How do I install the Openclaw Agent Token Optimizer skill?

Run npx skillmds@latest add tomevault-io/openclaw-agent-token-optimizer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Openclaw Agent Token Optimizer safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Openclaw Agent Token Optimizer?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Openclaw Agent Token Optimizer free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Openclaw Agent Token Optimizer?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Openclaw Agent Token Optimizer by tomevault-io

Name: Openclaw Agent Token Optimizer
Author: tomevault-io

Openclaw Agent Token Optimizer

Optimize an OpenClaw agent setup (model routing, context management, delegation, rules, memory). Use when asked about optimizing agents, improving OpenClaw setup, or agent best practices. Use when this capability is needed.

tomevault-io Updated Sep 21, 2026

File contents

OpenClaw Agent Optimization

Use this skill to tune an OpenClaw workspace for cost-aware routing, parallel-first delegation, and lean context.

Workflow (concise)

Audit rules + memory: ensure rules are modular/short; memory is only restart-critical facts.
Model routing: confirm tiered routing (lightweight / mid / deep) aligns with live config.
Context discipline: apply progressive disclosure; move large static data to references/scripts.
Delegation protocol: parallelize independent tasks; use sub-agents for long/isolated work.
Heartbeat optimization: treat heartbeat as control-plane; move heavy checks to isolated cron/scripts; offer profiles A/B/C and require user choice if removing checks.
Safeguards: add anti-loop + budget guardrails; prefer fallbacks over retries.

References

references/optimization-playbook.md
references/model-selection.md
references/context-management.md
references/agent-orchestration.md
references/cron-optimization.md
references/heartbeat-optimization.md
references/memory-patterns.md
references/continuous-learning.md
references/safeguards.md

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