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Agent skill

Meeting Insights

by borghei in borghei/Claude-Skills

Analyze meeting transcripts to extract decisions, action items, owners, due dates, open questions, and risks.

MITAuto-check passedProductivity & Automation

Install Meeting Insights

skills CLI
$ npx skills add borghei/Claude-Skills --skill meeting-insights -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install borghei/Claude-Skills meeting-insights --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/personal-productivity/meeting-insights .claude/skills/meeting-insights && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
meeting-insights
GitHub stars
891
Token cost
~1.5k tokens
SKILL.md length
644 words
Files
4 (incl. scripts, references, assets)
Skills in repo
354
Repo updated
First seen
Licence
MIT

At a glance

Analyze meeting transcripts to extract decisions, action items, owners, due dates, open questions, and risks.

  • Works in 4 steps: Save your transcript text as… → Run → Review the structured output: decisions,… → …
  • Tasks that involve Meeting notes and agendas
  • SKILL.md covers Table of Contents, Keywords, Clarify First and Quick Start, plus 6 more sections
  • Runs Python scripts from its folder; calls python

What it does

Meeting Insights is an agent skill from borghei/Claude-Skills. Analyze meeting transcripts to extract decisions, action items, owners, due dates, open questions, and risks. Use after recorded meetings, sales calls, customer interviews, or planning sessions, or to build a decision log.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts, reference files and assets (for example `assets/recap_template.md`, `references/insight_extraction_patterns.md` and `scripts/transcript_analyzer.py`).

It sits in Productivity & Automation, covering Meeting notes and agendas, Architecture decision records and User research. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Tasks that involve Meeting notes and agendas
  • Tasks that involve Architecture decision records
  • Tasks that involve User research

Example prompts

  • “/meeting-insights”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Save your transcript text as transcript.txt (one speaker turn per line, format Speaker: text)
  2. Run
  3. Review the structured output: decisions, action items, owners, due dates, open questions
  4. Drop into assets/recap_template.md to send a follow-up

What it can do on your machine

Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Meeting Insights loads about 1.5k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 60 tokens; SKILL.md has 644 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 644 words, ~1,494 tokens.

Download SKILL.mdSave it as .claude/skills/meeting-insights/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
meeting-insights
description
Analyze meeting transcripts to extract decisions, action items, owners, due dates, open questions, and risks. Use after recorded meetings, sales calls, customer interviews, or planning sessions, or to build a decision log.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
personal-productivity
metadata.domain
meetings
metadata.updated
2026-05-04
metadata.python-tools
transcript_analyzer.py
metadata.tech-stack
meetings, async-collaboration

Meeting Insights

Turn raw meeting transcripts into a structured set of decisions, action items, owners, due dates, open questions, and risks.

Table of Contents

Keywords

meeting, meetings, transcript, notes, minutes, action items, decisions, decision log, follow-up, recap, sales call, customer interview, retrospective, standup, planning, async

Clarify First

Before extracting insights, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Transcript with speaker labels — Speaker: text format drives owner attribution on action items
  • Meeting type — recap vs customer interview vs decision log changes which extractions matter (decisions/actions vs pains/quotes)
  • Output target — recap email, append-only decision log, or interview synthesis sets the structure of the deliverable

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

Process a Transcript in 5 Minutes
  1. Save your transcript text as transcript.txt (one speaker turn per line, format Speaker: text)
  2. Run:
    bash
    python scripts/transcript_analyzer.py transcript.txt
  3. Review the structured output: decisions, action items, owners, due dates, open questions
  4. Drop into assets/recap_template.md to send a follow-up

Core Workflows

Workflow 1: Post-Meeting Recap

Goal: Convert a 60-minute conversation into a 90-second readable summary that everyone can act on.

Steps:

  1. Export the transcript (Otter, Fireflies, Zoom, Google Meet, etc.)
  2. Run: python scripts/transcript_analyzer.py transcript.txt
  3. Verify owners and due dates — the analyzer is heuristic; humans correct
  4. Paste structured output into assets/recap_template.md
  5. Send within 24 hours of the meeting

Expected Output: Recap with decisions, action items (owner + due date), open questions, and risks.

Time Estimate: 5-10 minutes vs. 30+ for manual note review.

Workflow 2: Customer Interview Synthesis

Goal: Pull the signals out of a discovery call without losing the customer's actual words.

Steps:

  1. Run analyzer in JSON mode: python scripts/transcript_analyzer.py transcript.txt --json
  2. Filter for pains and quotes — these are the discovery signals
  3. Use references/insight_extraction_patterns.md to triangulate across multiple interviews
  4. Tag findings by ICP segment for product / marketing handoff

Expected Output: Tagged customer pain list with verbatim quotes per insight.

Time Estimate: 15 minutes per interview after the call.

Show full SKILL.md (283 more words)Show less
Workflow 3: Decision Log Maintenance

Goal: Build an organizational memory so the same decision is not re-litigated quarter after quarter.

