From greenfield-start
Research a product, topic, or set of URLs and synthesize structured documentation artifacts (product-brief, requirements, architecture, decisions) into docs/research/. Use when you need to document an existing product or concept as a baseline for your project.
How this skill is triggered — by the user, by Claude, or both
Slash command
/greenfield-start:researchThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are helping the user research an external product, topic, or set of sources and produce structured documentation artifacts from public information.
You are helping the user research an external product, topic, or set of sources and produce structured documentation artifacts from public information.
This skill is invoked as /greenfield-start:research <argument>.
The argument is free-form. Your first job is to determine the research mode.
Examine the argument provided after /greenfield-start:research.
If no argument was provided, ask:
What product, topic, or URL would you like me to research?
Wait for the user's response, then proceed with mode detection on their answer.
Constrained mode — the input contains one or more URLs or GitHub repo references (patterns like https://, http://, github.com/, gitlab.com/):
Examples:
https://bear.app/features/github.com/org/repohttps://docs.example.com/api https://blog.example.com/architectureIn constrained mode, the provided URLs are the confirmed source list. Derive a subject name from the URLs (e.g., domain name, repo name, or page title) to use in the dispatch prompt and output directory slug. Skip to Phase 3.
Open mode — the input is a product name, topic, or description without URLs:
Examples:
Bear note-taking appevent-driven architecture for IoT pipelinesIn open mode, proceed to Phase 2 (Source Discovery).
Ambiguous input — if the input is a single word or short phrase that could be either a specific product or a general topic, ask one clarifying question:
Are you looking to research a specific product called "", or the general topic of ""?
Then proceed based on the answer.
Use WebSearch to find relevant public sources for the subject. Target:
Present a numbered list of discovered sources with a one-line description of each:
I found these sources for "<subject>":
1. <url> — <one-line description>
2. <url> — <one-line description>
...
Which of these should I analyze? (all / comma-separated numbers / "also add <url>" / "drop <number>")
The user may:
This is a single confirmation round. Do not search again unless the user explicitly asks (e.g., "can you also search for X").
After confirmation, proceed to Phase 3 with the confirmed source list.
Generate the output directory path:
YYYY-MM-DD formatdocs/research/<date>-<slug>/-2 (then -3, etc.) until uniqueDispatch the research-analyzer agent with the following prompt:
Research subject: <subject name/description>
Output directory: <output_dir>
Research date: <YYYY-MM-DD>
Sources to analyze:
1. <url> — <description>
2. <url> — <description>
...
Analyze all sources and synthesize documentation artifacts into the output directory.
Follow your artifact format specifications exactly.
The subagent will work autonomously and produce files in the output directory.
After the subagent completes, read the generated README.md from the output directory and present a summary to the user:
Research complete. Artifacts written to `<output_dir>/`:
**Artifacts produced:**
- <artifact> (confidence: <level>)
- ...
**Skipped:**
- <artifact> — <reason>
**Notable gaps or conflicts:**
- <summary>
You can review the full research index at `<output_dir>/README.md`.
To integrate these into your project documentation later, a `/greenfield-start:integrate` skill is planned (not yet built).
If the subagent reported any unreachable sources, mention those in the summary.
npx claudepluginhub jeremygiberson/greenfield-start-plugin --plugin greenfield-startGathers external information via web search and fetch, synthesizing findings into a verified markdown report. Useful for researching libraries and comparing approaches.
Conducts deep parallel research on a topic using web searches, saves cited markdown files with validated URLs, and produces a synthesis summary.
Deep research on any topic by conducting web searches and fetching content. Can also add files or URLs to a research index. Useful for building knowledge bases or investigating unfamiliar subjects.