Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/ai-answer/contentrepurposesystem/ideationnpx skills add AI-Answer/ContentRepurposeSystem --skill ideationgit clone --depth 1 https://github.com/AI-Answer/ContentRepurposeSystemWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00091 | $0.01812 |
| Opus 5 | $0.00046 | $0.00906 |
| Sonnet 5 | $0.00018 | $0.00362 |
| Haiku 4.5 | $0.00009 | $0.00181 |
Grade A, and why
ideation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Ideation Engine
Generate positioned YouTube video ideas grounded in existing research and competitive analysis. Outputs structured idea briefs ready to feed into /hooks and /outlines.
This skill is strategy, not research. It consumes research outputs from /yt-pipeline, /firecrawl-search, or vault notes. It does NOT replicate deep research — if no research exists yet, it runs a lightweight competitive scan only.
When This Skill Activates
Activate when the user wants to:
- Brainstorm video ideas on a topic
- Figure out what video to make next
- Find angles on a trending topic
- Generate content ideas from research they've already done
Example triggers:
- "Give me video ideas about RAG"
- "What should I make a video about this week?"
- "Brainstorm some Claude Code video angles"
/ideationor/ideation <topic>
Workflow
Step 1 — Gather Existing Context
Check what research already exists before doing anything:
- Search the vault — look in
research/andprojects/for files related to the topic - Check for recent yt-pipeline or firecrawl-search outputs — these are your primary source material
- If the user references specific notes, read them
If research exists: Use it as the foundation. Do NOT re-research the topic.
If no research exists: Do a lightweight competitive scan only (Step 2). Suggest the user run /yt-pipeline <topic> or /firecrawl-search <topic> first if they want deeper analysis.
Step 2 — Lightweight Competitive Scan
Quick YouTube search to see what exists — this is positioning intel, not deep research:
Optional step. This uses a separate
yt-searchhelper script that does not ship with this plugin. If it isn't installed, skip the scan and generate ideas from the user's described topic and any vault/research context instead — the rest of the skill works fine without it.
python "${CLAUDE_PLUGIN_ROOT}/skills/yt-search/scripts/search.py" <topic keywords> --count 15 --months 3
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 172 lines · 91 tokens per session scan A c1df39b47a5e
ideation is a skill published in the GitHub repository AI-Answer/ContentRepurposeSystem (12 stars, last pushed 2mo ago), licensed MIT. It adds 91 tokens to every session and 1,812 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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