serejaris/meeting-copilot
Use when preparing for, running, or closing a live meeting with an AI assistant dashboard. Triggers on "meeting copilot", "live copilot", "prepare for a call", "update copilot", "close the session", or requests to turn transcript chunks into meeting questions, topic maps, decisions, and follow-ups.
npx skills add https://github.com/serejaris/personal-corp-skills --skill meeting-copilot
Create and maintain a local HTML dashboard for a live meeting. The dashboard gives the user a second-screen view of context, questions, topic progress, decisions, risks, and follow-ups while the call is happening.
This skill is designed for private workspaces. Do not publish raw transcripts, client names, personal notes, or generated meeting artifacts unless the user explicitly asks for a sanitized export.
Use one of three modes:
| Mode | When | Output |
| --- | --- | --- |
| CREATE | Before the meeting | A local dashboard app with prepared context and questions |
| UPDATE | During the meeting | Updated questions, topics, decisions, risks, and follow-ups from transcript chunks |
| CLOSE | After the meeting | Final summary, action items, CRM or notes updates, and optional sanitized export |
Inputs:
Create this structure:
YYYY-MM-DD-meeting-copilot/
app/
index.html
app.js
components.js
styles.css
tabs/
briefing.js
questions.js
topics.js
decisions.js
followups.js
state/
transcript.txt
diff.py
Dashboard tabs:
briefing.js: meeting goal, known context, participants, constraintsquestions.js: grouped live questionstopics.js: planned and discussed topicsdecisions.js: decisions, risks, blockers, open loopsfollowups.js: action items, owners, due dates, next message draftIf the app uses ES modules, serve it over HTTP:
cd YYYY-MM-DD-meeting-copilot/app
python3 -m http.server 8080
Then open http://127.0.0.1:8080.
Input is usually a full transcript copied from a transcription tool. Treat it as sensitive.
Use suffix diffing so the agent processes only the new part:
#!/usr/bin/env python3
import pathlib
import sys
baseline = pathlib.Path(__file__).parent / "transcript.txt"
old = baseline.read_text() if baseline.exists() else ""
new = sys.stdin.read()
old_s = old.strip()
new_s = new.strip()
if not old_s:
sys.stdout.write(new)
elif new_s.startswith(old_s):
sys.stdout.write(new_s[len(old_s):].lstrip())
else:
sys.stderr.write("[diff] baseline mismatch; using full transcript\n")
sys.stdout.write(new)
Recommended update flow:
state/transcript-new.txt.python3 state/diff.py < state/transcript-new.txt > state/delta.txt.state/delta.txt.questions.js, topics.js, decisions.js, followups.js.state/transcript-new.txt to state/transcript.txt.Do not update long-term profile or history files during UPDATE unless the user asks. Keep the live loop fast.
Group questions by topic. Avoid one long list.
Use 3 to 6 groups, with 3 to 6 questions per group:
function questionGroup(title, items) {
if (!items.length) return "";
return card(title, `<ul>${items.map((item) => `<li>${item}</li>`).join("")}</ul>`);
}
Good groups:
Mark critical questions clearly, especially around money, deadlines, authority, legal constraints, and irreversible decisions.
Track meeting flow as planned, discussed, skipped, or unresolved.
Use a compact visual language:
If using a graph, include only topics, projects, concepts, decisions, and risks. Do not put private participant names into public exports.
At the end of the meeting:
Close output template:
# Meeting Summary
## Outcome
## Decisions
## Action Items
| Item | Owner | Due | Status |
| --- | --- | --- | --- |
## Open Questions
## Follow-up Draft
Never put these in public artifacts:
For public examples, use placeholders:
Participant ACompany X~/workspace/crmhttps://example.com/private-docBefore calling the work done:
Take serejaris/meeting-copilot from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.