Ae1
- Category
- analysis-evasion
- Confidence
- 100% confidence
- Finding
Referenced artifact was not completely inspected
- Content
md python scripts/coach.py add "Build something cool" --type idea --importance important
Security audit
Security checks for vulnerabilities and agentic risk
The skill is a coherent idea manager that stores notes locally and uses user-triggered GitHub commands, with no artifact-backed evidence of hidden or malicious behavior.
Before installing, treat stored idea content as local plaintext data and review it before syncing to GitHub, especially when using public repositories or issue creation. Use the GitHub commands only when you intend to let the skill act through your authenticated gh account.
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
Referenced artifact was not completely inspected
python scripts/coach.py add "Build something cool" --type idea --importance important
The concept includes automated morning checks, overdue nudges, and weekly summaries, but it does not specify any explicit user consent flow, disclosure, or easy opt-out before ongoing reminders are sent. This creates a privacy and user-safety risk because the system may retain behavioral data and initiate outreach unexpectedly, potentially exposing sensitive personal project information or causing unwanted notifications.
The technical design documents persistent local storage, per-entry interaction logs, cron-based automation, and memory integration across conversations without a corresponding privacy notice, consent model, retention policy, or access controls. Because the stored content includes ideas, problems, challenges, and progress history, this can expose sensitive personal or work-related information and enable broader profiling across sessions.
Commands invoke sudo or root privileges. Verify this elevated access is necessary and justified.
brew install gh
# Linux
sudo apt install gh
# Then authenticate
gh auth login
The skill describes capabilities that read/write local files and invoke shell-based workflows (python scripts/coach.py ..., gh CLI) but does not declare any explicit tool scope or permissions boundary. That omission increases the chance an agent or user enables the skill without understanding its local-system and command-execution reach, which can lead to unintended file modification or command execution in a higher-privilege environment.
The GitHub integration advertises actions that create repositories and sync issues to a remote service, including optional public repo creation, but it does not clearly warn that idea contents may be transmitted off-device or become publicly visible. In this skill's context, users may store sensitive project ideas or internal problem statements, so silent or poorly signposted publication/synchronization creates a meaningful confidentiality risk.
The skill's natural-language logic classifies all content as either German or English based on simple heuristics, with no user opt-in or way to select another language. This creates a locale policy issue because language behavior is forced implicitly rather than offered as a user choice or documented as a region-specific limitation.
subprocess module calls execute external commands. Without careful input validation, this enables command injection.
def run_gh_command(args: List[str]) -> Dict[str, Any]:
"""Run a gh CLI command and return result."""
try:
result = subprocess.run(
["gh"] + args,
capture_output=True,
text=True,
The markdown describes that ideas are stored in ~/.openclaw/idea-coach/ideas.json, but it does not provide a user-facing warning that the skill persists potentially sensitive idea content to disk. Because this file may contain private plans or problem statements, the description should clearly disclose local data retention behavior.
No suspicious patterns detected.