From Content
Run deep, internet-enabled research on any topic to gather the raw material for content. First step of the content pipeline that feeds /linkedin and /newsletter. Automates prompt enhancement through clarifying questions, saves parameters for reproducibility, and executes web-enabled deep research via the OpenAI Deep Research API. Use when the user asks to research a topic, gather sources, investigate a subject, or build the foundation for a post or newsletter.
How this skill is triggered — by the user, by Claude, or both
Slash command
/content:researchThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Turns a research request into a comprehensive, sourced report using the OpenAI Deep Research API. The orchestration script assesses the prompt, enhances it through clarifying questions when needed, saves the exact prompt for reproducibility, runs the research, and saves a markdown report with numbered sources.
Turns a research request into a comprehensive, sourced report using the OpenAI Deep Research API. The orchestration script assesses the prompt, enhances it through clarifying questions when needed, saves the exact prompt for reproducibility, runs the research, and saves a markdown report with numbered sources.
Accept the user's research request (brief or detailed).
Decide whether to enhance. If the prompt is brief or generic, ask the 2-3 clarifying questions in references/prompt-enhancement.md (present numbered options plus a free-text option) and build the enhanced prompt. Skip when the prompt is already specific.
Confirm the final prompt with the user before executing. A run costs API spend and takes 10-20 minutes, so get a yes on the enhanced prompt first.
Run the orchestration script:
python3 scripts/run_deep_research.py "<prompt>"
It re-runs the enhancement check, saves research_prompt_*.txt, and executes synchronously. Options and output files are in references/cli.md. Wait silently for completion; do not poll for status.
Present results: the markdown report (research_report_*.md), the numbered source URLs, and the saved file paths. Offer follow-up research directions.
references/prompt-enhancement.md: when to enhance, the question templates (technical vs general), how to build the enhanced prompt, worked examples.references/cli.md: script options, output files, execution behavior.references/troubleshooting.md: requirements and error fixes (missing API key, script not found, timeout).This skill is never finished. Improve it as you use it.
references/examples/ so it becomes a model for future runs.npx claudepluginhub naveedharri/benai-skills --plugin contentGuides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.
Synthesizes the current conversation into a structured spec (PRD) and publishes it to the project issue tracker with a ready-for-agent label, without interviewing the user.