How can you optimize OpenClaw's context window usage across a session with many available skills?

• Rely on selective skill injection rather than manually forcing every skill into context, since OpenClaw already avoids injecting irrelevant skills by default
• Prune unused or rarely-needed skills from an agent's workspace rather than leaving every ever-installed skill discoverable
• Use multi-agent separation so a given agent only has the specific skills relevant to its role, reducing how many candidate skills the runtime has to consider per turn
• Keep SKILL.md instructions concise, since a bloated manifest for even a relevant, correctly-injected skill still consumes more tokens than necessary
• Monitor session transcripts for signs that irrelevant skill content is creeping into context, which shows up as degraded tool selection or unexpectedly high token usage

Most of these optimizations lean on the same idea driving OpenClaw's own skill-injection design, only surface what a given turn actually needs, rather than defaulting to maximal visibility for every capability the agent could theoretically use.