meeting-copilot: Workflow Automation for AI Agents | OpenAgentSkill

Overview

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.

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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 Do not publish raw transcripts, client names, personal notes, or generated meeting artifacts unless the user explicitly asks for a sanitized export.

Modes

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

CREATE

Inputs:

meeting title or contact name
meeting type, for example discovery, sales, mentoring, support, hiring, partnership
date
available context files, if any
output directory

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, constraints
questions.js: grouped live questions
topics.js: planned and discussed topics
decisions.js: decisions, risks, blockers, open loops
followups.js: action items, owners, due dates, next message draft

If 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.

UPDATE

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:

Save incoming transcript to state/transcript-new.txt.
Run python3 state/diff.py < state/transcript-new.txt > state/delta.txt.
Read state/delta.txt.
Update only live tabs: questions.js, topics.js, decisions.js, followups.js.
Move state/transcript-new.txt to state/transcript.txt.
Tell the user what changed and ask them to refresh the dashboard.

Do not update long-term profile or history files during UPDATE unless the user asks. Keep the live loop fast.

Question Design

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:

Check-in and goal
Business context
Budget, timeline, and constraints
Decision criteria
Risks and blockers
Next steps

Mark critical questions clearly, especially around money, deadlines, authority, legal constraints, and irreversible decisions.

Topic Map

Track meeting flow as planned, discussed, skipped, or unresolved.

Use a compact visual language:

filled marker: discussed
hollow marker: planned but not reached
warning marker: blocked or risky
check marker: decided

If using a graph, include only topics, projects, concepts, decisions, and risks. Do not put private participant names into public exports.

CLOSE

At the end of the meeting:

Process the final transcript chunk.
Write a concise meeting summary.
Extract decisions, action items, owners, deadlines, and open questions.
Update the user's chosen system of record, for example CRM, project issue, notes folder, or ticket.
Create a follow-up message draft.
If requested, create a sanitized export with names, company data, private links, and raw transcript removed.

Close output template:

# Meeting Summary

## Outcome

## Decisions

## Action Items

| Item | Owner | Due | Status |
| --- | --- | --- | --- |

## Open Questions

## Follow-up Draft

Privacy Rules

Never put these in public artifacts:

raw transcript
private names, emails, handles, phone numbers
company secrets, pricing, revenue, pipeline data
private repository paths or URLs
authentication tokens, meeting links, calendar links
internal prompts, model names, or routing rules that expose private operations

For public examples, use placeholders:

Participant A
Company X
~/workspace/crm
https://example.com/private-doc

Quality Bar

Before calling the work done:

dashboard opens locally
tabs render without console-breaking syntax errors
sensitive data is not present in public docs
close summary has decisions and action items separated
generated public export is clearly marked as sanitized

View source ↗

File metadata

name: meeting-copilot
description: 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.

View original text

---
name: meeting-copilot
description: 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.
---

# 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.

## Modes

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 |

## CREATE

Inputs:
- meeting title or contact name
- meeting type, for example discovery, sales, mentoring, support, hiring, partnership
- date
- available context files, if any
- output directory

Create this structure:

```text
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, constraints
- `questions.js`: grouped live questions
- `topics.js`: planned and discussed topics
- `decisions.js`: decisions, risks, blockers, open loops
- `followups.js`: action items, owners, due dates, next message draft

If the app uses ES modules, serve it over HTTP:

```bash
cd YYYY-MM-DD-meeting-copilot/app
python3 -m http.server 8080
```

Then open `http://127.0.0.1:8080`.

## UPDATE

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:

```python
#!/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:

1. Save incoming transcript to `state/transcript-new.txt`.
2. Run `python3 state/diff.py < state/transcript-new.txt > state/delta.txt`.
3. Read `state/delta.txt`.
4. Update only live tabs: `questions.js`, `topics.js`, `decisions.js`, `followups.js`.
5. Move `state/transcript-new.txt` to `state/transcript.txt`.
6. Tell the user what changed and ask them to refresh the dashboard.

Do not update long-term profile or history files during UPDATE unless the user asks. Keep the live loop fast.

## Question Design

Group questions by topic. Avoid one long list.

