Claude Code OpenAI Codex CLI Cursor Kiro

pip

When your AI gives up, pip it.

Claude Code / Codex not meeting expectations? PIP keeps AI from quitting, gives it methodology to succeed, and drives proactive problem-solving.

The Five AI Slacking Patterns

Claude Code looks busy but accomplishes nothing.

Pixel-Matching: 88.7% โ†’ 99.5%

ZenUML has two rendering paths (HTML/React and native SVG). The SVG renderer needed to pixel-match HTML output. AI kept spinning on anti-aliasing tweaks until PIP forced systematic investigation โ€” uncovering a 2px CSS box-model offset that fixed 83 pixels at once.

88.7% baseline
88.7%
Stage 1 โ€” Baseline
Heavy mismatch. Oversized icon, wrong stroke color. AI applies obvious fixes.
93.6% stuck
93.6%
Stage 2 โ€” Stuck
Scattered mismatches remain. AI starts spinning โ€” tweaking anti-aliasing parameters in circles.
99.5% final
99.5%
Stage 3 โ€” PIP Activated
PIP forced: extract every mismatch pixel, categorize by region, measure element positions. Found 2px CSS offset โ€” 83 pixels fixed at once.

Three Pillars of AI Accountability

Iron rules set the standard. Escalating pressure enforces it. Structured methodology makes success possible.

Three Iron Rules

Escalation Levels

5-Step Debugging

Install pip

Choose your platform. Takes 30 seconds.

# Install from marketplace
claude plugin marketplace add mrcoder/pip

# Or install directly
claude plugin install pip@pip-skills

Auto-triggers on repeated failures. Manual trigger: /pip

# Download skill file
mkdir -p ~/.codex/skills/pip
curl -o ~/.codex/skills/pip/SKILL.md \
  https://raw.githubusercontent.com/mrcoder/pip/main/codex/pip/SKILL.md
# Download rule file
mkdir -p .cursor/rules
curl -o .cursor/rules/pip.mdc \
  https://raw.githubusercontent.com/mrcoder/pip/main/cursor/rules/pip.mdc
# Download steering file
mkdir -p .kiro/steering
curl -o .kiro/steering/pip.md \
  https://raw.githubusercontent.com/mrcoder/pip/main/kiro/steering/pip.md