Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add alivirgo/Major-AI-Skills --skill summarize-meetings-into-decisionsgit clone --depth 1 https://github.com/alivirgo/Major-AI-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alivirgo/major-ai-skills/summarize-meetings-into-decisions)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/summarize-meetings-into-decisions"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/summarize-meetings-into-decisions/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/summarize-meetings-into-decisions"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/summarize-meetings-into-decisions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.00992 |
| Opus 5.5 | $0.00010 | $0.00397 |
| Sonnet 5.5 | $0.00005 | $0.00198 |
| Haiku 4.5 | $0.00003 | $0.00099 |
Grade A, and why
summarize-meetings-into-decisions scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Summarize Meetings into Decisions (Decision Log Extraction) (AI Skill)
Overview
When asked to summarize a 45-minute meeting transcript, standard AI outputs create a chronological play-by-play ("First, Sarah presented the Q3 slide deck. Then Mark asked about pricing. Then Sarah replied that pricing was under review...").
This chronological narrative is nearly useless for executives and team members who weren't in the room. What matters are the final decisions agreed upon, the rationale behind them, and who is accountable for execution.
The Decision Log Extraction Protocol filters out conversational chatter and formats the meeting into an Architecture / Executive Decision Record (ADR).
Chronological Narrative vs. Decision Record
┌─────────────────────────────────────────────────────────────┐
│ Transcript Processing Models │
│ │
│ Chronological Narrative (Low Value): │
│ • 4 pages of "Bob said this, then Alice disagreed..." │
│ • High reading fatigue, impossible to find final agreements│
│ │
│ Decision Record (High Value): │
│ • [DECISION 1]: What was decided & why │
│ • [OPTIONS REJECTED]: What was eliminated & why │
│ • [ACTION ASSIGNMENTS]: [Owner] + [Task] + [Deadline] │
└─────────────────────────────────────────────────────────────┘
Master Decision Record Prompt Templates
Pattern 1: The Executive Decision Record (ADR)
Use for product, strategy, and leadership meetings:
Analyze the attached meeting transcript: [ATTACH TRANSCRIPT / PASTE TEXT].
Do NOT write a chronological timeline of who spoke.
Extract a structured **Executive Decision Record**:
### 🎯 1. Key Decisions Made
For each decision, format as:
- **Decision**: [Clear 1-sentence statement of what was approved]
- **Rationale**: [Why this option won over alternatives]
- **Trade-off / Cost**: [What we are giving up or spending]
### 🚫 2. Options Explicitly Rejected
- [Option Name]: [Why the team decided NOT to proceed with this path]
### ⚡ 3. Accountable Action Items
| Task | Owner | Due Date | Definition of Done |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · -10 tokens per session e7b634e01a71
- 1mo ago First seen · 97 lines · 36 tokens per session scan A cbaa45c975cc
summarize-meetings-into-decisions is a skill published in the GitHub repository alivirgo/Major-AI-Skills (2 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 992 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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