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 irahardianto/awesome-agv --skill refactorgit clone --depth 1 https://github.com/irahardianto/awesome-agvWrote 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/irahardianto/awesome-agv/refactor)<a href="https://agentmods.dev/skills/irahardianto/awesome-agv/refactor"><img src="https://agentmods.dev/badge/skills/irahardianto/awesome-agv/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/irahardianto/awesome-agv/refactor"><img src="https://agentmods.dev/badge/skills/irahardianto/awesome-agv/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 | $0.00038 | $0.01224 |
| Opus 5.5 | $0.00015 | $0.00490 |
| Sonnet 5.5 | $0.00008 | $0.00245 |
| Haiku 4.5 | $0.00004 | $0.00122 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Refactor Skill
Entry-point guard: This is a user-invoked command skill (
/refactor). If you are a spawned subagent, do NOT execute this skill — return to your assigned scope card.
Purpose
Safely restructure existing code while preserving behavior. Uses a different mindset than greenfield feature development: understand first, then change structure.
Requirement Elicitation
Determine refactoring source before proceeding:
Path A — Human-Specified
User provides a specific, actionable target:
- ✅
/refactor extract storage interface in task feature - ✅
/refactor split user handler into separate auth handler - ✅
/refactor migrate callbacks to async/await in notification service→ Proceed directly to Phase 1
Path B — Tool-Driven
User references a static analysis tool as the requirement source:
- ✅
/refactor from-deepsource— read DeepSource MCP findings - ✅
/refactor from-clippy— parsecargo clippyoutput - ✅
/refactor from-lint— parse linter output (ESLint, golangci-lint, ruff) → Parse tool findings → present summary → user approves scope → proceed to Phase 1
Supported tools:
| Tool | Integration |
|---|---|
| DeepSource MCP | Read findings via deepsource MCP tools |
| cargo clippy | Parse cargo clippy --message-format json |
| golangci-lint | Parse golangci-lint run --out-format json |
| ESLint | Parse npx eslint . --format json |
| ruff | Parse ruff check . --output-format json |
| SonarQube | Read via API if available |
Path C — Discovery
User doesn't know what to refactor, or provides vague request:
- ✅
/refactor discover— audit first, then refactor - ❌
/refactor apps/backend— too vague - ❌
/refactor improve code quality— what specific issue? → Multi-agent mode (/workflow-team): Dispatch SCOUT(@scout + @reviewer, code smell audit) → Single-agent mode: Run/auditon the target area first, then use findings as input → Present findings → user approves scope → proceed to Phase 1
Vague request without path → "Run /refactor discover to find issues, or specify a target like /refactor extract storage interface in task feature."
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 · 119 lines · 38 tokens per session scan A 5eb7b7d0ad8b
refactor is a skill published in the GitHub repository irahardianto/awesome-agv (156 stars, last pushed 5d ago), licensed MIT. It adds 38 tokens to every session and 1,224 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 2026-10-15.
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Post-merge UAT verification workflow. Walks JIRA reproduce steps, performs comparative audits (Before/After), attaches evidence to JIRA, and transitions status on PASS.
common-subagent-driven-development
Execute multi-task implementation plans by dispatching a fresh implementer subagent per task with independent review gates. Use when implementing plans, executing multi-task PRs, or transitioning from planning to implementation.
implement-feature
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common-tdd
Guides quality-first TDD for new behavior, bug fixes, and test changes. Selects the smallest test layer, proves a distinct regression risk, and runs bounded RED-GREEN-REFACTOR verification.