X Algorithm Optimization

Provides actionable insights into X's For You feed algorithm to optimize content for engagement by predicting and maximizing key user interaction types.

This skill appears coherent and self-contained: it documents inferred mechanics of X's ranking pipeline and includes a local Python heuristic evaluator. Before installing or running it, consider the following: 1) Inspect scripts/evaluate_post.py yourself — it runs locally and uses only string heuristics, but you should confirm it won't call external network endpoints (it doesn't). 2) Do not feed the skill private or internal X platform data (weights, internal analytics) unless you have explicit authorization and understand legal/ToS implications — the docs mention optional refinement with such data but do not require it. 3) Treat the recommendations as heuristics/inferences, not guaranteed behavior; validate any strategy with your own analytics. 4) Confirm license and provenance if you plan to redistribute (the README claims the source repo is Apache 2.0). If you want extra assurance, request a manual code review focused on any future changes that add network or credential use.

Type: OpenClaw Skill Name: x-algorithm-optimization Version: 1.0.0 The skill bundle is a comprehensive knowledge base and toolset for optimizing content for the X (Twitter) algorithm. The Python script (scripts/evaluate_post.py) is a safe text analyzer that uses basic regex and keyword matching to provide heuristics-based feedback; it contains no network calls, file system access, or dangerous execution sinks like eval() or os.system(). The documentation (SKILL.md, AGENT_USAGE.md) is strictly aligned with the stated purpose of social media strategy and does not contain any prompt injection attempts or instructions to exfiltrate data.