By a3lem
Theodore Calvin's testing framework - language-agnostic, JSON-based test runner
Personal collection of Claude Code plugins, published as a marketplace.
tc: input.json to output.json, diffed against expected.json.tk, a git-backed issue tracker for AI agents.~/.claude/.notes/, structured decision log, and timestamped journal entries.Three plugins work together to manage project knowledge:
| Store | Plugin | Contract | Purpose |
|---|---|---|---|
specs/ | spec-driven-dev | Strongest | Behavioral truth — Gherkin scenarios, verified before shipping |
docs/ | (none needed) | Strong | Durable reference — maintained, authoritative |
notes/DECISIONS.md | project-notes | Medium | What was decided — concise dcn-xxxx entries |
notes/ | project-notes | Weak | Working knowledge — may go stale |
notes/journal/ | project-notes | Weakest | Timestamped snapshots — decay over time |
project-knowledge provides routing rules for deciding where information should live and where to look for it.
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npx claudepluginhub a3lem/my-claude-plugins --plugin theo-calvin-testingSkills for using shablon, a CLI that renders Jinja2 templates from a .shablon/ directory into a project tree.
File-based inter-agent messaging for parallel Claude Code sessions
Spec-driven development system with structured directories for requirements, design, tasks, and notes
Project knowledge management with notes, decision logs, and timestamped journal entries
Automatically prompt execution of Session Setup steps from CLAUDE.md on session start
Test framework detection, convention-aware test generation, and changed-file test execution.
Documentation, research, test generation, document generation, and prompt optimization tools
Documentation testing and validation using Doc Detective. Test documentation procedures, convert docs to executable test specs, and validate that documented workflows match actual application behavior.
SPEC-First development workflow with TDD, Ralph Loop, and autonomous agent coordination for Claude Code
TestForge - Master of quality assurance through intelligent test generation. Analyzes code behavior to auto-generate comprehensive tests that catch real bugs, not just boost coverage numbers. Supports Jest, Pytest, Vitest, and more.
Systematic testing through mental execution - trace code, skills, commands, and configs line-by-line with concrete values to find bugs, missing logic, edge cases, and AI hallucinations