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 ashtonian/llm-init --skill refactorgit clone --depth 1 https://github.com/ashtonian/llm-initWrote 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/ashtonian/llm-init/refactor)<a href="https://agentmods.dev/skills/ashtonian/llm-init/refactor"><img src="https://agentmods.dev/badge/skills/ashtonian/llm-init/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/ashtonian/llm-init/refactor"><img src="https://agentmods.dev/badge/skills/ashtonian/llm-init/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 | $0.00014 | $0.01379 |
| Opus 5.5 | $0.00006 | $0.00552 |
| Sonnet 5.5 | $0.00003 | $0.00276 |
| Haiku 4.5 | $0.00001 | $0.00138 |
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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Refactoring Skill
Structured workflow for identifying refactoring opportunities, assessing impact, and executing safe refactors that preserve behavior. Produces a refactoring plan with before/after examples and generates task files for large refactors.
Workflow
Step 1: Identify Refactoring Opportunities
Scan the codebase for common refactoring signals:
| Signal | Detection Method |
|---|---|
| Code duplication | Search for repeated patterns across files (similar function signatures, copy-paste blocks) |
| High complexity | Functions exceeding 60 lines, deeply nested conditionals (>3 levels), high cyclomatic complexity |
| Code smells | Long parameter lists (>4 params), god objects, feature envy, primitive obsession |
| Naming issues | Inconsistent naming conventions, misleading names, abbreviations without context |
| Dead code | Unused exports, unreachable branches, commented-out code blocks |
| Tight coupling | Concrete type dependencies where interfaces should be used, circular imports |
| Missing abstractions | Repeated patterns that could be extracted into shared utilities or interfaces |
For each opportunity found, record:
- File and line range: Exact location
- Category: Which signal it matches
- Severity: High (blocks new features), Medium (increases maintenance cost), Low (cosmetic)
- Estimated effort: Small (< 1 hour), Medium (1-4 hours), Large (> 4 hours)
Output: Refactoring opportunity inventory sorted by severity then effort.
Step 2: Impact Analysis
For each candidate refactoring, assess:
- Blast radius: How many files/packages are affected?
- Test coverage: Are the affected areas well-tested? Check coverage reports.
- Active development: Is anyone currently working on these files? Check recent git history.
- Risk level: Could this break existing behavior?
Impact Matrix:
| Refactoring | Files Affected | Test Coverage | Risk | Priority |
|-------------|---------------|---------------|------|----------|
| Extract X | 3 | 85% | Low | High |
| Rename Y | 12 | 40% | Med | Medium |
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 · 150 lines · 14 tokens per session scan A f9fc17e8ecae
refactor is a skill published in the GitHub repository ashtonian/llm-init (2 stars, last pushed today), licensed MIT. It adds 14 tokens to every session and 1,379 once invoked, about $0.0001 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.
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