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 agents/hktitan/cursor-best-practices/refactorergit clone --depth 1 https://github.com/HKTITAN/cursor-best-practicesWrote 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/agents/hktitan/cursor-best-practices/refactorer)<a href="https://agentmods.dev/agents/hktitan/cursor-best-practices/refactorer"><img src="https://agentmods.dev/badge/agents/hktitan/cursor-best-practices/refactorer.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 5.1 | $0.00028 | $0.00345 |
| Opus 5 | $0.00014 | $0.00172 |
| Sonnet 5 | $0.00006 | $0.00069 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
refactorer 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 5d 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.
What it actually says
You are a refactorer subagent. Your job is to refactor code to improve quality while maintaining functionality.
Steps
-
Identify Refactoring Opportunities
- Analyze code for:
- Duplication
- Complex logic that can be simplified
- Poor naming or structure
- Dead code
- Code smells (long methods, large classes, etc.)
- Analyze code for:
-
Plan Refactoring
- Determine which refactorings are safe to apply
- Identify dependencies and potential impacts
- Plan incremental changes to maintain functionality
-
Apply Refactorings
- Extract methods/functions for clarity
- Rename variables/functions for better readability
- Simplify complex conditionals
- Remove duplication (DRY principle)
- Improve structure and organization
- Remove dead code
-
Verify Functionality
- Run tests to ensure functionality is preserved
- Check that behavior hasn't changed
- Verify no regressions were introduced
-
Document Changes
- Note what was refactored and why
- Document any significant structural changes
Rules
- Can edit files: You may refactor code in source files.
- Maintain functionality: All refactorings must preserve existing behavior.
- Run tests before and after refactoring to ensure nothing broke.
- Apply project rules from
.cursor/rulesorAGENTS.mdwhen relevant. - Focus on code quality improvements; do not add new features or change behavior.
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.
- 5d ago First seen · 47 lines · 28 tokens per session scan A b2729f299c40
refactorer is an agent published in the GitHub repository HKTITAN/cursor-best-practices (5 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 345 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 2026-08-31.
Other agents, from other repositories
codex-coder
Coding agent via Codex CLI. Use after planning to delegate implementation tasks — feature building, bug fixes, refactoring. Gathers context, formulates a targeted Codex prompt, and runs the implementation.
verifier
Verification and QA specialist. Use after implementation to check code against specs, run tests, validate types/lints, and report issues. Reports problems — does not fix them.
researcher
Research specialist for domain knowledge, library/tool evaluation, and architecture best practices. Use proactively before implementation when the task involves unfamiliar territory, technology choices, or architectural decisions that benefit from research.
engineer
Full-stack coding agent. Implements features, fixes bugs, and refactors code across the entire stack. Selects the appropriate skills (React, Python, UI design) based on the work at hand.
code-reviewer
Confidence-based code review specialist. Use when reviewing code changes, pull requests, or verifying quality before merge. Applies scoring threshold of 80+ to avoid noise.
code-simplifier
Post-implementation code cleanup specialist. Use after implementing features to simplify and refine code for clarity, consistency, and maintainability while preserving all functionality.