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Agentic Engineering Lab

Public portfolio hub for applied AI engineering, agent tooling, reusable skills, OSS contributions, and sanitized production engineering case studies by blockedby.

This repository is an index, not a product monorepo. The active work lives in the linked public repositories; this lab provides a concise map of the tools, operating model, and supporting evidence.

Current focus

  • Isolated Pi/Pipi environments and coding-agent runtime integration
  • Multi-model delegation across Pi, Codex, Claude, Luna, and Terra
  • Reusable Agent Skills for review, browser work, planning, and verification
  • Deterministic evidence collection with bounded LLM-assisted interpretation
  • Dependency-aware GitHub planning and conflict-safe parallel work
  • Backend, Linux, browser-runtime, and operational automation

Current agent toolkit

Project What it demonstrates
blockedby/my-pi-setup Pipi, my current isolated Pi environment: pinned runtime, separate state, subagent profiles, parallel workflows, background terminals, browser/Codex integration, and reusable skills. Maintained as a public fork of davis7dotsh/my-pi-setup.
blockedby/plan-gh-backlog Agent Skill and Python CLI for validating roadmap structure, planning dependency-ready batches, and safely publishing idempotent GitHub issue backlogs.
blockedby/gpt5.6-reviewer Evidence-driven code-review contracts, routing, closure semantics, CLI validation, and a reusable review skill.
blockedby/pi-codex Deterministic web search/fetch plus bounded Codex summarization, patch handling, and delegated coding tools for Pi.
blockedby/browser-chrome-skill Portable Chrome DevTools skill with disposable headless sessions and an explicit persistent-browser boundary.

Pipi composes the working environment around these capabilities: scoped implementation and audit agents, eight-way workflow fan-out, long-running background terminals, fd/rg discovery, ask-user interactions, browser MCP servers, and Codex/Claude/Pi delegation. The individual repositories keep each tool or skill inspectable and independently reusable.

Reusable Agent Skills

The public skills/general collection contains the reusable engineering layer behind these workflows:

Skill Purpose
backend-quality Backend, API, storage, validation, auth, idempotency, and data-safety evidence.
frontend-quality Frontend implementation and UI-quality checks.
devops-quality Configuration, CI, container, deployment, and runtime readiness.
visual-composition Product-quality hierarchy, responsive composition, complete states, and interaction polish.
completion-verification Fresh acceptance evidence before readiness or completion claims.
git-branching Safe PR-first branches, worktrees, rebases, and target synchronization.
browser-chrome Controlled persistent and disposable Chrome automation.
explanatory-html-pages Self-contained technical explainers with readable diagrams.
modern-skill-revising Focused context and instruction design for modern models.

Standalone skills add specialized workflows: code-review provides evidence-driven review and closure contracts, while plan-gh-backlog validates and publishes dependency-aware GitHub backlogs.

Additional public work

Area Public target Notes
Voice tooling blockedby/kwispr Actively developed fork of MaksBoi/kwispr: Wayland/KDE dictation with cloud, OpenRouter, and local/offline STT, plus a Rust inference runtime and native desktop integration.
Systems automation blockedby/vibe-practicum-vpn Public-safe Linux/KDE VPN and routing tooling, container test labs, guarded operations, and redacted diagnostics.
LLM SDK work blockedby/go-openrouter Fork/contribution work around a Go OpenRouter SDK, with upstream attribution.
Linux automation blockedby/linux-kubuntu-tweaks Personal Linux/Kubuntu automation and recovery runbook; environment-specific rather than a packaged product.
Browser runtime Upstream Obscura commit Merged Rust/CDP contribution attributed to blockedby: promise settling, DOM event and navigation side effects, click-submit parity, and end-to-end regression coverage.

Selected case studies

Start with case-studies/ for the reading guide.

Workflow references

How I work

I use agents as engineering tools, not as unchecked decision makers:

  1. define the problem, constraints, and acceptance criteria;
  2. split work into bounded slices with explicit ownership and dependencies;
  3. route exploration, implementation, and audit to the appropriate tool or model;
  4. keep deterministic evidence separate from model summaries or opinions;
  5. verify with tests, builds, static checks, browser evidence, or explicit manual checks;
  6. record what changed, why it changed, and what remains risky.

Optional public submodules

The submodules/ directory contains optional references to selected public repositories. They are convenient review links, not vendored source or ownership claims over upstream projects.

git clone --recurse-submodules https://github.com/blockedby/agentic-engineering-lab.git

Only public repositories belong here. Private repositories must not be published or added as submodules.

Public-safety rules

  • No secrets, tokens, cookies, credentials, raw logs, chat IDs, webhook URLs, private endpoints, or real user data.
  • No private repositories are published or linked as public evidence.
  • Forks and contributions are described as fork work, contribution work, or my changes in a fork.
  • Upstream projects and maintainers are attributed clearly.

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Public portfolio hub for agentic engineering, AI tooling, OSS contributions, and sanitized case studies.

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