Review Agent

Pre-meeting review coach for Lark/Feishu (or WeCom). Invoked when a Requester DMs their dedicated review-agent subagent with a draft, proposal, plan, or 1:1...

Key things to check before installing or running this skill: - Do not run install/update/patch scripts (install.sh / update.sh / feishu_seed_workspace_patch.py) on production systems until reviewed. These scripts clone code from a third‑party GitHub repo and apply a core patch to OpenClaw; review every line in those scripts and the patch file in a trusted environment. - Verify the upstream repository and the publisher identity. Confirm the GitHub repo (https://github.com/jimmyag2026-prog/review-agent-skill) is trustworthy and inspect commit history, recent changes, and install scripts for unexpected network calls or arbitrary command execution. - Audit scripts for network endpoints and secrets handling. Search the code for any hardcoded URLs, remote upload routines, or uses of open network sockets (e.g., dashboard-server.py), and confirm they point only to expected hosts. - Check for undeclared credential needs. The skill will need Lark/Feishu app scopes and OpenClaw gateway credentials to function; do not supply broad platform tokens blindly. Prefer scoped service accounts and rotate tokens after testing. - Sandbox first. Install and run the skill in an isolated test environment (VM/container) with no access to production secrets or tenant tokens, and simulate a minimal session to observe behavior, file writes, and outbound connections. - Review persona/profile files and templates. Since persona files are injected into LLM system prompts, inspect agent_persona.md, boss_profile.md and other templates for any instructions that could force the model to leak data or override system-level safeguards. - Disable automatic updates until you trust the source. Do not enable any auto-update behavior; prefer to pull updates manually after review. - If you must proceed in production, minimize scope: restrict Lark/Feishu app scopes to the least privilege needed, do not apply the core patch until reviewed, and backup OpenClaw core before applying any modifications. If you want, I can: (1) list specific files/lines to inspect next (install.sh, update.sh, feishu_seed_workspace_patch.py, scripts that call network), (2) scan the included Python scripts for obvious I/O/network calls to external hosts, or (3) produce a short sandbox test plan you can run safely.

Type: OpenClaw Skill Name: review-agent Version: 2.1.2 The skill bundle implements a complex 'Review Agent' with significant system-level interactions. While the logic appears aligned with its stated purpose, it exhibits high-risk behaviors including the use of subprocesses to execute external binaries (pdftotext, tesseract, whisper) on user-provided files in 'ingest.py', and it requires an invasive 'source patch' to the OpenClaw core platform (modifying node_modules) as described in 'POST_INSTALL.md'. Additionally, it handles sensitive API keys across multiple legacy and current configuration paths and performs automated network requests to GitHub and OpenRouter. These capabilities, particularly the platform patching, represent a significant security risk and high attack surface, though no clear evidence of intentional malice was found.