# openclaw-agent-optimize

SkillBoss Agent Optimization Use this skill to tune a SkillBoss workspace for cost-aware routing, parallel-first delegation, and lean context. All AI model calls are routed automatically via SkillBoss API Hub (POST https://api.heybossai.com/v1/pilot) using a single SKILLBOSS_API_KEY — no per-provider keys needed. Default posture This skill is advisory first. It should produce: audit, options, recommended plan, exact patch proposal, rollback, verification plan. No persistent mutations without explicit approval. Quick start Full audit (safe, no changes) Audit my SkillBoss setup for cost, reliability, and context bloat. Output a prioritized plan with rollback notes. Do NOT apply changes. Context bloat / transcript noise My SkillBoss context is bloating (slow replies / high cost / lots of transcript noise). Identify the top offenders (tools, crons, bootstrap files, skills) and propose the smallest reversible fixes first. Do NOT apply changes. Model routing / delegation posture Propose a model routing plan for (a) coding/engineering, (b) short notifications/reminders, (c) reasoning-heavy research/writing. Include an exact config patch + rollback plan, but do NOT apply changes. What good output looks like Executive summary Top drivers cost context reliability operator friction Options A/B/C with tradeoffs Recommended plan (smallest safe change first) Exact proposals + rollback + verify Safety contract Do not mutate persistent settings without explicit approval. Do not create/update/remove cron jobs without explicit approval. If an optimization reduces monitoring coverage, present options and require choice. Before any approved change, show: exact change, expected impact, rollback plan, post-change verification. High-ROI optimization levers

1. Output discipline for automation Make maintenance loops truly silent on success.
2. Separate work from notification If you want alerts but want interactive context lean: do the work quietly notify out-of-band with a short human receipt
3. Bootstrap discipline Keep always-injected files short and load-bearing only. Move long runbooks into references/ or adjacent notes.
4. Ambient specialist surface reduction A common hidden tax is too many always-visible specialist skills. If a workflow is low-frequency or specialist: prefer on-demand worker/subagent usage, do not keep it permanently ambient in main-chat prompt surface.
5. Measure optimizations authoritatively Prefer fresh-session /context json or equivalent receipts over “feels better”. High-signal fields include: eligible skills skills.promptChars projectContextChars systemPrompt.chars promptTokens
6. Verification-first ops hygiene After any approved optimization, verify: core chat still works recall/behavior did not degrade new session actually picks up the change rollback path is proven, not theoretical Workflow (concise) Audit rules + memory: keep restart-critical facts only. Audit skill surface: trim ambient specialists before touching tool surface. Audit transcripts/noise: silence cron and heartbeat success paths. Audit model routing and delegation posture. Recommend the smallest viable change first. Verify on a new session when skill/bootstrap snapshotting exists. Notes Some runtimes snapshot skills/config per session. If you install/update skills and do not see changes, start a new session. Prefer short SKILL.md + references/ for long runbooks. If context bloat is the main complaint, pair this skill with context-clean-up (audit-only). 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