القائمة
Classify a published post into brand content-types (multi-label). Populates post_content_types via ClassifyContentTypesJob.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
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}.
General content-utility prompts — the writer-persona system prompt, content summarization, and free-form content-to-JSON conversion. Use for the writer system role, condensing content, or coercing content into structured JSON.
استنادا إلى تصنيف SOC المهني
| name | content-type-classifier |
| description | Classify a published post into brand content-types (multi-label). Populates post_content_types via ClassifyContentTypesJob. |
| license | Apache-2.0 |
| metadata | {"category":"utility","prompts":[{"key":"content.classify_content_type","output_format":"json","description":"Default content-type classifier prompt — basic but functional; a premium pack can ship sharper definitions."}]} |
Labels a published post with zero or more content-types from a DB-configurable
set (app_settings.content_type_labels). The {labels} set injected at render
time is authoritative — the job drops anything the model returns that isn't in
it. The definitions below describe the default label set; an operator who
customizes the labels should adjust these definitions to match.
You label a technical blog post with zero or more CONTENT TYPES from this exact set:
{labels}
Definitions (for the default label set):
- ai-ml: AI/ML models, LLM inference, agents, training, prompting, RAG.
- pc-hardware: GPUs, CPUs, cooling, peripherals, physical builds and their performance.
- gaming: games, game performance, frame times, gaming setups.
- software-engineering: coding, CI/CD, databases, architecture, dev practices not centered on AI.
- founder-meta: building in public, the business, indie hacking, the content operation itself.
Assign every type that genuinely applies — a post can have several (a GPU-for-local-LLM
post is ai-ml AND pc-hardware). Assign none if none truly fit; never force a label.
Return ONLY a JSON object — no markdown, no reasoning, no code fences:
{{"labels": [{{"label": "<one of the set above>", "confidence": <0.0-1.0>}}]}}
TITLE: {title}
TAGS (noisy hints, may be wrong): {tags}
EXCERPT:
{excerpt}