quill copilot-instructions.md

Repository instructions for Quill, including its product requirements, development commands, tests, formatting, linting, and type-checking rules. A monorepo is one repository containing multiple related parts, but the description does not say whether Quill is one.

In plain words
What is it for?
Finding the product requirements, setting up the Python environment, running focused or full tests, checking formatting and lint rules, and running strict type checks.
Why use it?
They give coding agents a shared reference for the intended design and the checks required before changes are accepted. They also provide faster test paths for day-to-day work.

Instructions file for GitHub Copilot

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 instructions/community-access/quill/copilot-instructions
Clone the repo
git clone --depth 1 https://github.com/Community-Access/quill

Made for: GitHub Copilot.

Per session 3,570 This file is loaded in full into every session.
When invoked 3,570 The same file — it is already loaded in full.
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 $0.03570 $0.03570
Opus 5 $0.01785 $0.01785
Sonnet 5 $0.00714 $0.00714
Haiku 4.5 $0.00357 $0.00357

Measured 3d ago against content hash be449c61bf14, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

quill copilot-instructions.md 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 3d 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.

.github/copilot-instructions.md · 264 lines

How it starts

The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Copilot instructions for this repository

Repository state

This repository contains the implementation source tree together with the product requirements document under docs/Product Requirement Documents and Specifications/QUILL-PRD.md and docs/QUILL-PRD.html.

When generating code or task plans, treat the PRD as the source of truth for intended architecture and conventions. For the detailed day-to-day command and invariant reference, read CLAUDE.md; keep this file as the concise, always-on guide.

Build, test, and lint commands

The project has a runnable test suite and CI gates. Use focused tests while developing, then run the narrowest applicable quality checks:

# Environment setup
uv python install 3.12
uv sync --all-extras
pre-commit install

# Fast test paths
pytest -m smoke -q
pytest tests\unit\path\to\test_file.py::test_name -q
pytest -q -n 8 --dist loadgroup

# Lint + strict type-check
ruff check .
ruff format --check .
mypy quill\core quill\io

# Optional suites
RUN_PERF=1 pytest -m perf -q
$env:QUILL_UIA_TESTS = "1"; pytest -m uia -q

tests/conftest.py forces quill.core.paths._DEV_BUILD = True and puts the pytest temp root under the user home directory. This is what makes per-test QUILL_DATA_DIR overrides safe; preserve it and use tmp_path for isolated persistence tests. The parallel command above serializes tests/unit/ui on one worker because wx, clipboard, hotkey, and screen-reader resources are process-global.

quill/core and quill/io are strict and wx-free. Keep mypy scoped to those layers; quill/ui is gradually typed. Before changing the UI dependency, note that wxPython is exactly pinned in pyproject.toml because screen-reader acceptance covers that tested build, not every upstream wx release.

High-level architecture (from PRD)

Quill is designed as a screen-reader-first Windows desktop app in Python + wxPython, with a strict separation between UI, core logic, I/O format handlers, platform bindings, and optional AI providers.

Read the full file on GitHub · 264 lines

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. 3d ago First seen · 264 lines · 3,570 tokens per session scan A be449c61bf14

Subscribe to this mod's changes

quill copilot-instructions.md is an instructions file published in the GitHub repository Community-Access/quill (43 stars, last pushed 3d ago), licensed MIT. It adds 3,570 tokens to every session, about $0.0178 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.

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