Use 3 to 6 groups, with 3 to 6 questions per group:

```js
function questionGroup(title, items) {
  if (!items.length) return "";
  return card(title, `<ul>${items.map((item) => `<li>${item}</li>`).join("")}</ul>`);
}
```

Good groups:
- Check-in and goal
- Business context
- Budget, timeline, and constraints
- Decision criteria
- Risks and blockers
- Next steps

Mark critical questions clearly, especially around money, deadlines, authority, legal constraints, and irreversible decisions.

## Topic Map

Track meeting flow as planned, discussed, skipped, or unresolved.

Use a compact visual language:
- filled marker: discussed
- hollow marker: planned but not reached
- warning marker: blocked or risky
- check marker: decided

If using a graph, include only topics, projects, concepts, decisions, and risks. Do not put private participant names into public exports.

## CLOSE

At the end of the meeting:

1. Process the final transcript chunk.
2. Write a concise meeting summary.
3. Extract decisions, action items, owners, deadlines, and open questions.
4. Update the user's chosen system of record, for example CRM, project issue, notes folder, or ticket.
5. Create a follow-up message draft.
6. If requested, create a sanitized export with names, company data, private links, and raw transcript removed.

Close output template:

```markdown
# Meeting Summary

## Outcome

## Decisions

## Action Items

| Item | Owner | Due | Status |
| --- | --- | --- | --- |

## Open Questions

## Follow-up Draft
```

## Privacy Rules

Never put these in public artifacts:
- raw transcript
- private names, emails, handles, phone numbers
- company secrets, pricing, revenue, pipeline data
- private repository paths or URLs
- authentication tokens, meeting links, calendar links
- internal prompts, model names, or routing rules that expose private operations

For public examples, use placeholders:
- `Participant A`
- `Company X`
- `~/workspace/crm`
- `https://example.com/private-doc`

## Quality Bar

Before calling the work done:
- dashboard opens locally
- tabs render without console-breaking syntax errors
- sensitive data is not present in public docs
- close summary has decisions and action items separated
- generated public export is clearly marked as sanitized

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 224 stars, 25 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: serejaris/personal-corp-os
License: MIT
Version: 1.0.0
Last GitHub push: Aug 26, 2026
Registry updated: Sep 3, 2026
Instruction path: skills/meeting-copilot/SKILL.md @ 2055336e7a23

Version reported in registry metadata; check source releases before relying on it.

Quality

70/100

Strong

Trust

65/100

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
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      "success_rate": null,
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      "install_attempts": 0,
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      "risk_blocked": 0,
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  "quality": {
    "score": 70,
    "label": "Strong"
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  "supply": {
    "track": "Marketing and growth automation",
    "scenario": "Sales and CRM",
    "maintenance": "22d since push",
    "risk": "Needs review"
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  "alternative_skills": [],
  "do_not_use_when": [
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    "high-compliance environments without internal security review",
    "No OpenAgentSkill engagement data yet",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Quality score needs review",
    "Permission surface needs review: secrets or environment access, shell or command execution"
  ],
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    "minimum_review_before_use": [
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      "Audit: 78/100 Needs review",
      "Safety: 38/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "serejaris-meeting-copilot (meeting-copilot)",
      "install_command": "npx skills add serejaris/personal-corp-os --skill meeting-copilot",
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    "expected_outcomes": [
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      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
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    "payload_template": {
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      "skill_slug": "serejaris-meeting-copilot",
      "task": "Use meeting-copilot in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
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      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
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      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
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  "endpoints": {
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    "api": "https://www.openagentskill.com/api/agent/skills/serejaris-meeting-copilot",
    "audit": "https://www.openagentskill.com/skills/serejaris-meeting-copilot/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=serejaris-meeting-copilot&task=Use%20meeting-copilot%20in%20an%20agent%20workflow&max_risk=medium",
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    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20meeting-copilot%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/serejaris-meeting-copilot/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/serejaris-meeting-copilot"
  }
}

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Creator: serejaris
Source: serejaris/personal-corp-os
Indexed by: OpenAgentSkill community index

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/serejaris-meeting-copilot?metric=listed&label=Listed)](https://www.openagentskill.com/skills/serejaris-meeting-copilot?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/serejaris-meeting-copilot?metric=trust&label=Trust)](https://www.openagentskill.com/skills/serejaris-meeting-copilot?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/serejaris-meeting-copilot?metric=audit&label=Audit)](https://www.openagentskill.com/skills/serejaris-meeting-copilot/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/serejaris-meeting-copilot?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/serejaris-meeting-copilot?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

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