Teamo Strategy

Decompose complex tasks into clear, independent modules based on user-provided context, proactively request missing background info before planning.

This skill appears to do what it says (decompose tasks and request missing context), but there are a few things you should consider before installing or using it: - Privacy of uploads: The skill explicitly encourages attaching documents (PDFs, CSVs, Word). Do not upload sensitive credentials, personal data, or proprietary secrets unless you trust the environment and have reviewed data handling policy. Prefer redacting secrets before upload. - Chain-of-thought instructions: The SKILL.md instructs the model to follow a detailed internal CoT workflow. That increases the chance the agent might reveal internal reasoning or make verbose, introspective outputs. Test outputs carefully to ensure no sensitive internal deliberation is leaked. - Resource use and recursion: The skill instructs spawning parallel calls to itself for sub-tasks. That can lead to high compute usage, long-running jobs, or runaway recursion. Limit the depth/parallelism when testing, and watch for unexpectedly large outputs (the document references very large word-count outputs). - Output sizing: The doc sets expectations for huge deliverables (tens of thousands of words) while forbidding explicit word-count discussion with the user. Be prepared to impose output-size or time limits when invoking this skill. - Testing: Try the skill with small, non-sensitive sample tasks first to observe behaviour (interaction prompts, parallel calls, and how attachments are handled). If you plan to enable autonomous invocation in production, monitor usage and rate limits closely. If these operational patterns are acceptable to you and you avoid uploading secrets, the skill is coherent with its purpose; otherwise proceed cautiously or request the author clarify recursion/parallelism and CoT handling.

Type: OpenClaw Skill Name: teamo-strategy Version: 0.1.0 The `teamo-strategy` skill's `SKILL.md` instructs the AI agent to proactively request and handle user-provided attachments (e.g., PDF, Word, CSV) containing potentially sensitive information like 'API documentation, or financial report PDFs'. It further instructs the agent to pass these attachments to sub-tasks during recursive delegation to itself or other instances of `teamo_strategy`. While these actions are aligned with the stated purpose of improving task accuracy, the explicit handling and transmission of user-uploaded files, combined with recursive self-delegation, represent meaningful high-risk behaviors for data exposure or resource management if not rigorously secured by the underlying platform. There is no evidence of intentional malicious behavior such as data exfiltration to unauthorized external endpoints, command execution, or persistence mechanisms.