Call Geo Agent

AdvisoryAudited by Static analysis on Apr 30, 2026.

Overview

No suspicious patterns detected.

Findings (0)

Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.

What this means

A code-capable tool may be used to generate a local or attached HTML file for the project.

Why it was flagged

The skill instructs the agent to use a Python execution-capable tool to create an HTML deliverable. This is disclosed and scoped to the project dashboard, with no packaged code or unrelated execution shown.

Skill content
**工具**:`python_executor` ... **任务**:生成一个名为“xx品牌GEO项目看板.html”的交互式HTML文件
Recommendation

Review generated files before opening or sharing them, especially interactive HTML outputs.

What this means

Brand or product details supplied to the skill may be shared with several model agents during content generation.

Why it was flagged

The workflow explicitly passes user-provided product information and prompt context to multiple named writer agents/providers, but the artifact does not define data-retention or boundary controls for those agents.

Skill content
调用`geo-call-gemini-2-5-pro-agent``geo-call-gpt-5-agent``geo_call_claude_sonnet_4_agent``geo-call-claude-4-1-opus-thinking`,将用户上传附件或者描述中的产品相关信息、目标优化prompt、各平台的范文原文URL给到相应的写手。
Recommendation

Do not provide confidential product plans, private customer data, or unreleased materials unless those downstream agent/provider data policies are acceptable.

What this means

Project details and model-returned results may remain in persistent wiki/log artifacts after the task completes.

Why it was flagged

The workflow persists project actions, prompts, external-tool results, URLs, and generated content into wiki/log documents. This is expected for a project workflow, but it stores potentially sensitive or untrusted context for later reuse.

Skill content
创建”xx品牌GEO项目执行日志“,后续你按照工作流执行的关键动作和结果都不断追加在日志中。
Recommendation

Review the generated logs and wiki documents, remove sensitive details if needed, and avoid treating stored external-model output as verified without human review.