refactors

refactors is a cursor rule for Cursor from sisig-ai/doctor. It costs 6 tokens per session (87 once invoked), scanned A, original, MIT.

A coding rule for refactoring code or adding new logic.

In plain words
What is it for?
Guiding code changes that alter existing behaviour, including running tests with the project's virtual-environment Python.
Why use it?
It reminds the agent to run the test suite after changes and to fix logic problems or update tests when needed.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/sisig-ai/doctor/refactors
Clone the repo
git clone --depth 1 https://github.com/sisig-ai/doctor

Made for: Cursor.

Wrote 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.

agentmods badge for refactors

README.md
[![agentmods](https://agentmods.dev/badge/rules/sisig-ai/doctor/refactors.svg)](https://agentmods.dev/rules/sisig-ai/doctor/refactors)
Your own site
<a href="https://agentmods.dev/rules/sisig-ai/doctor/refactors"><img src="https://agentmods.dev/badge/rules/sisig-ai/doctor/refactors.svg" alt="Measured on agentmods" height="20"></a>
Per session 6 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 87 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00006 $0.00087
Opus 5 $0.00003 $0.00044
Sonnet 5 $0.00001 $0.00017
Haiku 4.5 $0.00001 $0.00009

Measured 4d ago against content hash d14da00b1590, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

refactors 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 4d 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.

.cursor/rules/refactors.mdc · 9 lines

What it actually says

  • Run tests after refactor/implementation is completed, ensuring they pass, and add news tests as necessary
  • To run the tests, do pytest (making sure that you are using .venv/bin/python)
  • When tests fail, adjust them according to the changes in code OR fix the code if it's a logic issue
Changes

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.

  1. 4d ago First seen · 9 lines · 6 tokens per session scan A d14da00b1590

Subscribe to this mod's changes

refactors is a cursor rule published in the GitHub repository sisig-ai/doctor (462 stars, last pushed 1y ago), licensed MIT. It adds 6 tokens to every session and 87 once invoked, about $0.0000 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.