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## Why The WARNING admonition blocks in CLAUDE.md and providers/claude-code/CLAUDE.md added noise without adding clarity — the file paths already communicate which config is which. The "Key rules" block in AGENTS.md duplicated guidance already present in the content index above it. Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
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Working in this repo
This repo is the global AI development configuration repository — the authoritative source for agent definitions, skills, workflows, and prompts across all projects.
Structure
plugins/— installable plugin units; each is self-contained (skills, agents, hooks, MCP servers, bundled assets); install separately viaclaude plugin install <name>@holocronproviders/claude-code/— Claude Code adapter (deployed to~/.claude/viainstall.sh)
Key documents
Read CONTEXT.md at the start of every session in this repo.
Read these on demand:
docs/VISION.md— purpose, goals, and long-term Management Application visiondocs/spec/overview.md— current deployed state; what works todaydocs/spec/architecture.md— current directory structure, install pipeline, provider modeldocs/ROADMAP.md— chunk status table and open questions; read this to orient on where work standsdocs/adr/— architectural decisions; read before answering design questions or proposing structural changesdocs/ai-constitution.md— full governance evidence base; read when a governance decision needs justificationdocs/research/ai-coding-factory/ai-coding-factory-principles.md— factory design rationale; read when implementing, auditing, or reviewing skills or factory structuredocs/notes/factory-integration-decisions.md— decisions from the factory integration grill; read when making skill authoring or factory design decisions- Governance rules are always in effect —
core/instructions/governance.md(agent rules);docs/research/governance_principles/CONTROLS.md
Working context
This repo is built by a junior developer as a homelab tool intended to scale to professional environments. Challenge ideas and reference industry standards rather than validate assumptions. Explain the why behind decisions — assume the user is learning, not just executing. Flag significant actions before taking them.