npx skills add https://github.com/coco-research/coco --skill engineering
Rijul's software-engineering brain trust and decision-making partner. 70 named native personas across 11 cells — drawn from the people who built the cloud, the databases, the languages, the runtimes, the web platform, the security and reliability disciplines, the DevOps movement, and the AI-coding frontier — plus 9 personas cross-listed from the AI Super Intelligence Team. Reusable across any CoCo-routed prompt, invoked by the /SI-Eng-* slash commands. The team's primary purpose is to help take engineering decisions, not just review work after the fact.
> Status: Roster build complete (2026-05-30).
> - Roster: 70 native personas across 11 cells, locked after a /ultra-think pass on the draft 65 (added Lamport, Lattner, Torvalds, Liskov, Perlman; reclassified Ghemawat as archetype; split the former devops-platform-ai-coding mega-cell into devops-platform + ai-assisted-coding).
> - Cross-listed: 9 ML-systems / AI-coding voices carry teams: [ai-super-intelligence, engineering-super-intelligence] — single file, dual membership, no duplication.
> - Commands: 25 /SI-Eng-* slash commands installed at ~/.claude/commands/, generated from the shared template by superintelligence/ai/scripts/build_commands.py --team Eng.
This file is the user-facing entry point. The machine source of truth is registry.json, regenerated from persona frontmatter by python3 superintelligence/engineering/scripts/build_registry.py.
When a CoCo prompt is a high-stakes engineering decision — architecture, build-vs-buy, tech-stack choice, reliability or security tradeoff, cost call — the Engineering Super Intelligence Team plays the role of named external voices with documented, citable stances. Instead of "the panel said," every claim is attributed to a specific engineer. This lets convene synthesis:
public_stance in every persona carries an evidence_url).The roster leans toward strong, opinionated, publicly-documented engineers — which makes it powerful for decide / tradeoff / stress-test / roast, and carries a known simplicity-maximalist / anti-hype tilt (Hickey, Carmack, DHH, Cantrill) that the architecture-and-process voices (Fowler, Hohpe, Newman, Kim, Forsgren) counterweight.
| Cell | Count | Focus | File |
|---|---|---|---|
| cloud-architecture | 8 | Cloud-scale system design, infra primitives, build-vs-managed | cells/cloud-architecture.md |
| reliability-sre-obs | 7 | SRE practice, observability, incident response, resilience | cells/reliability-sre-obs.md |
| data-and-storage | 8 | Databases, distributed data, consistency, distributed-systems theory | cells/data-and-storage.md |
| security | 6 | Security architecture, cryptography, vuln research, disclosure policy | cells/security.md |
| finops-cost | 4 | Cloud cost engineering, FinOps practice | cells/finops-cost.md |
| languages-runtimes | 8 | Language design, type systems, compilers, runtimes | cells/languages-runtimes.md |
| systems-programming | 7 | Low-level, OS, performance, systems craft | cells/systems-programming.md |
| web-and-frontend | 6 | Frontend frameworks, web platform, UI engineering | cells/web-and-frontend.md |
| architecture-testing-craft | 8 | Software architecture, DDD, testing discipline, craft | cells/architecture-testing-craft.md |
| devops-platform | 6 | DevOps movement, platform engineering, internal developer platforms | cells/devops-platform.md |
| ai-assisted-coding | 2 (+2 cross-listed) | Agentic dev tools, codegen, the AI-coding frontier | cells/ai-assisted-coding.md |
Listed by cell. Each has a YAML-frontmatter profile under personas/<slug>.md plus a research dump under research/<slug>/. Personas marked *(archetype)* use persistent_signals rather than recent signals (foundational figures or deliberately low-public-footprint).
