ruff-linting

Project rules for using Ruff, a Python tool that checks code style and common mistakes. They describe the command for automatically fixing lint errors and how to document justified exceptions.

In plain words
What is it for?
Use them when checking Python code, applying Ruff fixes, repeating checks until clean, or adding rule-specific ignores with reasons.
Why use it?
They make linting consistent and prevent contributors from hiding legitimate exceptions without explaining them.

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/technickai/claude_telemetry/ruff-linting
Clone the repo
git clone --depth 1 https://github.com/TechNickAI/claude_telemetry

Made for: Cursor.

Per session 4 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 227 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00004 $0.00227
Opus 5 $0.00002 $0.00113
Sonnet 5 $0.00001 $0.00045
Haiku 4.5 $0.00000 $0.00023

Measured 2d ago against content hash fbc74bfcdeb9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ruff-linting scanned grade A with 1 finding 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 2d 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

process = subprocess.Popen(["pbcopy"], stdin=subprocess.PIPE) # ruff: ignore=S603,S607 - Needed for clipboard
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.cursor/rules/ruff-linting.mdc · 31 lines

What it actually says

Ruff Linting

We use ruff for linting. If there are lint errors, or if the user says "fix lint errors":

  1. Run: ruff check --fix --unsafe-fixes
  2. Repeat until all errors are fixed

Using Targeted Ignores

For legitimate exceptions, use targeted ignores with specific rule codes and explanations:

# Include the rule code and why we're ignoring it
process = subprocess.Popen(["pbcopy"], stdin=subprocess.PIPE)  # ruff: ignore=S603,S607 - Needed for clipboard

result = eval(user_formula)  # ruff: ignore=S307 - Safe: formula validated by parser

api_key = os.getenv("SECRET_KEY")  # ruff: ignore=S105 - Environment variable, not hardcoded

Use # ruff: ignore=RULE_CODE format. Multiple rules: # ruff: ignore=S603,S607

When we fix all errors, celebrate! Clean code feels good. 🌟

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. 2d ago First seen · 31 lines · 4 tokens per session scan A fbc74bfcdeb9

Subscribe to this mod's changes

ruff-linting is a cursor rule published in the GitHub repository TechNickAI/claude_telemetry (30 stars, last pushed 10mo ago), licensed MIT. It adds 4 tokens to every session and 227 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.