aggregate-logs
CommandGenerate LEARNINGS.md from skill execution logs over a configurable time window.
Interactively refine research results by searching deeper into a specific subtopic or channel. Requires an active research session from /tome:research.
> /plugin marketplace add athola/claude-night-market
name: dig description: >- Interactively refine research results by searching deeper into a specific subtopic or channel. Requires an active research session from /tome:research. usage: >- /tome:dig "<subtopic>" [--channel code|discourse|academic|triz]
Refine an active research session by searching deeper.
# Dig deeper into a subtopic /tome:dig "event loop implementation details" # Search only a specific channel /tome:dig "tokio runtime" --channel code # Dig into academic literature specifically /tome:dig "formal verification of consensus" --channel academic
1. Loads the most recent active research session 2. Runs targeted searches on the subtopic using selected channels (or all channels from the original session) 3. Merges new findings into the existing session 4. Updates the saved report
Invoke the dig skill:
Skill(tome:dig)
`/tome:research`
available channels
A plugin marketplace for Claude Code. Install only the plugins you need to run git workflows, code review, spec-driven development, and autonomous agents from inside your Claude Code session.
Generate LEARNINGS.md from skill execution logs over a configurable time window.
Analyze skill file complexity metrics and generate modularization recommendations for splitting or progressive loading.
Generate context optimization report for skill directories
Create slash commands with brainstorming and best practices
Scaffold new Claude Code skills with brainstorming, TDD methodology, and proper frontmatter and module structure.
Implement tasks incrementally — build, test, verify, commit. Add "auto" to run the whole plan in one approved pass.