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 PaulRBerg/agent-skills --skill large-file-refactorgit clone --depth 1 https://github.com/PaulRBerg/agent-skillsWrote 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/paulrberg/agent-skills/large-file-refactor)<a href="https://agentmods.dev/skills/paulrberg/agent-skills/large-file-refactor"><img src="https://agentmods.dev/badge/skills/paulrberg/agent-skills/large-file-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/paulrberg/agent-skills/large-file-refactor"><img src="https://agentmods.dev/badge/skills/paulrberg/agent-skills/large-file-refactor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00026 | $0.00782 |
| Opus 5 | $0.00013 | $0.00391 |
| Sonnet 5 | $0.00005 | $0.00156 |
| Haiku 4.5 | $0.00003 | $0.00078 |
Grade A, and why
large-file-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 10d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Large File Refactor
This skill is coordination-exempt: skip the ai-coord gate for its declared work.
If these instructions are already present in the conversation from a slash or dollar invocation, follow them directly; do not invoke this skill again through a skill tool.
Use LOC thresholds to discover candidates, then decide whether a split is justified by cohesion, coupling, ownership, and change risk. Test files use a relaxed 2000 LOC discovery threshold.
Arguments
path: Optional file or directory to scan. Default: current working directory.--include-generated: Include generated, vendored, dependency, and build-output paths that are skipped by default.
Workflow
-
Resolve the skill directory, then run the helper from the target repository:
uv run "<skill-dir>/scripts/large-file-refactor.py" [path] [--include-generated] -
Preserve the helper's Markdown table as the exhaustive report. Do not omit matching rows, even when the refactor plan only covers a subset.
-
If the helper reports no threshold matches, stop after the report. A match is a candidate, not proof that the file should be split.
-
Draft a refactor plan for the 3 largest files only, unless the user explicitly requested another count.
-
For each candidate, rank split value by mixed responsibilities, change frequency/risk, coupling, and testability. Use whichever semantic symbol/reference tooling is available; prefer Serena when installed:
- Inspect symbol overviews, references, imports, and relevant history.
- Use the evidence to choose extraction boundaries, target module names, migration order, and test coverage.
-
Do not implement the refactor unless the user separately asks for execution.
Refactor Plan Format
For each selected file, include:
- Current role: the file's apparent responsibility and why line count is a symptom.
- Semantic pass: the exact symbol/reference/history inspection to run before moving code.
- Split proposal: 2-5 target modules or files with responsibilities.
- Migration order: small, reviewable steps that preserve public behavior.
- Verification: narrow tests, type checks, builds, or smoke checks that prove the split.
What ships with it
2 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.
- 10d ago First seen · 80 lines · 26 tokens per session scan A 2ac6250fe5c4
large-file-refactor is a skill published in the GitHub repository PaulRBerg/agent-skills (70 stars, last pushed yesterday), licensed MIT. It adds 26 tokens to every session and 782 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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