Orchestrate iterative visual style searches with branch prompts, decision graphs, feedback loops, and final direction selection.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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 Do not publish raw transcripts, client names, personal notes, or generated meeting artifacts unless the user explicitly asks for a sanitized export.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:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Orchestrate iterative visual style searches with branch prompts, decision graphs, feedback loops, and final direction selection.
日本語の概要は準備中です。原文の説明を表示しています。
Audits the agent rules in the current folder (AGENTS.md, nested AGENTS.md files) and the skill descriptions the agent sees at start, then reports what to cut, move or rewrite and edits only after the user says yes. Use on «аудит правил», «проверь AGENTS.md», «почему агент не слушается правил», «проверь скиллы».
日本語の概要は準備中です。原文の説明を表示しています。
Робот агента Personal Corp. Агент делает себе голову робота из набора деталей, хранит её в штабе в stack/avatars.json и кладёт в штаб страницу avatar/robot.html, где робот стоит за партой своего штаба и вокруг видны отделы, без сервера и интернета. На уроке по ссылке входа с экрана урока робот входит в живой класс и горит маячком, пока агент работает. Триггеры /avatar, /avatar <ссылка входа>, сделай себе аватар, покажи своего робота, приди на урок.
日本語の概要は準備中です。原文の説明を表示しています。
Use when choosing between engines or models for an agent pipeline and the answer must come from measurement on your own data, not from marketing pages: speech recognition for meeting recordings, the model that turns a transcript into notes, the critic model that checks it. Runs every variant in an isolated container, measures time, cost per hour of input (USD and RUB, with price source and date) and quality (WER/CER and course terms for ASR; code checks plus a judge of a different model for LLM steps), writes results.json/csv and one static analytics page. Triggers on "бенчмарк", "сравни движки", "сколько стоит час записи", "какую модель взять для пайплайна", "benchmark the pipeline", "compare ASR engines".
日本語の概要は準備中です。原文の説明を表示しています。
Use when user asks for Claude Code usage stats, weekly analytics, project activity summary, or wants to see what projects were worked on. Triggers on "аналитика", "статистика claude", "cc stats", "weekly report", "что делал"
日本語の概要は準備中です。原文の説明を表示しています。
Use when needing strategic project analysis from multiple independent expert perspectives. Triggers on business decisions, growth strategy, product direction, competitive analysis, or any situation where diverse C-level opinions reduce blind spots
日本語の概要は準備中です。原文の説明を表示しています。