Skill flagged — suspicious patterns detected
ClawHub Security flagged this skill as suspicious. Review the scan results before using.
i-am
v0.0.5Simple personality analysis. Consolidated SKILL.md with embedded code. AI-guided installation and IM-adaptive file sending.
⭐ 1· 260·0 current·0 all-time
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
Reading past user messages and building a personality model aligns with a 'personality analysis' skill. However, the description also mentions 'IM-adaptive file sending' which is not justified or detailed in the SKILL.md excerpt. Creating changelogs, temp files, and backups in the skill workspace is consistent, but automated background scheduling and adaptive sending behavior expand the scope beyond simple analysis.
Instruction Scope
The SKILL.md tells the agent to scan ~/.openclaw/agents/main/sessions for all user messages (initial run: unbounded historical data), apply regexes to extract content, and filter/verify senders. Those instructions give the agent broad discretion to access and parse potentially sensitive conversation logs and to automatically create and modify cron task configuration. The document does not show explicit, user-facing consent prompts for accessing stored conversations or for sending generated USER.md files via IM channels.
Install Mechanism
There is no install spec or external code download; this is instruction-only. That lowers supply-chain risk because no additional binaries or archives are fetched or written beyond files the skill itself creates under the user's home directory.
Credentials
No environment variables or external credentials are requested, which is appropriate. However, the instructions access sensitive local data (conversation session logs) and configuration files under ~/.openclaw and propose creating/modifying cron task JSON. Accessing entire session histories and unbounded message sets is a high-sensitivity operation relative to a 'simple' personality analysis and is not scoped or limited in the document.
Persistence & Privilege
The skill will create workspace files, ChangeLog.md backups, and (optionally, by default) add scheduled tasks to the user's cron-tasks.json to run twice daily. While 'always: false', the persistent cron scheduling gives the skill ongoing privilege to re-run analyses and re-read session data without a fresh explicit user action each time — this increases the blast radius if the behavior is undesired.
What to consider before installing
Before installing or enabling this skill, consider the following:
- This skill reads your OpenClaw conversation session files (~/.openclaw/agents/main/sessions) and may load unbounded historical messages on first run — if you don't want your past conversations analyzed or included, do not install.
- The skill proposes creating/modifying a cron-tasks.json entry to run automatically twice daily. If you prefer no background activity, choose the manual mode and verify cron entries before enabling them.
- The description references 'IM-adaptive file sending' and the instructions parse message metadata; clarify exactly where generated/backup files (USER.md, ChangeLog.md) will be sent, to whom, and whether any data will leave your machine or be posted externally. If this is not explicit, assume it could be transmitted and avoid installing.
- Ask the publisher for a minimal, auditable runtime flow: explicit consent prompts before first data access, a configurable message-history limit, a dry-run that shows extracted messages before analysis, and an opt-out for automatic scheduling.
- If you still want the functionality: run in manual mode, inspect the created files and cron-tasks.json yourself, and consider running the skill in a restricted/testing account or environment first.
My confidence is medium because the skill is internally coherent for its stated goal, but the combination of broad local data access, automatic scheduling, and implied adaptive sending is disproportionate without clearer consent and data-exfiltration controls. Additional information that would raise confidence toward 'benign': explicit, user-visible consent prompts; a clear, auditable description of any sending behavior (endpoints/recipients); and configurable limits on how much history is read on first run.Like a lobster shell, security has layers — review code before you run it.
latestvk97ct4b5c1bgxaaatk7y7a6e2s82twj3
License
MIT-0
Free to use, modify, and redistribute. No attribution required.
