General
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CLAUDE
AGENTS.md
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General
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AG2 Beta Development Guidelines
Before opening a PR, read and follow `.github/AI_POLICY.md`.
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General
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Security Policy
Please email [email protected] with a description of the vulnerability, steps to reproduce, and any relevant details.
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AI Usage Policy
> This policy is adapted from [Ghostty's AI Policy](https://github.com/ghostty-org/ghostty/blob/main/AI_POLICY.md) with modifications for the Letta project.
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docs/contributing.md
generic skill
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.github/workflows/*.lock.yml linguist-generated=true merge=ours
generic skill
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General
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Security Policy
For a more in-depth look at our security policy, please check out our [Coordinated Vulnerability Disclosure Policy](https://openai.com/security/disclosure/#:~:text=Disclosure%20Policy,-Security%20is%20essential&text=OpenAI%27s%20coordinated%20vulnerability%20disclosure%20policy,expect%20from%20us%20
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lefthook.yml
assert_lefthook_installed: true
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General
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Optional local lefthook configuration
pre-commit:
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General
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typescript-sdk Review Conventions
Guidance for reviewing pull requests on this repository. The first three sections are
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General
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Troubleshooting Guide
This page collects common issues and setup tips encountered while working through the book.
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Generated files
docs/llms.txt
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globs:
- "*.md"
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Code-eval runners are Lambda handler test fixtures (Node + Python). They
scripts/code-eval-runners/
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Security Advisory: Malicious code in guardrails-ai 0.10.1
**Status:** Active. Package quarantined on PyPI. Tracking issue: [#1473](https://github.com/guardrails-ai/guardrails/issues/1473).
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yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json
language: "en-US"
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Monorepo Packages
| Package | npm name | Purpose |
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<div align="center" markdown="1">
<sup>Special thanks to:</sup>
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/css
/extensions
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extends: default
rules:
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@AGENTS.md
generic skill
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General
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Agent Instructions for vLLM
> These instructions apply to **all** AI-assisted contributions to `vllm-project/vllm`.
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General
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CLAUDE
AGENTS.md
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General
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Axolotl
Fine-tuning framework for LLMs. Config-driven: every training run is defined by a single YAML file.
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