OntoLedgy Main Organisation
Official@ontoledgy
Offers rigorous ontological engineering, clean-code governance, and multi-platform project management for enterprise-grade software development and data pipeline architecture.
Agent Skills by OntoLedgy Main Organisation
Showing 44 vetted skills indexed across 1 GitHub repositories.
OntoLedgybclearer-pipeline-engineer
Implement and review bclearer data pipelines with strict stage boundaries.
OntoLedgyob-engineer
Implement and review Python code against BORO Quick Style Guide rules.
OntoLedgyjavascript-data-engineer
Enforce TypeScript type safety and JS/TS best practices in data pipelines.
OntoLedgysprint-planner
Plan executable sprints by ordering prioritized tickets into dependency-aware waves.
OntoLedgysoftware-architect
Produce BORO-grounded solution architectures with BIE data identity specifications.
OntoLedgyob-ontologist
Enforce BORO foundational principles in domain ontology modeling workflows.
OntoLedgybie-component-ontologist
Design BIE component ontologies and review implementations for compliance.
OntoLedgylinear-backlog-manager
Publish approved feature specs as hierarchical issue trees in Linear.
OntoLedgyclean-code-size
Identify oversized source files exceeding language-specific line thresholds.
OntoLedgyconfluence-space-manager
Scaffold, audit, and align Confluence spaces to canonical structure.
OntoLedgyclean-code-reviewer
Audit source code for clean coding standard violations across multiple languages.
OntoLedgycsharp-data-engineer
Implement and review .NET 8+ C# data engineering code with clean-coding standards.
OntoLedgyrelease-planner
Generate prioritized, capacity-aligned feature lists from steering documentation.
OntoLedgyskill-feedback
Capture structured defect reports for AI skills and submit them as GitHub issues.
OntoLedgyclean-code-commit
Validate and generate Conventional Commits messages for git workflows.
OntoLedgygo-data-engineer
Implement idiomatic Go ETL pipelines with bounded concurrency and race-safe tests.
OntoLedgydata-engineer
Implement data pipeline components and review code against clean coding standards.
OntoLedgytask-executor
Automate end-to-end tracker ticket implementation across JIRA, Linear, Azure DevOps, and filesystem.
OntoLedgyvulnerability-manager
Detect, triage, and remediate dependency vulnerabilities across multiple ecosystems.
OntoLedgyontologist
Produce structured ontology models defining entities, relationships, and identity criteria.
OntoLedgyui-architect
Enforce frontend architecture guardrails for UI design and review.
OntoLedgyboro-ontologist
Apply BORO methodology to re-engineer legacy entity models into four-dimensional ontological representations.
OntoLedgyui-engineer
Enforce standardized React/TypeScript frontend patterns with WCAG 2.2 AA and Core Web Vitals quality gates.
OntoLedgybie-data-engineer
Implement BIE domains in Python from approved ontology models.
Frequently Asked Questions About OntoLedgy Main Organisation
FAQPage SchemaWhat specific tasks are enabled by OntoLedgy's engineering suite?▼
OntoLedgy enables rigorous ontological modeling, automated clean-code auditing, and synchronized project management. It facilitates the transformation of legacy data into BIE-compliant structures, enforces language-specific coding standards across multiple ecosystems, and manages complex dependency-aware task hierarchies across JIRA, Linear, and Azure DevOps.
Which personas benefit most from these technical capabilities?▼
Software architects, ontologists, and data engineers benefit from these capabilities. The suite is designed for technical leads requiring strict adherence to BORO foundational principles, developers needing automated code quality enforcement, and project managers seeking to align documentation with executable task hierarchies across distributed development environments.
What are the primary prerequisites for implementing these engineering standards?▼
Implementation requires adherence to the BORO methodology for domain modeling and the adoption of OntoLedgy's canonical documentation structures. Users must maintain approved feature specifications in markdown format to trigger the downstream generation of epics, stories, and tasks within their respective project management trackers.