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Generalised autonomous optimisation loop — soft RLVR for any artifact a user can measure. Web runtime package: uses memory in this order: connector-backed, project-pack, none. Never assumes subprocess access or unrestricted local files. Use this skill whenever a user wants to iteratively improve an artifact — code, prompts, documents, configs, designs, content — by running structured experiments, evaluating results against a multi-dimensional rubric, and learning from each attempt. Triggers include: "optimise this", "keep improving until it's good", "run experiments on", "autoresearch", "iterate on this overnight", "try different approaches and pick the best", or any request implying repeated evaluate-and-improve cycles.

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Optimize Docker build times using layer caching, multi-stage builds, BuildKit features, and dependency-first copy patterns. Applicable to R, Node.js, and Python projects. Use when Docker builds are slow due to repeated package installations, when rebuilds reinstall all dependencies on every code change, when image sizes are unnecessarily large, or when CI/CD pipeline builds are a bottleneck.

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Create, merge, and deduplicate BibTeX bibliography files using R packages (RefManageR, bibtex). Parse .bib files into structured R objects, merge multiple bibliographies with deduplication by DOI or title similarity, generate entries from DOI/ISBN/arXiv ID, and export clean sorted .bib files. Use when creating a new .bib file for an R Markdown or Quarto project, merging bibliographies from multiple collaborators, deduplicating a .bib that has grown through copy-paste accumulation, or generating BibTeX entries programmatically from DOIs or other identifiers.

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Format a Quarto or R Markdown report following APA 7th edition style. Covers apaquarto/papaja packages, title page, abstracts, citations, tables, figures, and reference formatting. Use when writing an academic paper in APA format, creating a psychology or social science research report, generating reproducible manuscripts with embedded analysis, or preparing a thesis or dissertation chapter.

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Install and configure the putior R package for workflow visualization. Covers CRAN and GitHub installation, optional dependencies (mcptools, ellmer, shiny, shinyAce, logger, plumber2), and verification of the complete annotation-to-diagram pipeline. Use when setting up putior for the first time, preparing a machine for workflow visualization tasks, when a downstream skill requires putior to be installed, or restoring an environment after an R version upgrade or renv wipe.

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Create a Work Breakdown Structure (WBS) and WBS Dictionary from project charter deliverables. Covers hierarchical decomposition, WBS coding, effort estimation, dependency identification, and critical path candidates. Use after a project charter is approved, when planning a classic or waterfall project with defined deliverables, breaking a large initiative into manageable work packages, or establishing a basis for effort estimation and resource planning.

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Create a Dockerfile for R projects using rocker base images. Covers system dependency installation, R package installation, renv integration, and optimized layer ordering for fast rebuilds. Use when containerizing an R application or analysis, creating reproducible R environments, deploying R-based services (Shiny, Plumber, MCP server), or setting up consistent development environments across machines.

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Scaffold a new puzzle type across all 10+ pipeline integration points in jigsawR. Creates the core puzzle module, wires it into the unified pipeline (generation, positioning, rendering, adjacency), adds ggpuzzle geom/stat layers, updates DESCRIPTION and config.yml, extends the Shiny app, and creates a comprehensive test suite. Use when adding a completely new puzzle type to the package or following the 10-point integration checklist to ensure nothing is missed end-to-end.

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Add Rcpp or RcppArmadillo integration to an R package for high-performance C++ code. Covers setup, writing C++ functions, RcppExports generation, testing compiled code, and debugging. Use when an R function is too slow and profiling confirms a bottleneck, when you need to interface with existing C/C++ libraries, or when implementing algorithms (loops, recursion, linear algebra) that benefit from compiled code.

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GraphQL, WebSockets, and microservices patterns for NestJS. Apply only when the relevant package is in dependencies (`@nestjs/graphql`, `@nestjs/websockets`, `@nestjs/microservices`). Each section is orientation, not exhaustive — defer to NestJS docs for deep dives. Use this skill to: - Wire a GraphQL resolver (code-first) with class-validator inputs. - Build a WebSocket gateway with auth and room management. - Set up a microservice transport (TCP/RabbitMQ/NATS/Redis/Kafka) and message handlers. Do NOT use this skill for: - REST controllers (see nest-conventions + decorator-patterns). - ORM (see nest-data-layer). - Auth strategies (see security-analyst phase guidance).

