arshai: Instructions file for Claude Code

CLAUDE.md

arshai CLAUDE.md is an instructions file for Claude Code from felesh-ai/arshai. It costs 4,966 tokens per session, scanned A, original, MIT.

Repository instructions for developing Arshai, a Python framework for building AI applications with separated layers and interfaces. It documents the project's commands, testing, formatting, type-checking, security checks, and documentation build.

In plain words
What is it for?
Use it when changing Arshai code, running unit or integration tests, checking coverage, formatting Python files, running mypy or security scans, and building Sphinx documentation.
Why use it?
It gives coding agents and developers the repository's expected workflow and quality checks in one place. This reduces guesswork about how to install dependencies, test changes, and validate the project.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: mentions CLAUDE.md; mentions Claude Code.

This is felesh-ai/arshai's own configuration. It tells Claude Code how to work on arshai itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything arshai configures →

Reuse

Borrowing it

Nothing to install: this file belongs to felesh-ai/arshai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/felesh-ai/arshai/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/felesh-ai/arshai

Made for: Claude Code.

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Per session 4,966 This file is loaded in full into every session.
When invoked 4,966 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.04966 $0.04966
Opus 5.5 $0.01986 $0.01986
Sonnet 5.5 $0.00993 $0.00993
Haiku 4.5 $0.00497 $0.00497

Measured 2mo ago against content hash 954a29617e21, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

arshai CLAUDE.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 2mo 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.

CLAUDE.md · 585 lines

How it starts

The opening of the file, as written. The whole thing — 585 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Development Commands

Testing

poetry run pytest                    # Run all tests
poetry run pytest tests/unit/        # Run unit tests only
poetry run pytest tests/integration/ # Run integration tests only
poetry run pytest --cov=arshai      # Run tests with coverage

Code Quality

poetry run black .                  # Format code
poetry run isort .                  # Sort imports
poetry run mypy arshai/             # Type checking
poetry run bandit -r arshai/        # Security analysis
poetry run safety check             # Check dependencies for vulnerabilities

Documentation

cd docs_sphinx && make html  # Build Sphinx documentation

Package Management

poetry install           # Install all dependencies
poetry install -E all    # Install with all optional dependencies (redis, milvus, flashrank)
poetry install -E docs   # Install documentation dependencies

Architecture Overview

Arshai is an AI application framework built on clean architecture principles with interface-driven design. The system follows a layered approach with clear separation of concerns:

Core Layers

  1. Application Layer: Workflows and Agents that orchestrate business logic
  2. Domain Layer: Memory, Tools, and LLM integrations that handle core functionality
  3. Infrastructure Layer: Document processing, vector storage, and external integrations

Key Components

  • Agents (arshai/agents/): Intelligence units that process user interactions
  • Workflows (arshai/workflows/): Orchestrate complex multi-step processes with state management
  • Memory (arshai/memory/): Handle conversation context and state persistence
  • Tools (arshai/tools/): External capabilities that extend agent functionality
  • LLMs (arshai/llms/): Language model integrations with unified interface
  • Factories (arshai/factories/): Component creation and dependency injection

Read the full file on GitHub · 585 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. 2mo ago First seen · 585 lines · 4,966 tokens per session scan A 954a29617e21

Subscribe to this mod's changes

arshai CLAUDE.md is an instructions file published in the GitHub repository felesh-ai/arshai (24 stars, last pushed 26d ago), licensed MIT. It adds 4,966 tokens to every session, about $0.0199 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 2026-08-30.

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