project-setup
Scaffold or modernise a Meaningfy-standard repo and PROJECT the Meaningfy spine into it — a top-level package (no src/), Poetry + dedicated root tool configs, cosmic-python layering with import-linter guardrails, TDD+BDD tests, a CLAUDE-canonical agentic setup (CLAUDE.md is canonical; AGENTS.md is an optional symlink), the openspec/ spine (config + pinned meaningfy schema + /opsx:* commands + golden thread), three archetypes (product/library/doc-only) with fixed gate profiles, conditional model/ and CD seam, Antora docs, infra, and CI. Use when starting a new repo or bringing an existing one up to standard. Trigger on "set up a new project", "scaffold a repo", "bootstrap a Python project", "new Meaningfy project", "initialise project structure", "add the standard tooling/docs/CI", "project the spine / set up openspec", "modernise/revamp an existing repo", "bring this project up to standard", "gap analysis against Meaningfy standards".
meaningfy-release
The Meaningfy release lifecycle — semantic versioning policy (MAJOR/MINOR/PATCH + -rc.N pre-releases), GitFlow release/hotfix branches, changelog + GitHub release notes, semi-automated releases via release-please, publishing Python libraries to PyPI with Trusted Publishing (OIDC, no tokens), opt-in supply-chain hardening (signing/provenance/SBOM), and release governance (SECURITY.md, yanking, deprecation). Use when cutting, versioning, publishing, or documenting a release. Trigger on "cut a release", "bump the version", "publish to PyPI", "write release notes", "release branch / hotfix", "yank a bad release", "how do we version this", "set up the release workflow".
modelling-conventions
The shared, representation-agnostic modelling craft reused across the modelling skills — naming discipline, modelling anti-patterns, and the guardrails a modeller follows while working, plus the two load-bearing principles (decouple attributes into reusable first-class properties; identify everything by a stable URI, implicit by default). Use when authoring or reviewing ANY model regardless of representation (conceptual, UML, LinkML, ontology). Trigger on "modelling conventions", "naming conventions for a model", "modelling anti-patterns", "reusable properties/slots", "should this attribute be shared", "URI/identity discipline", "review this model for smells". This is the cosmic-python-style reuse layer for modelling — cited by conceptual-modelling and linkml-engineering, never restated by them.
ci-cd-delivery
Standardise the application-repo Continuous Delivery side of Meaningfy systems — the deploy trigger, the reusable deploy mechanism, and the release/image standard. Use to set up a CD/deploy workflow, release and push a versioned Docker image to a registry (recommended GHCR, tagged by semver + git sha), standardise or migrate the deploy trigger, kill the duplicated SSH/bastion/rsync/.env deploy block by consuming the canonical reusable workflow, or understand the three-repo deploy model. CI (build, test, lint, coverage, architecture, docs publish) is NOT here — that is owned by project-setup; this skill owns only CD + release + the delivery contract. Trigger on "set up CD / deploy workflow", "release and push a versioned image", "GHCR image build", "standardise the deploy trigger", "migrate the duplicated deploy block", "how do we deploy this repo".
conceptual-modelling
Build and evolve a living, representation-agnostic conceptual model for a product (programming) project — the domain's entities, attributes, relationships, and meaning — and choose how it is rendered. Use to model the domain, do conceptual data modelling in UML, run ontology-engineering at the concept level (stable-IRI policy, vocabulary reuse), decide the model *source* (LinkML directly vs model2owl-first), set up a conceptual model, or run terminology/definitions/glossary management. Trigger on "model the domain", "conceptual/UML data model", "set up conceptual model", "which model source", "ontology/terminology management", "ubiquitous language glossary". For the LinkML craft itself (authoring, generation, gates) see linkml-engineering; for generic modelling conventions see modelling-conventions. Conditional: applies to product-development repos that build software; a doc-only/non-product repo does not need it.
linkml-engineering
The operational LinkML craft, downstream of an existing model or spec — never greenfield. Use to derive a LinkML schema from a UML model, a text spec, a model2owl output, or another existing model; to author/refine it (reusable slots, the URI-as-datatype artifice, implicit class_uri/slot_uri, enums, schema-level constraints); to generate the full target set (Pydantic/JSON Schema/OWL/SHACL/TS/SQL) with custom templates and make-target automation including diagrams; and to establish LinkML quality gates. Trigger on "write/derive a LinkML schema", "generate models/OWL/SHACL from LinkML", "custom Pydantic template", "LinkML quality gates", "per-module generation", "make generate-models". Reuses modelling-conventions for generic craft; defers the model concept to conceptual-modelling. Not an ontology-authoring skill.
meaningfy-git-workflow
Meaningfy git and GitHub conventions — Conventional Commits (imperative, no trailing punctuation), branch naming, rebase/merge etiquette, the pull-request workflow, free-tier GitHub constraints, and dev-environment hygiene. Use when committing, branching, opening or maintaining a PR, or setting up a development environment for a Meaningfy project.
agent-harness
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autoresearch-agent
Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.
senior-architect
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senior-security
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senior-data-engineer
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senior-devops
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senior-frontend
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senior-fullstack
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senior-ml-engineer
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senior-prompt-engineer
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senior-qa
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senior-backend
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codex-cli-specialist
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computer-use-automation
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context-engine
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data-quality-auditor
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database-designer
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database-schema-designer
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dependency-auditor
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design-auditor
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devops-workflow-engineer
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doc-drift-detector
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docker-development
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env-secrets-manager
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extended-thinking-architect
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feature-flags-architect
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focused-fix
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gcp-cloud-architect
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git-worktree-manager
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google-workspace-cli
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helm-chart-builder
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incident-commander
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interview-system-designer
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kubernetes-operator
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llm-cost-optimizer
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mcp-server-builder
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migration-architect
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monorepo-navigator
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ms365-tenant-manager
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observability-designer
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performance-profiler
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playwright-pro
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pr-review-expert
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