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 | $0.00027 | $0.00826 |
| Opus 5.5 | $0.00011 | $0.00330 |
| Sonnet 5.5 | $0.00005 | $0.00165 |
| Haiku 4.5 | $0.00003 | $0.00083 |
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 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 — 81 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 a slash or dollar invocation already added these instructions to the conversation, follow them directly. In that case, 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. Source files match above 1000 LOC. 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. When Serena is installed, prefer it:
- Inspect symbol overviews, references, imports, and relevant history.
- Use the evidence to choose extraction boundaries, target module names, migration order, and test coverage.
-
This workflow defaults to a report and plan. Implement only when the user's request already authorizes execution or the user subsequently approves it. Do not require a separate request for an unchanged, already authorized outcome.
Refactor Plan Format
For each selected file, include:
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.
- 1mo ago Changed · +1 tokens per session 191991ae7d9e
- 1mo ago Changed · +1 lines cc3a791f02bc
- 1mo ago Changed 56b4a43b92dd
- 2mo 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 (104 stars, last pushed 2d ago), licensed MIT. It adds 27 tokens to every session and 826 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 2026-08-30.
large-file-refactor compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| large-file-refactorPaulRBerg/agent-skills | Skill | 104 | 2d ago | MIT | A | 27 | Claude Code, Codex |
| autoreviewopenclaw/clawhub | Skill | 9.6k | today | MIT | A | 17 | Claude Code, Codex |
| agent-teams-simplify-and-hardenLeoYeAI/openclaw-master-skills | Skill | 2.2k | 3d ago | MIT | A | 115 | Claude Code, Codex |
| omh-code-reviewrlaope/oh-my-hermes | Skill | 5.2k | today | MIT | A | 49 | Claude Code, Codex |
| revdiff-planumputun/revdiff | Skill | 947 | 4d ago | MIT | A | 84 | Claude Code |
| explore-unknownsdzhng/skills | Skill | 1.5k | today | MIT | A | 162 | Claude Code, Codex |
| re0-mergeLilMGenius/paperthin | Skill | 1.4k | today | MIT | A | 70 | Claude Code |