Steps:

  1. After each meeting, run the analyzer to extract decisions
  2. Append to a running decision log keyed by date and topic
  3. When a future meeting raises an old topic, search the log first
  4. Re-open formally rather than silently overturning

Expected Output: Append-only decision log searchable by topic and date.

Time Estimate: 2-3 minutes per meeting.

Tools

transcript_analyzer.py

Reads a transcript text file and extracts:

  • Decisions — sentences with decision markers ("we decided", "agreed", "going with")
  • Action items — sentences with action markers ("will", "going to", "by next week"), with heuristic owner + due date
  • Open questions — sentences ending in "?" or marked with "open question"
  • Risks — sentences with risk markers ("risk", "concern", "blocker", "if X then Y")
  • Quotes — distinctive verbatim sentences > 12 words (for customer interview workflows)
bash
# Human-readable
python scripts/transcript_analyzer.py transcript.txt

# JSON for programmatic use
python scripts/transcript_analyzer.py transcript.txt --json

Transcript format expected:

Alice: We need to decide on the launch date this week.
Bob: I'll send the draft by Friday.
Alice: Are we blocked on legal review?
Bob: Yes, that's the risk — if legal slips, launch slips.

Reference Guides

  • references/insight_extraction_patterns.md — Heuristic triggers for decisions, actions, and risks; how to triangulate across interviews

Templates

  • assets/recap_template.md — Post-meeting recap email with placeholder sections

Best Practices

  • Verify before sending. The analyzer is heuristic; an unverified recap that mis-attributes an action item destroys trust.
  • Owner + date or it does not exist. An action item without an owner is a hope; without a date, it is a wish.
  • Send within 24 hours. Memory of who said what fades fast; recap latency directly correlates with action-item completion rate.
  • Quote verbatim. For customer interviews, the customer's words matter more than your summary of them.
  • Decision log is append-only. Never silently overturn — re-open with a dated update.

Integration Points

  • Pairs with product-team/user-story/ for converting interview pains into stories
  • Pairs with project-management/ for action-item tracking
  • Feeds into marketing/ voice-of-customer workflows

© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references, assets) in personal-productivity/meeting-insights of borghei/Claude-Skills.

  • SKILL.md
  • assets/recap_template.md
  • references/insight_extraction_patterns.md
  • scripts/transcript_analyzer.py

Open the folder on GitHubat commit 4a698e8

Compare with similar skills

Meeting Insights next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Meeting Insights compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Meeting Insights this skillborghei/Claude-Skills891—~1.5kAutomated safety check: PassMIT
Foundation Meeting Recapproduct-on-purpose/pm-skills716—~2.6kAutomated safety check: PassApache-2.0
Decision Recordsericrisco/rsc-harness180—~2.9kAutomated safety check: PassMIT
Discover Interview Synthesisproduct-on-purpose/pm-skills716—~1.3kAutomated safety check: PassApache-2.0
Decision Register Builderpnp/sharepoint-skills133—~3.4kAutomated safety check: PassMIT
Product Methodologymagnus919/hermes-profiles289—~1.5kAutomated safety check: PassMIT

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  • Foundation Meeting Recap

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Categories

Questions about Meeting Insights

What does Meeting Insights do?

Analyze meeting transcripts to extract decisions, action items, owners, due dates, open questions, and risks. Meeting Insights is an agent skill from borghei/Claude-Skills. Analyze meeting transcripts to extract decisions, action items, owners, due dates, open questions, and risks.

When should I use Meeting Insights?

Meeting Insights fits situations like: tasks that involve Meeting notes and agendas; tasks that involve Architecture decision records; tasks that involve User research.

How do I install Meeting Insights in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill meeting-insights -a claude-code`. Or copy the skill folder (personal-productivity/meeting-insights in borghei/Claude-Skills) into .claude/skills/meeting-insights in your project. Claude Code loads it when a task matches its description.

How do I install Meeting Insights in Codex?

Run `npx skills add borghei/Claude-Skills --skill meeting-insights -a codex`. Or copy the skill folder (personal-productivity/meeting-insights in borghei/Claude-Skills) into .agents/skills/meeting-insights in your project. Codex loads it when a task matches its description.

Can I use Meeting Insights in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill meeting-insights -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meeting-insights, .gemini/skills/meeting-insights, .github/skills/meeting-insights and .opencode/skills/meeting-insights in your project.

What does Meeting Insights need to run?

Going by SKILL.md and its folder, Meeting Insights needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Meeting Insights access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Meeting Insights safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Meeting Insights use?

Meeting Insights is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Meeting Insights use?

About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 950 tokens, read only when the agent opens those files.

What are the alternatives to Meeting Insights?

Skills that share tags, products or a category with Meeting Insights: Foundation Meeting Recap (product-on-purpose/pm-skills, 716 stars), Decision Records (ericrisco/rsc-harness, 180 stars), Discover Interview Synthesis (product-on-purpose/pm-skills, 716 stars) and Decision Register Builder (pnp/sharepoint-skills, 133 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Meeting Insights?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 891 GitHub stars. The repository holds 354 skills in this directory. The repository was last updated on October 7, 2026.

Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.