python-proper-exception-chaining

A Python rule for preserving the original cause of an error when raising another exception, using raise from or raise from None.

In plain words
What is it for?
Use it when catching one Python exception and raising a different one, especially when reviewing or fixing error-handling code.
Why use it?
It makes error handling clearer by showing where an error came from or intentionally hiding the underlying cause.

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/gmoncor/agentic-engineering-framework/python-proper-exception-chaining
Clone the repo
git clone --depth 1 https://github.com/gmoncor/agentic-engineering-framework

Made for: Cursor.

Per session 741 This file is loaded in full into every session.
When invoked 741 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00741 $0.00741
Opus 5 $0.00370 $0.00370
Sonnet 5 $0.00148 $0.00148
Haiku 4.5 $0.00074 $0.00074

Measured yesterday against content hash 6f7a29e54bb7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-proper-exception-chaining 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 yesterday.

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/python-proper-exception-chaining.mdc · 93 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. yesterday First seen · 93 lines · 741 tokens per session scan A 6f7a29e54bb7

Subscribe to this mod's changes

python-proper-exception-chaining is a cursor rule published in the GitHub repository gmoncor/agentic-engineering-framework (5 stars, last pushed 3d ago), with no licence file. It adds 741 tokens to every session, about $0.0037 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 2026-08-31.