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Node.js backend conventions: project layout, configuration, logging, routing, and error handling patterns. Apply when implementing or modifying Node.js backend code in projects matching the nodejs stack profile. Use this skill to: - Pick conventional file/folder structure for a new module. - Wire configuration through env vars correctly. - Use the project's existing logger style. - Implement error handling that matches the framework (Express/Fastify/Koa). - Follow async/await patterns consistently. Do NOT use this skill for: - Frontend code (React/Vue/RN have their own conventions). - NestJS-specific patterns (decorators, DI, modules) — nest-plugin owns those. - Database schema design (call out as a sub-task; npm-patterns covers package management, not DB).

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Use when installing or refreshing sound taste rules in a project — an explicit "sound setup", starting work in a repo with no .claude/sound/, or a taste-not-defined nudge. Also use to re-run after a stack change (new framework, new package in a monorepo).

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Use Therapeutics Data Commons through the PyTDC Python package for registry discovery, approved dataset access, task-aware splits (scaffold, cold-start, temporal, combination), evaluator metrics, benchmark groups, and bounded molecular-oracle workflows. Use this skill to find which TDC datasets exist for a therapeutic task, load them with a split that does not leak, score predictions with the task's own official metric rather than a generic one, and run benchmark groups reproducibly. Also trigger on PyTDC, Therapeutics Data Commons, tdc.single_pred, tdc.multi_pred, ADMET Benchmark Group, scaffold split, get_split, or molecular oracles such as GSK3B, JNK3 and DRD2.

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Use when writing CMakeLists.txt, out-of-source builds, target_link_libraries, target properties, find_package/FetchContent, toolchain files, CPack, CMake presets, or cmake configure errors.

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Use when work reaches a session boundary or the user asks to hand off, delegate, or get a clipboard-ready prompt. Mode brief packages continuity; mode prompt builds the delegation prompt.

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Use when a repository needs Git safety controls: guard destructive commands, set up gitignore or fix gitignore when untracked files keep appearing, or install or repair a repository-local pre-commit hook from project gates, including package-manager-native commit-time checks. Not for remote, credential, publish, deploy, or irreversible changes.

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Use when the user asks for release, version bump, changelog, or branch workflow beyond a single commit. Don't use for single commits or for publishing to a package registry.

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Update Proto UI human documentation, localized pages, contributor guidance, demos, or package prose as a projection of governed repository facts. Use when the reader problem and source authority are known. Do not use documentation to invent semantics, hide drift, or widen a lifecycle guarantee.

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Apply one governed bounded Proto UI dependency update after pui-deps establishes the exact manifest, lockfile, consumers, compatibility evidence, and rollback boundary. Use for ordinary package or toolchain updates whose intended compatibility is already fixed. Route unresolved public compatibility, security disclosure, publication, release, or provenance exceptions to their dedicated decision path.

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Prepare a reviewed Proto UI global release candidate as repository state after current project authority has chosen the exact version and stage. Use for draft Version identity, exact package metadata, notes, bill of materials, rehearsal, and publish dry-run. Publication remains a distinct privileged operation.

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Trace a Proto UI change through authoritative spec lifecycle, legacy explanation, dated context, implementation, executable evidence, package surfaces, and public projections. Use before deciding scope, changing behavior, reviewing a pull request, or investigating drift.

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Distill books, documents, folders, or URLs into compact, practical Agent Skills. Use when source material should become either one reusable skill package or a split set of focused skills, each with a concise SKILL.md plus detailed references and examples.

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Generate professional Agent Skills for AI agents. Creates complete skill packages with SKILL.md, references, scripts, and templates. Use when creating new skills, generating custom slash commands, or building reusable AI capabilities. Validates against Agent Skills specification.

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Design guide + benchmarked pitfalls for building Monte-Carlo / Simulated Annealing refinement layers on top of greedy hex-grid layouts for code visualization (packages/gui/src/store/hexLayout.ts, sandbox/hex-sandbox, future Rust ports). Use when: (1) planning to add MC/SA on top of an existing hex-grid pack, (2) deciding whether a simpler SA would match a hierarchical MC with force-directed + chain drag, (3) budgeting wall-clock for million-node cold-start, (4) debugging "blob turns Swiss-cheese" or "folders stop nucleating" during MC refinement, (5) choosing between folder cohesion and raw Σ-link-length as cost function. Contains four hard-won, quantified lessons and anti-patterns that would take a full day of experiments to rediscover.

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