Cross-Axis Analysis Framework. Use when you need to systematically research an unfamiliar domain, product, company, or technology concept through longitudina...

This skill is a template-driven research method and appears internally consistent. Before using it, consider: (1) privacy — the research target text you fill into the prompt will be sent to whatever LLM the agent uses (OpenAI/Anthropic/Google/etc.), so avoid inserting confidential or sensitive material; (2) cost & latency — the 'deep' version asks for very long outputs (10k–30k words) which may be expensive and slow with some models; (3) factual verification — LLM outputs can hallucinate, so independently verify important claims; (4) autonomy settings — if you are concerned about the agent initiating long-running or costly LLM calls on its own, restrict autonomous invocation or monitor model usage. Other than those operational considerations, there are no hidden installs, requested credentials, or unrelated file accesses.

Type: OpenClaw Skill Name: cross-axis-analysis Version: 1.1.0 The skill bundle is a research framework designed to guide an AI agent through longitudinal and cross-sectional analysis of products or technologies. It consists entirely of instructional Markdown and prompt templates (SKILL.md and references/prompt-template.md) without any executable code, shell commands, or network requests. There are no indicators of data exfiltration, malicious prompt injection, or unauthorized access.