Help us improve
Share bugs, ideas, or general feedback.
From autocontext
Interactively reviews and curates low-confidence project lessons from .autocontext/lessons.json in batches of 3-4, supporting approve, edit, delete, supersede, and skip actions.
npx claudepluginhub jamditis/claude-skills-journalism --plugin autocontextHow this command is triggered — by the user, by Claude, or both
Slash command
/autocontext:reviewThe summary Claude sees in its command listing — used to decide when to auto-load this command
Review accumulated lessons in `.autocontext/lessons.json`. Use AskUserQuestion to walk through lessons. ## Initialization The script first reads `.autocontext/lessons.json` and separates lessons into two groups: - **Active lessons** — `deleted: false` or not marked deleted - **Tombstoned lessons** — `deleted: true` (lessons that were intentionally removed) If `.autocontext/cache/curated-pending.json` exists (from previous curation sessions with pending items), those are presented first for final approval. ## Review order Active lessons are sorted by **confidence score (lowest first)**....
/hatch3r-learnCaptures learnings from development sessions into reusable knowledge files for future consultation.
/learnRecords lessons learned from input, errors, sessions, or git history into CLAUDE.md. Supports listing, editing, removing entries and git-based automation suggestions.
/learnManage project learnings: save insights and patterns, search past knowledge, prune entries, and export for team sharing.
/reviewReviews staged changes or recent commits across five axes—correctness, readability, architecture, security, performance—producing categorized findings with file:line references and fixes.
/reviewRuns Codex code review on local git state (working tree or vs base branch). Supports --wait/--background, --base <ref>, --scope auto|working-tree|branch.
/reviewPerforms an enhanced multi-LLM code review using multiple providers (Codex, Gemini, Claude) and posts inline PR comments. Designed as escalation path beyond standard /review.
Share bugs, ideas, or general feedback.
Review accumulated lessons in .autocontext/lessons.json. Use AskUserQuestion to walk through lessons.
The script first reads .autocontext/lessons.json and separates lessons into two groups:
deleted: false or not marked deleteddeleted: true (lessons that were intentionally removed)If .autocontext/cache/curated-pending.json exists (from previous curation sessions with pending items), those are presented first for final approval.
Active lessons are sorted by confidence score (lowest first). Low-confidence lessons need the most attention — these are either new, frequently contradicted, or validated by few developers.
Lessons are presented in batches of 3-4 using AskUserQuestion. For each lesson, the review shows:
Example format:
Lesson: "Always run git pull before pushing to main"
Category: workflow
Confidence: 0.9 | Validated: 12 times | Created by: alice | Age: 45 days
For each lesson, you choose one action:
Options:
deleted: true)Bumps confidence by 0.2. Use this when you confirm a lesson is still valid and useful.
Opens the lesson for modification. You can update:
Edited lessons are automatically marked as reviewed by you.
Marks the lesson as tombstoned (deleted: true). The original content is preserved in .autocontext/archive/superseded.json for historical reference, but the lesson won't load during future sessions.
Use this for lessons that are outdated, wrong, or no longer relevant.
Replace the current lesson with a completely new version. You provide the new lesson text. The old lesson is tombstoned and the new one is added as a fresh, high-confidence lesson.
Use this when a lesson is correct in spirit but the specific guidance has changed (e.g., "Use React class components" → "Use React functional components with hooks").
Leaves the lesson unchanged and moves to the next one. Use this when you're not sure or want to review later.
When a lesson has a skill field (non-null) and skill_learning.enabled is true in config, a sixth action is available:
scope to "skill" in lessons.json. Report: "Promoted to global store for [skill name]."The global store path comes from config: skill_learning.global_store (default ~/.claude/skill-lessons/).
To perform the promotion, run:
python3 -c "
import sys
sys.path.insert(0, '${CLAUDE_PLUGIN_ROOT}/scripts/skill-evolution')
from store import promote_lesson, ensure_store
import json
ensure_store()
lesson = json.loads('''LESSON_JSON_HERE''')
result = promote_lesson(lesson, 'SKILL_NAME_HERE', 'PROJECT_NAME_HERE')
print('promoted' if result else 'already_exists')
"
Only show this action when skill_learning.enabled is true in config and the lesson has a non-null skill field.
After reviewing all active lessons, you'll be asked about any tombstoned lessons:
Question: There are N tombstoned lessons. What would you like to do?
Options:
If you choose to review individually, each tombstoned lesson is presented with options to:
deleted: false and add back to active lessonsAfter all reviews are complete, the script automatically regenerates .autocontext/playbook.md using:
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/generate-playbook.py .autocontext/lessons.json .autocontext/playbook.md
The playbook reflects your curated lessons and is the human-readable summary of project knowledge.
At the end, you'll see a report:
Review complete:
- N lessons reviewed
- M lessons approved (confidence increased)
- K lessons deleted (tombstoned)
- J lessons edited
- Playbook regenerated with X active lessons
This summary confirms what changed and gives you confidence that the curation was applied.
/autocontext-review weekly or after major changes to keep lessons fresh and accurate