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Show AI/LLM spending, budget usage, and operational cost metrics. Use when the user says "how much have we spent", "cost report", "show costs", "budget status", or "spending breakdown".
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
TTS pronunciation configuration. Controls how written text is normalized to natural spoken English before being passed to the Speaches/Kokoro TTS engine. Two DB-configurable app_settings keys let operators add or override pronunciation rules without code changes.
Image-direction prompts for the content pipeline. Generate featured-image prompts, build stock image search queries, run the image-director reasoning that picks which sections get visuals (image_gen vs pexels, style, and prompt/query for each) plus one featured hero image, and caption rendered images with vision-derived alt text.
Generate a native, community-appropriate Reddit value-post from a published blog post
Blog drafting & revision prompts. Turn a topic + research context into a publication-ready markdown article, then refine it against reviewer feedback. Includes the writer system prompt, the draft request, the anti-fabrication initial-draft prompt, an SEO-metadata helper, and the iterative-refinement prompt. Use during the content-generation stage of the pipeline.
Video director — given a post body + podcast script + target duration, produces a JSON shot list (ordered shots with per-shot source plugin, prompt/query, and duration) for the post's video. Enforces the no-AI-humans + stylized-not-photoreal policies. Used by the generate_video_shot_list pipeline stage. Operator brand is templated via {site_name}.
Classify a published post into brand content-types (multi-label). Populates post_content_types via ClassifyContentTypesJob.
| name | cost-report |
| description | Show AI/LLM spending, budget usage, and operational cost metrics. Use when the user says "how much have we spent", "cost report", "show costs", "budget status", or "spending breakdown". |
Shows Glad Labs pipeline spending and budget consumption by combining two API endpoints:
GET /api/metrics/costs/budget — daily/monthly spend vs. configured limitsGET /api/metrics/operational — task counts and throughput metrics that indirectly reflect costCosts are primarily electricity for local GPU inference (Ollama + image-gen on RTX 5090).
Per-token "cost" is calculated from GPU power draw × duration × electricity_rate_kwh
(currently $0.2552/kWh, Rhode Island residential).
scripts/run.sh # Full report (budget + operational)
scripts/run.sh budget # Budget status only
scripts/run.sh operational # Operational metrics only
None.
The two endpoints are independent — budget shows money, operational shows throughput. Read them together to answer "are we on track this month and is the worker actually doing anything".