Secrets management for AI agents. Never expose your API keys again.

What to check before installing or using this skill: - Master key handling: inspect src/core/crypto.ts and the init flow. The init template writes a 'masterKey' into ~/.janee/config.yaml. If the master key is stored in the same file as the encrypted credentials, encryption provides no protection — a compromise of that file yields immediate key exposure. Require the author to explain where the master key is stored and to use a proper OS-level key store (e.g., macOS Keychain, Windows DPAPI, Linux kernel keyring) or at minimum keep the master key separate and not in the same plaintext config. - Binary provenance: the OpenClaw plugin spawns a subprocess by executing the 'janee' binary. The registry metadata did not declare a required binary; ensure you actually install the npm package from a trusted source and verify the package contents (and checksums) before running. A malicious 'janee' binary would run as your user. - Audit the code that performs decryption and network access (src/core/* and MCP server code). Confirm network endpoints and any optional LLM integration do not leak secrets to third-party services. The template shows optional LLM provider configuration that can read an env var (e.g., OPENAI_API_KEY) — if you enable such features, be explicit about required env vars and trust boundaries. - File permissions and logs: the code sets config and logs directories with 0700/0600 modes — good practice. Still review where logs are written (~/.janee/logs) as they contain request metadata and may include agent-provided 'reason' text. Ensure logs do not accidentally include plaintext keys. - Least privilege and policies: the rule/policy system appears coherent (deny-before-allow), but test it thoroughly (unit tests included). For sensitive services, prefer narrow capabilities and require human approval (requiresReason) and consider running Janee in an isolated account or container to limit blast radius. - If you cannot confirm the masterKey handling and binary provenance, treat the project as untrusted. Ask the author/maintainer to clarify and fix: (1) do not store the master decryption key in the same config file as ciphertext, (2) declare the required binary/runtime in metadata, and (3) document network endpoints and any optional external services. Confidence: high that these inconsistencies are real from the provided sources; resolving them would change the assessment to benign if the master key storage and binary provenance issues are fixed and documented.

Type: OpenClaw Skill Name: janee Version: 0.1.2 The OpenClaw AgentSkills skill bundle for Janee is designed as a security tool for AI agents, focusing on secrets management and API access control. It encrypts API keys at rest, prevents agents from directly accessing keys, enforces path-based access policies, and maintains a full audit log of all API requests. The code demonstrates strong security practices, including the use of AES-256-GCM encryption for secrets, restrictive file permissions (0o600/0o700) for configuration and logs in `~/.janee/`, and safe URL construction to prevent injection. The `SKILL.md` and `README.md` documentation clearly outlines these security features and does not contain any instructions that could lead to prompt injection or malicious agent behavior. All network and file access is directly aligned with its stated purpose of securely proxying API calls.