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wtf is pre-meeting-intel?

dd-ai427/pre-meeting-intel — explained in plain English

Analysis updated 2026-05-18

12PythonAudience · pm founderComplexity · 3/5LicenseSetup · easy

TL;DR

A Claude/Mira skill that researches a person before a first meeting using four parallel research agents, then produces a 6-section briefing with recent activity, self-vs-other analysis, and talking points.

Mindmap

mindmap
  root((repo))
    What it does
      Pre meeting research brief
      Four parallel agents
      Self vs other analysis
    Tech stack
      Python
      Claude Code
      Mira
    Use cases
      Research before meetings
      Compare narratives
      Generate talking points
    Audience
      BD and founders

Code map

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filefunction / class

Why would anyone build with this?

REASON 1

Generate a pre-meeting research brief on someone before a first business development conversation.

REASON 2

Compare how a person describes themselves versus how media and their community describe them.

REASON 3

Get speakable talking points tied to someone's most recent public activity before a meeting.

What's in the stack?

PythonClaude CodeMira

How it stacks up

dd-ai427/pre-meeting-intelaim-uofa/reasonmatchairbone42/360-data-athlete
Stars121212
LanguagePythonPythonPython
Setup difficultyeasyhardhard
Complexity3/55/54/5
Audiencepm founderresearchergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you spin it up?

Difficulty · easy Time to first run · 5min

Works out of the box with web search, web fetch, and Python, two internal ByteDance-only enhancers are optional and degrade gracefully.

You can use, modify, and redistribute this freely, including commercially, as long as you keep the original copyright notice.

Wtf does this do

Pre-meeting-intel is a Claude or Mira skill that puts together a research brief about a person before you meet them for the first time, built specifically for business development style meetings. Instead of relying on a static LinkedIn summary, it looks at what the person has actually been doing and saying recently, on the idea that knowing what someone shipped yesterday or what people are saying about them this week matters more than an outdated career overview. You run it with a single slash command, giving it a name, a company, and the context for your meeting, and it launches four research agents at the same time. One looks at community discussion about the person on places like Reddit, Hacker News, or social media replies, another looks at the person's own recent posts, talks, or writing, a third looks at coverage from outside media outlets, and a fourth gathers official self descriptions like a bio or company page. It then compares what the person says about themselves against how others describe them, since the authors consider that gap to be where the real insight is. The final output is a brief of around 2000 to 2500 words split into six sections: an identity summary, a short biographical narrative, a timeline of the last 90 days with direct quotes and confidence levels, a side by side comparison of self versus other descriptions, a deeper personality portrait, and a set of talking points meant to be spoken aloud in the actual meeting. There is also a data confidence section showing the underlying facts and how they were weighted. Two optional pieces of the pipeline rely on internal services from ByteDance, one for pulling verified social media post links instead of guessing them, and one for writing the finished brief into a Feishu or Lark document. Both are built to fail gracefully: if they are not available, which will be the case for anyone outside that company, the skill still produces the complete brief, just using a homepage link instead of a verified post link, and returning the brief as plain markdown text instead of a hosted document. To install it for Claude Code, you clone the repository into your Claude skills folder. It works out of the box using web search, web fetch, and Python, with no extra configuration required unless you have access to the internal enhancers.

Yoink these prompts

Prompt 1
Install this skill in Claude Code and run it on a person I'm meeting next week.
Prompt 2
Explain how the four parallel research agents in this skill divide up their research.
Prompt 3
Show me an example brief this skill produces and how the talking points section is structured.

Frequently asked questions

wtf is pre-meeting-intel?

A Claude/Mira skill that researches a person before a first meeting using four parallel research agents, then produces a 6-section briefing with recent activity, self-vs-other analysis, and talking points.

What language is pre-meeting-intel written in?

Mainly Python. The stack also includes Python, Claude Code, Mira.

What license does pre-meeting-intel use?

You can use, modify, and redistribute this freely, including commercially, as long as you keep the original copyright notice.

How hard is pre-meeting-intel to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is pre-meeting-intel for?

Mainly pm founder.

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