no-no-debug
A self-evolution system for AI coding assistants
v1.3.0 — periodic review now actually works. Earlier versions promised "auto-triggers every 3 days" but had no enforcement mechanism — the review only ran when manually invoked, and the tracker went stale silently. v1.3.0 ships
hooks/review_reminder.py, aUserPromptSubmithook that checks the tracker on each message and reminds the AI to run the review when it's overdue. See CHANGELOG.md for the one-step migration from v1.2.0.
What problem does this solve?
10 minutes writing code, 2 hours debugging.
This skill fills the gap in AI's cross-session error memory, delivering three things:
- Dramatically less debug time
- Higher code quality
- A self-evolution feedback loop
The longer you use it, the fewer mistakes get repeated.
How it works
1. Real-time Logging (automatic)
When the AI is corrected, code errors occur, deploys fail, or tests don't pass — it automatically appends to a local error_log.md with a timestamp. No need to say "write that down."
2. Three Gates (on every code change)
Before the change: what does this affect? After the change: did you actually verify it? Before deploying: did you test with a non-admin account?
Runs silently. No output when all gates pass.
3. Periodic Review (auto-triggers every 3 days)
Reads error_log.md, categorizes by dimension, updates error_tracker.md, outputs an evolution report. Review frequency is configurable: 1 day / 3 days (default) / 7 days.
4. Rule Accumulation
New error type → automatically creates a prevention rule. Repeated offense → counter increments, rule strengthens. 4 consecutive clean periods → marked as cured.
Rules persist across sessions — nothing gets lost.
5. Confirmation Gate
The following situations require user confirmation before proceeding:
- New feature development (not a bug fix)
- Changes involving databases, environments, or deployments
- Publishing to external platforms
- When the user raises a new idea or new direction mid-task
6. Auto Hooks
Automatically configures Claude Code hooks on install:
- Command errors → auto-logged to error_log.md
- After editing a file → auto-reminder to verify
- When user corrects the AI → correction content auto-logged
- Review overdue → auto-reminder to start Mechanism 3 review
Tracked Dimensions
| Dimension | What it tracks |
|---|---|
| Data Accuracy | Do displayed numbers/formulas match actual code |
| Environment Safety | Did config changes break login or the database |
| Foresight | Were permission, migration, or cache issues caught before deploy |
| User Perspective | Does the feature work end-to-end from the user's account |
| Verification | Was there a real end-to-end test after the fix |
| Memory Consistency | Did the AI read existing records instead of asking again |
| Tool Judgment | Did failing tools get swapped out promptly |
| Review Completeness | Were reviews and summaries thorough with nothing missed |
| Operational Precision | Did changes produce unintended side effects |
| Check Before Doing | With unfamiliar tools/versions, was documentation checked first |
| Conciseness | Was a 3-line solution turned into 300 lines |
| Regression Awareness | Did fixing one bug introduce a new one |
| Style Consistency | Does new code follow the project's existing style and architecture |
| Independent Judgment | When the user's premise is wrong, does the AI push back instead of blindly executing |
| Real-env Verification | Was the fix validated with the real production command, not a sandbox/test harness |
| Cross-agent Trust | Did the AI re-verify another agent's "pass" report instead of trusting it blindly |
| Dumb things humans will do | Not yet committed, but inevitable |
| Dumb things AI will do | Same, but the AI edition |
Real-world data
| Period | Errors | Notes |
|---|---|---|
| Week 1 | 29 | Baseline, 10 dimensions identified |
| Week 2 | 6 | Rules starting to take effect |
| Week 3 | ~0 | Still running |
Installation
Claude Code (recommended — full experience with auto hooks)
claude skill add summerliuuu/no-no-debug
Zero configuration. Tracking files and hooks are initialized automatically on first run.
If you're installing manually or upgrading from v1.1.0, also copy the hook scripts:
mkdir -p ~/.claude/hooks
cp hooks/user_prompt_filter.py ~/.claude/hooks/
cp hooks/post_tool_failure.sh ~/.claude/hooks/
cp hooks/review_reminder.py ~/.claude/hooks/
chmod +x ~/.claude/hooks/post_tool_failure.sh
Then merge the PostToolUseFailure / UserPromptSubmit blocks from SKILL.md → Mechanism 6 into ~/.claude/settings.json.
Prerequisites. The shipped hooks use python3 (UserPromptSubmit filter) and jq (PostToolUseFailure parser). Both ship by default on recent macOS and most Linux distros; if either is missing the corresponding hook degrades gracefully — python3 missing means the correction detector silently no-ops, jq missing writes a one-time jq_not_installed marker to the log. Install with brew install jq (macOS) or your package manager if you want full coverage.
ChatGPT / Cursor / Copilot / Other AI assistants
- Copy the contents of SKILL.md
- Paste it into your system prompt or custom instructions
- Core features (3-gate checkpoint, periodic review, rule accumulation) work immediately
- Auto hooks are Claude Code only — other tools rely on the AI following the rules in SKILL.md
Compatibility
- Claude Code — full experience with auto hooks and one-line install
- Other AI coding assistants (ChatGPT, Cursor, Copilot, etc.) — paste SKILL.md content into your system prompt to use core features
- Any project, any language
- Pairs well with claude-mem (for session search)
⭐
Thank you for starring this project during installation.
📕 Xiaohongshu @Summer的AI日常 — AI coding in practice
🇨🇳 中文版
License
MIT — @summerliuuu