PeerBerry SDK

Use this skill when assisting with FortressQuant's peerberry-sdk for PeerBerry investor automation, P2P lending education, and alternative-investment onboard...

This skill appears to be documentation and runtime guidance for a PeerBerry Python SDK, but the bundle does not include the actual SDK implementation (no src/ package files were provided) and the packaging metadata/versioning is inconsistent. Before installing or using it: - Do not paste credentials into any public chat. Use local, private execution. - Verify the true source of the package you will install (pip install peerberry-sdk): check PyPI and the GitHub repo referenced in pyproject.toml to ensure you are installing the intended project and version. Confirm author/maintainer identity and read the package code before installing. - Prefer installing into an isolated virtual environment. Inspect the installed package contents (site-packages) after install. - If you plan to run purchase/automation flows, keep DRY_RUN enabled initially and set conservative MAX_ORDERS; test read-only flows first. - The docs allow pointing the SDK at a header profile JSON file (header_profile_path / peerberry_sdk_HEADER_PROFILE). Only use that with files you control; do not point it at system files or shared secrets. What would raise confidence to benign: the skill including the actual src/ implementation, a matching package version and a trusted homepage/repository, or an explicit install spec that points to a verified release artifact (e.g., a GitHub release tarball from the disclosed repo). If you want, I can check PyPI/GitHub for 'peerberry-sdk' and compare the package contents and maintainers to what this skill claims.

Type: OpenClaw Skill Name: peerberry-sdk Version: 1.0.0 The peerberry-sdk skill bundle is a well-documented tool for interacting with the PeerBerry P2P lending platform. The provided files consist of comprehensive documentation, AI agent instructions (SKILL.md), and documentation generation scripts (docs/gen_api.py, docs/gen_client_reference.py). The SKILL.md and reference files (task-recipes.md, api-quickref.md) are specifically designed to guide the AI agent toward safe operations, explicitly mandating safety guards like DRY_RUN modes, order caps (MAX_ORDERS), and read-only initializations for financial transactions. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the logic is entirely consistent with the stated purpose of providing a programmable interface for investor automation.