Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ratnesh-maurya/cursor-claude-personas --skill kaizengit clone --depth 1 https://github.com/ratnesh-maurya/cursor-claude-personasWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ratnesh-maurya/cursor-claude-personas/kaizen)<a href="https://agentmods.dev/skills/ratnesh-maurya/cursor-claude-personas/kaizen"><img src="https://agentmods.dev/badge/skills/ratnesh-maurya/cursor-claude-personas/kaizen/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ratnesh-maurya/cursor-claude-personas/kaizen"><img src="https://agentmods.dev/badge/skills/ratnesh-maurya/cursor-claude-personas/kaizen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.04135 |
| Opus 5 | $0.00018 | $0.02067 |
| Sonnet 5 | $0.00007 | $0.00827 |
| Haiku 4.5 | $0.00004 | $0.00413 |
Grade A, and why
kaizen scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
98% identical to kaizen — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 734 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kaizen: Continuous Improvement
Overview
Small improvements, continuously. Error-proof by design. Follow what works. Build only what's needed.
Core principle: Many small improvements beat one big change. Prevent errors at design time, not with fixes.
When to Use
Always applied for:
- Code implementation and refactoring
- Architecture and design decisions
- Process and workflow improvements
- Error handling and validation
Philosophy: Quality through incremental progress and prevention, not perfection through massive effort.
The Four Pillars
1. Continuous Improvement (Kaizen)
Small, frequent improvements compound into major gains.
Principles
Incremental over revolutionary:
- Make smallest viable change that improves quality
- One improvement at a time
- Verify each change before next
- Build momentum through small wins
Always leave code better:
- Fix small issues as you encounter them
- Refactor while you work (within scope)
- Update outdated comments
- Remove dead code when you see it
Iterative refinement:
- First version: make it work
- Second pass: make it clear
- Third pass: make it efficient
- Don't try all three at once
// Iteration 2: Make it clear (refactor) const calculateTotal = (items: Item[]): number => { return items.reduce((total, item) => { return total + (item.price * item.quantity); }, 0); };
// Iteration 3: Make it robust (add validation) const calculateTotal = (items: Item[]): number => { if (!items?.length) return 0;
return items.reduce((total, item) => { if (item.price < 0 || item.quantity < 0) { throw new Error('Price and quantity must be non-negative'); } return total + (item.price * item.quantity); }, 0); };
Each step is complete, tested, and working
</Good>
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 734 lines · 36 tokens per session scan A d4bc4852c274
kaizen is a skill published in the GitHub repository ratnesh-maurya/cursor-claude-personas (8 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 4,135 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to kaizen, differing in 1 line, and is treated as a copy.
Other skills, from other repositories
gentle-ai-collab-perfect
Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the…
sdd-verify
Skill "sdd-verify" from Gentleman-Programming/gentle-ai, covering execution role, language domain contract, activation contract, hard rules and decision gates.
branch-pr
Create Gentle AI pull requests with issue-first checks. Trigger: creating, opening, or preparing PRs for review.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
cognitive-doc-design
Design docs that reduce cognitive load. Trigger: writing guides, READMEs, RFCs, onboarding, architecture, or review-facing docs.
systemic-issue-triage
Trigger: new issue, bug report, triage, backlog, issue flood, community report, root cause, dead-end, blocked user. Attack issues by root class, never one-by-one; fixes must shrink the system, not grow it.