the gen z liminal horror thing is so funny to me. i can’t get over the idea that for them the scariest thing imaginable is a circuit city

JUST IN: More than 30 major Seattle companies, including Microsoft, Costco, & Starbucks, sign letter demanding action from Mayor Katie Wilson over the city’s deteriorating public safety.

I’ve accumulated a lot of recurring tasks in my @NousResearch Hermes instance. Eventually I couldn’t tell which jobs were still useful, which ran too often, or which were spending an expensive model on work that should’ve been a script. I audited my whole set of scheduled tasks and the estimates showed an embarrassing amount of wasted tokens I should've caught. Model choice was part of it but there were some bigger fixes in deleting obselete/dupe jobs, right sizing the schedules, narrowing tool access and even deciding if "no-agent" mode should be used. INITIAL AUDIT PROMPT: --- Audit every scheduled cron job in this Hermes profile. This is a read-only review: do not pause, edit, remove, create, or run any job. For each job, inspect its: - purpose and prompt - schedule - recent execution history and failures - delivery behavior - attached skills and enabled toolsets - scripts, monitors, and change-detection logic - continuity and context settings - model, provider, and reasoning configuration where visible For each job, recommend: 1. Keep, pause, consolidate, or remove. Flag obsolete, duplicate, consistently failing, or low-value jobs. 2. A right-sized schedule based on urgency, source update frequency, and cost. Call out collisions, unnecessary polling, and noisy delivery. 3. The cheapest reliable execution path, evaluated in this order: - remove unnecessary work - reduce frequency - use script-only/no-agent mode for deterministic work - use monitoring or change detection to suppress unchanged runs - narrow toolsets - reduce unnecessary context or continuity - lower reasoning effort - use a cheaper model or provider when judgment is still required 4. Any prompt, idempotency, delivery, security, or reliability fixes needed. For every recommendation, show: - current state - proposed state - rationale - risk - expected monthly savings Use actual execution and usage data when available. Otherwise label savings as estimates, state the assumptions, and provide a range. Do not fabricate precision. End with: - number of jobs reviewed - current estimated monthly run volume - recommended removals, pauses, and consolidations - estimated monthly agent runs and tokens before vs. after - model-cost implications where pricing can be verified - prioritized changes grouped by low, medium, and high risk - the exact changes or CLI commands you would use after approval Ask for my approval. Make no changes during this run. --- MAKE IT RECURRING: Then I used this to propose a recurring audit without giving it permission to “optimize” anything on its own: --- Propose a monthly read-only cron-fleet audit named “Monthly cron efficiency audit.” Before creating or updating anything: 1. Check for an existing equivalent audit. Reuse or update it instead of creating a duplicate. 2. Inspect existing schedules and propose a low-traffic daytime slot in my local timezone that avoids collisions. 3. Make the audit self-contained and give it only the toolsets and context required to inspect cron definitions, execution history, and usage data. 4. If scheduled sessions cannot inspect those sources directly, propose a read-only pre-run script that collects the required data. Do not enable autonomous cron mutation. 5. Recommend an economical model and low or minimal reasoning only after confirming they can perform the audit reliably. Keep model and provider pins user-owned and provide the exact Hermes CLI command required. The monthly job must: - perform the same read-only review as the one-time audit - deliver a concise change proposal - never edit, pause, remove, create, or run other jobs - never change model or provider settings - clearly distinguish measured savings from estimates Show me the proposed schedule, full prompt, data inputs, toolsets, model and reasoning choice, delivery target, and exact creation or update command. Ask for approval before creating or updating anything. --- The useful order is: remove work, run it less often, avoid invoking an agent when a script will do, reduce what each run can see, then make the remaining judgment calls cheaper.