By shihwesley
Ambient .tech.md generation — auto-documents and tracks freshness of your codebase
Update chronicler.yaml settings with key=value pairs
First-time project setup — detects language, generates config, builds merkle tree, generates initial docs
Regenerate stale .tech.md documentation
Show documentation freshness report — fresh, stale, uncovered, orphaned
Modifies files
Hook triggers on file write and edit operations
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npx claudepluginhub shihwesley/chronicler --plugin chroniclerResearch pipeline + sandboxed Python execution for Claude Code. Turns any topic into agent expertise: structured question tree → source discovery → zero-context fetch (content never enters LLM context) → .mv2 indexing → REPL-based distillation → compact expertise artifact. Also runs Python in isolated Docker containers for code execution, DSPy sub-agents, and data analysis.
Maps codebases of any size using parallel Sonnet subagents with Merkle-tree change detection. Generates docs/CODEBASE_MAP.md with architecture diagrams, module guides, data flows, and navigation guides. Creates docs/.mercator.json merkle manifest for O(1) staleness checks — compare a single root hash to know if anything changed. Post-commit hook auto-refreshes hashes in ~2 seconds with zero API tokens. Supports incremental updates: only re-explores changed modules. Works without git via pure hash-based diff.
Reverse engineer and extract capabilities from any source — repos, configs, binaries, articles — into your agent workflow. Security scanning, manifest tracking, cross-agent restore.
TLDR-aware code simplifier — uses AST summaries for context, full reads only for target files. 80%+ token savings on large codebases. Merkle-integrated for O(1) change detection when used with mercator-ai.
Ambient dev environment management — auto-switches between dev, test, staging, and prod using Docker containers, sidecars, and task-aware classification. Provides /orbit commands for explicit control.
Documentation quality, generation, and improvement using Diataxis principles. Pairs with beagle-core for full workflow.
Lightweight documentation memory for AI coding agents: scaffold a docs tree, validate it, and auto-load recent context each session.
Generate and maintain documentation from code with drift detection. Validates docs against source, auto-generates from code patterns, syncs outdated content, and provides reusable templates for consistent documentation.
Documentation and authoring workflow router: audit docs vs code drift, sync docs after changes, optimize prompts and SKILL.md files, validate GLFM and Markdown formatting, summarize files/URLs/images with fidelity enforcement. Use when: docs are out of date, CLAUDE.md needs improving, SKILL.md needs optimizing, checking if documentation matches code, summarizing files or URLs.
Documentation generation, API docs, and README maintenance
Make your AI agent code with your project's architecture, rules, and decisions.