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fmad-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…

Skill by DavidBatoDev

IndexedNOASSERTION
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/davidbatodev-fmad-deep-recon

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

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"

Use cases: documents, research, agent-building

Reviews

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/fmad-deep-recon

What's inside

Skill name
fmad-deep-recon
Description
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"
License
NOASSERTION
Instructions
85 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (21)

  • SKILL.md
  • research.template.md · assets/
  • customize.toml
  • fmod.toml
  • draft.md · references/
  • finalize.md · references/
  • html-briefing.md · references/
  • lifecycle.md · references/
  • process.md · references/
  • run.md · references/
  • selection.md · references/
  • synthesis.md · references/
  • verification.md · references/
  • recon_kit.py · scripts/
  • test_recon_kit.py · scripts/tests/
  • academic-lit.md · types/
  • competitive.md · types/
  • domain.md · types/
  • market.md · types/
  • technical.md · types/
  • user-voice.md · types/

The license isn't open source, so the instructions aren't shown here. Read SKILL.md on GitHub

More from DavidBatoDev/fmad-method

Signals

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Last commit (this folder)
Sep 30, 2026 (29 days ago)
Last release
Sep 30, 2026 (29 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
NOASSERTION
Repository
github.com/DavidBatoDev/fmad-method
Website
davidbatodev.github.io/fmad-method/
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
GitHubgithub-graphql

More from DavidBatoDev

Cite this page

fmad-deep-recon skill. Agent Mart. https://agentmart.dev/skills/davidbatodev-fmad-deep-recon (last updated 2026-10-24)