mepuka

Value-based data structures (Data.struct, tuple, array) and high-performance collections (Chunk, HashSet). Use for safe comparisons and pipelines.

Concurrency with Effect.all, forEach concurrency, Fiber lifecycle, race and timeouts. Use for parallelizing tasks safely.

Config loading and Schema validation/transform. Use when defining configuration or validating inputs.

Error modeling and recovery with TaggedError, catchTag(s), mapError, and retry schedules. Use when defining errors or adding resilience.

Core Effect foundations and style for a coding agent. Use when starting an Effect task, choosing operators, or structuring a small pipeline.

HTTP server, routing, JSON responses and dependencies via layers. Use when wiring endpoints and services.

Skill index and decision guide. Use to pick the right Effect Skill quickly and follow a minimal decision tree.

Define services, provide layers, compose dependencies, and switch live/test. Use for DI boundaries and app composition.

Formalizes an approved conceptual model as programmatic OWL 2 artifacts using Programmatic Ontology Development (POD). Creates OWL 2 axioms, manages class hierarchies, generates and preflights ROBOT templates, writes KGCL patches, drafts SHACL shapes from…

Builds a conceptual model from requirements and reuse findings: glossaries, taxonomies / class hierarchies, property designs, module and layer design, and a BFO upper ontology category decision (continuant vs occurrent; quality vs role vs disposition). Aligns…

Maintains existing ontologies through classified KGCL change proposals, term deprecation, reparenting, and renaming; import refresh against the imports-manifest; diff generation; versioning; release workflows (preparation + release notes + FAIR / OBO…

Generates, verifies, evaluates, and maintains cross-ontology mapping and alignment using SSSOM, lexical matching via oaklib (lexmatch), and LLM-assisted verification and semantic review. Produces mapping sets with SEMAPV justification, confidence, and…

Elicits, refines, and formalizes ontology requirements specification and competency questions (CQs). Writes ORSD documents (scope, use cases, non-goals), converts stakeholder questions into validated SPARQL acceptance tests (CQ test suites), and maintains a…

Searches, finds, evaluates, and imports reusable ontological resources before new term creation. Queries OLS, BioPortal, OBO Foundry, LOV, schema.org, and domain registries; checks term existence, license, maintenance cadence, BFO/RO fit; picks an import…

Runs ontology and mapping quality gates: OWL reasoners, OWL profile validation, ROBOT quality reports, SHACL / pyshacl validation, CQ acceptance test suites, anti-pattern SPARQL, SSSOM validation, computes quality metrics, and generates diff reports for…

Designs, validates, runs, and debugs SPARQL 1.1 and SPARQL-star queries for ontology engineering: CQ tests, anti-pattern checks, coverage metrics, mapping clique analysis, import diagnostics, ROBOT query, and rdflib graphs. Handles dialect differences between…