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 agentmods add skills/djscheuf/agentic-dev-ecosystem-template/refactor-code-with-ainpx skills add djscheuf/agentic-dev-ecosystem-template --skill refactor-code-with-aigit clone --depth 1 https://github.com/djscheuf/agentic-dev-ecosystem-templateWrote 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/djscheuf/agentic-dev-ecosystem-template/refactor-code-with-ai)<a href="https://agentmods.dev/skills/djscheuf/agentic-dev-ecosystem-template/refactor-code-with-ai"><img src="https://agentmods.dev/badge/skills/djscheuf/agentic-dev-ecosystem-template/refactor-code-with-ai.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.01596 |
| Opus 5 | $0.00015 | $0.00798 |
| Sonnet 5 | $0.00006 | $0.00319 |
| Haiku 4.5 | $0.00003 | $0.00160 |
Grade A, and why
refactor-code-with-ai 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Steps
TDD-Refactor Workflow
Purpose
Improve code quality, remove duplication, and enhance design while keeping all tests green.
Trigger
- After code has been implemented and all tests are passing
- Code smells detected
- Duplication exists
- Design can be improved
Prerequisites
- All tests passing (green)
- Code successfully implements required behavior
- Understanding of refactoring techniques
Workflow Steps
Step 1: Identify Refactoring Opportunities
Review code for:
DUPLICATION:
- [ ] Repeated code blocks
- [ ] Similar methods that could be unified
- [ ] Copy-pasted logic
NAMING:
- [ ] Unclear variable names
- [ ] Method names that don't describe behavior
- [ ] Magic numbers without constants
STRUCTURE:
- [ ] Long methods (>20 lines)
- [ ] Deep nesting (>3 levels)
- [ ] Large classes (>200 lines)
- [ ] Missing abstractions
SOLID VIOLATIONS:
- [ ] Class doing too much (SRP)
- [ ] Rigid dependencies (DIP)
- [ ] Large interfaces (ISP)
Step 2: Prioritize Refactorings
Order by impact and safety:
HIGH PRIORITY (Safe, high impact):
1. Rename for clarity
2. Extract constants
3. Remove dead code
4. Simplify conditionals
MEDIUM PRIORITY (Moderate risk):
5. Extract methods
6. Extract classes
7. Introduce parameters
LOW PRIORITY (Higher risk, do carefully):
8. Change method signatures
9. Restructure inheritance
10. Modify public APIs
Step 3: Apply ONE Refactoring
IMPORTANT: One change at a time!
1. Make a single, focused change
2. Run all tests immediately
3. Verify tests still pass
4. Commit if green
5. Repeat for next refactoring
Step 4: Run Tests After Each Change
After EVERY refactoring step:
$ dotnet test # C#
$ pytest # Python
$ npm test # TypeScript
If ANY test fails:
- STOP immediately
- Undo the change
- Understand why it broke
- Try a smaller step
Step 5: Review Refactored Code
Verify improvements:
- [ ] Code is more readable
- [ ] Duplication is reduced
- [ ] Names are clearer
- [ ] Structure is simpler
- [ ] All tests still pass
- [ ] No new functionality added
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 280 lines · 29 tokens per session scan A ba2233328f4d
refactor-code-with-ai is a skill published in the GitHub repository djscheuf/agentic-dev-ecosystem-template (12 stars, last pushed 4d ago), licensed MIT. It adds 29 tokens to every session and 1,596 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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