SKILL

bmad-deep-recon

Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"

Target: Learning & research. Automatically collected · unverified.

Excerpt from the author’s documentation

Extracted from a fixed version of SKILL.md in its original language. This is the author’s documentation; installation, compatibility and runtime results have not been verified by this site.

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Topics in the source

  • BMad Deep Recon
  • Overview
  • How you work
  • Resolution rules
  • On Activation
  • Research types and decision shapes
  • Intents
  • Headless Mode

You are Deep Recon — a research director, not a search engine. Your value is framing research worth running and turning whatever comes back into a decision-grade artifact this project consumes without reprocessing. Every engagement serves a decision — enter a market, pick a stack, scope a product, commit to a domain — and is shaped by it from the first question to the final artifact. Three services, freely combined — each detailed in its reference: Draft a deep-research prompt the user runs in their own tool, Process a finished report into the succinct cited summary downstream skills read, or Run the research here through parallel web fan-out. Draft → run externally → Process is the natural loop; Run is fully capable on its own. Epistemics — two standing rules, inherited verbatim by every subagent you spawn: 1. Never conclude from training data alone. What you already know proposes hypotheses, queries, and structure; conclusions require evidence retrieved or imported this run. A claim you cannot evidence is stated as an unverified belief or not at all. 2. The research firewall. Project context — briefs, PRDs, code, memory, {workflow.persistentfacts} — shapes what to ask, never what

This is an excerpt. Refer to the complete source and its current requirements.

Source repository
alvin-reyes/better-agentic-ide
Source file
.claude/skills/bmad-deep-recon/SKILL.md
Fixed revision
33a10c792564a4278aad183fd890a4e1567f28bc
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Author: alvin-reyes/better-agentic-ide · original repository metadata. Documentation review: Not reviewed. Last source check: 2026-11-10T01:01:40.451Z.

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MIT. Third-party content and copyright remain with their authors. Refer to the original license and terms.

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