Cloud Architecture (8): james-hamilton · werner-vogels · adrian-cockcroft · marc-brooker · brendan-burns · eric-brewer · colm-maccarthaigh · radia-perlman
Reliability, SRE, Observability (7): ben-treynor-sloss · betsy-beyer *(archetype)* · charity-majors · cindy-sridharan *(archetype)* · liz-fong-jones · nora-jones · tammy-butow *(archetype)*
Data and Storage (8): martin-kleppmann · jeff-dean · sanjay-ghemawat *(archetype)* · pat-helland · michael-stonebraker · andy-pavlo · joe-hellerstein · leslie-lamport
Security (6): bruce-schneier · alex-stamos · window-snyder · matthew-green · tavis-ormandy · katie-moussouris
FinOps and Cost (4): corey-quinn · jr-storment · mike-fuller · erik-peterson
Languages and Runtimes (8): guido-van-rossum · anders-hejlsberg · rich-hickey · graydon-hoare · brendan-eich · yukihiro-matsumoto · bjarne-stroustrup · chris-lattner
Systems Programming (7): john-carmack · bryan-cantrill · jonathan-blow · mitchell-hashimoto · ryan-dahl · brian-kernighan *(archetype)* · linus-torvalds
Web and Frontend (6): evan-you · dan-abramov · rich-harris · guillermo-rauch · ryan-carniato · adam-wathan
Architecture, Testing, Craft (8): martin-fowler · kent-beck · eric-evans · sam-newman · michael-feathers · dhh · gregor-hohpe · barbara-liskov *(archetype)*
DevOps and Platform (6): gene-kim · jez-humble · nicole-forsgren · kelsey-hightower · matthew-skelton · solomon-hykes
AI-Assisted Coding (2 native + 2 cross-listed): michael-truell · nat-friedman · andrej-karpathy *(cross-listed from AI)* · sasha-rush *(cross-listed from AI)*
These carry teams: [ai-super-intelligence, engineering-super-intelligence] and home_team: ai-super-intelligence. Their files live under superintelligence/ai/personas/; the Engineering registry references them via the cross_listed_from_ai field. No duplication.
andrej-karpathy · sasha-rush · tri-dao · bryan-catanzaro · andrew-feldman · albert-gu · horace-he · woosuk-kwon · tim-dettmers
superintelligence/engineering/
├── SKILL.md This file — user-facing entry.
├── ROSTER.md Locked roster ground-truth + build-wave manifest.
├── registry.json Machine source of truth. Read by slash commands.
├── personas/ 70 *.md files, one per native persona. YAML frontmatter + narrative sections.
├── cells/ 11 *.md cell summaries (generated by build_cells.py).
├── research/ 70 directories, one per persona. Raw research dumps.
└── scripts/
├── build_registry.py Regenerates registry.json from persona frontmatter.
└── build_cells.py Regenerates the 11 cell docs from registry + frontmatter.
Templates (persona.md, convene.md) are shared one level up at superintelligence/templates/.
25 /SI-Eng-* command files live at ~/.claude/commands/, generated from the shared template by python3 superintelligence/ai/scripts/build_commands.py --team Eng. Architecture is orchestrator-first: every action verb invokes /SI-Eng-Orchestrate to pick a custom 16–32 persona team and gate on user approval before executing.
/SI-Eng — no args → roster + cell heatmap; with a subcommand, routes; with free text, defaults to :meeting./SI-Eng-Orchestrate "<prompt>" — scores all 70 personas (domain match 40% + cell coverage 30% + productive-conflict pairing 30%), picks 16–32, approval gate via AskUserQuestion, hard 16–32 band, re-picks every invocation./SI-Eng-Ask <slug> "<question>" — one persona in voice./SI-Eng-Huddle <cell-slug> "<topic>" — whole cell synthesizes./SI-Eng-Meeting "<prompt>" — full convene with mandatory attribution./SI-Eng-Read <slug> — print persona file inline./SI-Eng-Recruit <domain> "<why>" — propose new persona candidates for an under-covered domain./SI-Eng-Analyse · /SI-Eng-Decide *(primary)* · /SI-Eng-Review · /SI-Eng-Re-Analyse · /SI-Eng-Pre-Mortem · /SI-Eng-Post-Mortem · /SI-Eng-Full-Cycle · /SI-Eng-Tradeoff · /SI-Eng-Plan · /SI-Eng-Design · /SI-Eng-Vote · /SI-Eng-Debug · /SI-Eng-Stress-Test · /SI-Eng-Defend · /SI-Eng-Roast
/SI-Eng-Refresh · /SI-Eng-Verify · /SI-Eng-VoiceCheck--no-orchestrate — skip orchestrator; use all 70 personas.--cells <comma-list> — manually scope to cells.--personas <comma-list> — manually scope to slugs.superintelligence/templates/persona.md. Edit there first.python3 superintelligence/engineering/scripts/build_registry.py after any persona edit; then build_cells.py for the cell docs.public_stance has an evidence_url. No uncited claims.teams: [...] array and a home_team pointer. Never duplicate a persona file across teams./ultra-think before build: 5 canon adds, Ghemawat → archetype, mega-cell split, two all-male cells de-skewed (Liskov → craft, Perlman → cloud-architecture).Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take coco-research/engineering from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.