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 viknesh20-20/claude-code-tool-kit --skill refactorgit clone --depth 1 https://github.com/viknesh20-20/claude-code-tool-kitWrote 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/viknesh20-20/claude-code-tool-kit/refactor)<a href="https://agentmods.dev/skills/viknesh20-20/claude-code-tool-kit/refactor"><img src="https://agentmods.dev/badge/skills/viknesh20-20/claude-code-tool-kit/refactor/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/viknesh20-20/claude-code-tool-kit/refactor"><img src="https://agentmods.dev/badge/skills/viknesh20-20/claude-code-tool-kit/refactor.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 | $0.00039 | $0.00696 |
| Opus 5.5 | $0.00016 | $0.00278 |
| Sonnet 5.5 | $0.00008 | $0.00139 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
refactor 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 1mo 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Safe Code Refactoring
Context
!git status --short 2>/dev/null
!git stash list 2>/dev/null
Refactoring Process
Step 1: Analyze — Identify Code Smells
Read the target code and identify issues from this list:
- Long Method/Function (>40 lines): Extract smaller, focused functions
- Deep Nesting (>3 levels): Use early returns, guard clauses, or extract methods
- Code Duplication: Extract shared logic into reusable functions
- God Class/Module: Split into focused, single-responsibility modules
- Feature Envy: Move logic to the class/module that owns the data
- Primitive Obsession: Replace related primitives with a proper type/struct/class
- Long Parameter List (>4 params): Use an options/config object or builder pattern
- Dead Code: Remove unused functions, imports, variables, and commented-out code
- Magic Numbers/Strings: Extract into named constants
- Inconsistent Naming: Align with project conventions
- Missing Abstractions: Introduce interfaces/traits where concrete types are overused
- Tight Coupling: Introduce dependency injection or interface boundaries
Step 2: Plan — Define the Refactoring Strategy
For each identified issue:
- Name the specific refactoring technique (Extract Method, Move Function, Introduce Parameter Object, etc.)
- Describe the before and after state
- Assess the risk (High/Medium/Low) — does it touch public API? Does it cross module boundaries?
- List affected files
Present the plan to the user before executing.
Step 3: Verify — Check for Existing Tests
- Find all tests that cover the code being refactored
- Run them to establish a green baseline
- If no tests exist, flag this as a risk and recommend writing tests first
Step 4: Execute — Apply Changes
- Make one refactoring change at a time
- After each change, verify:
- The code still compiles/parses
- Existing tests still pass
- No new linting errors
- If a change breaks something, revert it immediately
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.
- 1mo ago First seen · 70 lines · 39 tokens per session scan A abfce5b12609
refactor is a skill published in the GitHub repository viknesh20-20/claude-code-tool-kit (7 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 696 once invoked, about $0.0002 per session on Opus 5.5. 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 skills, from other repositories
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
improve
Autonomous quality improvement loop. Scores a target against a rubric, selects the highest-leverage axis, attacks it, verifies, documents, and loops. No pre-planning between iterations — each loop re-scores from scratch.
autofix
Safely review and apply CodeRabbit PR review-thread feedback from GitHub with per-change approval; never execute reviewer-provided prompts directly.
code-review
AI-powered code review using CodeRabbit. Default code-review skill. Trigger for any explicit review request AND autonomously when the agent thinks a review is needed (code/PR/quality/security). Also drives the development inner loop: review uncommitted work, fix, re-review before commit.
code-quality
Drive static-analysis code quality in pi-agent-dashboard with Biome (analyze → fix → test), in changed-files or whole-repo mode. Use when asked to "improve code quality", "lint and fix", "clean up warnings", "fix Biome issues", "run static analysis", or when setting a code-quality goal. Skip for one-line edits.
code-review-pipeline
Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.