug discovery, bioprocessing, clinical development, and regulatory science into bounded, searchable agent tasks.
Each task node provides a stable routing surface for:
- agent discovery and delegation;
- retrieval-augmented planning;
- workflow decomposition;
- evaluation and benchmarking;
- conversion into complete production
SKILL.mdimplementations.
MYRIAD is not a collection of 10,000 experimentally validated wet-lab protocols.
The graph currently contains:
| Maturity level | Count | Meaning |
|---|---|---|
| Taxonomy-defined nodes | 10,000 | Bounded tasks with routing metadata, objectives, provenance expectations, review boundaries, and completion evidence |
| Implemented seed skills | 3 | Complete procedural SKILL.md examples with schemas, tool contracts, validation logic, and examples |
Operational use still requires current primary sources, validated local procedures, appropriate authorization, and qualified human review.
100 domains
x 10 workstreams per domain
x 10 atomic tasks per workstream
= 10,000 task nodes
| Layer | Count |
|---|---|
| Biotech and pharmaceutical domains | 100 |
| Standardized batches | 10 |
| Workstreams | 1,000 |
| Atomic task nodes | 10,000 |
| Individual node Markdown files | 10,000 |
Complete seed SKILL.md implementations |
3 |
|
|
Live explorer: https://myriad-explorer.vercel.app
The dependency-free explorer reads the canonical graph directly and provides search, domain/workstream filtering, shareable task URLs, JSON export, task/CLI copy actions, and links to canonical GitHub nodes.
npm run explorerThen open http://localhost:4173/explorer/. A local server is required so the browser can load the canonical JSONL data.
npx kalaris-myriad <command>npm install --global kalaris-myriad
kalaris-myriad statsgit clone https://github.com/KalarisLabs/myriad.git
cd myriad
npm ci
npm test
npm run validate| Command | Purpose |
|---|---|
kalaris-myriad stats [--json] |
Show release counts and maturity |
kalaris-myriad list domains [--json] |
List all 100 domains |
kalaris-myriad list tasks [--domain N] [--limit N] |
Browse task nodes |
kalaris-myriad search <query> [--domain N] [--limit N] |
Search titles, objectives, and routing names |
kalaris-myriad show <id-or-name> [--json] |
Inspect one task node |
kalaris-myriad export --format <jsonl|json|md> --output <path> |
Export all or part of the graph |
kalaris-myriad validate [--json] |
Validate the installed release |
kalaris-myriad init [directory] [--domain N] |
Initialize a working subset |
More command examples
Search only the bioreactor domain:
npx kalaris-myriad search "residence-time distribution" --domain 78Return machine-readable output:
npx kalaris-myriad show MYR-D078-T001 --jsonExport one domain to JSONL:
npx kalaris-myriad export \
--domain 51 \
--format jsonl \
--output crispr-guide-design.jsonlValidate a globally installed release:
kalaris-myriad validate --jsonMYRIAD preserves three layers deliberately:
| Layer | Purpose |
|---|---|
data/raw/ |
Original source records from the ten taxonomy batches |
data/canonical/ |
Homogenized records with consistent routing, provenance, uncertainty, safety, and review contracts |
dist/sanitized/ |
Public-facing distribution without internal build history or legacy release artifacts |
Earlier nodes were not padded with invented scientific detail merely to make every batch look equally verbose. Source meaning is preserved, while the canonical layer normalizes operational boundaries.
.
|-- bin/ Dependency-free command-line interface
|-- data/
| |-- raw/ Preserved source records
| `-- canonical/ Homogenized 10,000-node graph
|-- dist/sanitized/ Public-facing distribution
|-- docs/ Architecture, QA, safety, and release documentation
|-- lib/ CLI and data-access implementation
|-- myriad/
| |-- batches/ Ten standardized batches
| `-- domains/ 100 domains and 10,000 node Markdown files
|-- references/ Controlled reference documentation
|-- schemas/ JSON Schema contracts
|-- scripts/ Release and scientific-structure validators
|-- skills/ Complete seed SKILL.md implementations
|-- tests/ Deterministic Node.js tests
|-- CITATION.cff
|-- CREDITS.md
|-- LICENSE.md
|-- NOTICE.md
|-- SECURITY.md
`-- package.json
Three nodes have been expanded into complete reference implementations:
- Diploid PacBio HiFi assembly optimization
- Variant-aware CRISPR off-target scoring
- HTS normalization, plate QC, and hit calling
These demonstrate the target shape for Phase 3: strict frontmatter, input schemas, procedural stages, decision gates, provenance, failure handling, outputs, and human-review boundaries.
Task names communicate when a node should activate and what decision artifact it produces.
Agents can begin with the global index, narrow to a domain or workstream, and load a full node only when needed.
A score, prediction, or model output is never treated as experimental, clinical, manufacturing, or regulatory proof.
Nodes support explicit pass, warning, fail, and no-call outcomes rather than forcing unsupported conclusions.
The graph does not authorize autonomous wet-lab execution, clinical decisions, GMP disposition, regulatory determinations, or safety overrides.
The release validator checks:
- exactly 100 domains and 10,000 task nodes;
- exactly 100 tasks per domain;
- globally unique IDs, routing names, titles, and objectives;
- valid JSONL and node Markdown frontmatter;
- required execution boundaries and completion evidence;
- placeholder and near-duplicate detection;
- schema compliance;
- deterministic CLI behavior;
- npm package contents.
Run everything locally:
npm ci
npm test
npm run validate
npm run pack:checkSee docs/QUALITY_ASSURANCE_REPORT.md for the readable release summary.
MYRIAD is computational-advisory infrastructure.
It must not autonomously:
- execute wet-lab procedures;
- operate or alter bioreactor controls;
- prescribe treatment or determine patient care;
- release clinical or diagnostic results;
- disposition GMP lots;
- issue final regulatory-compliance determinations;
- bypass institutional biosafety, biosecurity, ethics, privacy, or authorization controls.
A node is not a substitute for current primary literature, validated protocols, local SOPs, approved lab systems, or qualified professional judgment.
Read docs/SAFETY_AND_LIMITATIONS.md.
Good contributions include:
- implementing a taxonomy node as a complete
SKILL.md; - improving source mappings and version resolution;
- adding reproducible evaluation fixtures;
- correcting scientific scope or terminology;
- improving routing, schemas, validators, or documentation.
Please read CONTRIBUTING.md before opening a pull request.
Do not submit credentials, proprietary datasets, controlled information, unsupported clinical recommendations, or operational procedures you are not authorized to disclose.
Citation metadata is available in CITATION.cff.
Suggested acknowledgement:
Srihari Muralikrishnan and Kalaris Labs. MYRIAD: A 10,000-Node Biotech Agent Skill Graph. Version 1.0.2, 2026. AI systems architecture and release engineering supported by ChatGPT, OpenAI.
- Srihari Muralikrishnan - creator, project lead, systems architect, and co-founder of Kalaris Labs.
- ChatGPT - GPT-5.6 Thinking by OpenAI - AI systems architecture, synthesis, normalization, validation tooling, documentation, and release engineering.
- Kalaris Labs - project home, organizational direction, and release stewardship.
See AUTHORS.md and CREDITS.md.
MYRIAD uses a split, attribution-preserving license:
- Software and executable tooling: Apache License 2.0
- Task graph, datasets, and documentation: CC BY 4.0
Public use, modification, redistribution, and commercial use are allowed under the applicable license. Preserve the required notices and credit:
MYRIAD by Srihari Muralikrishnan and Kalaris Labs.
https://github.com/KalarisLabs/myriad