---
name: Minutes Ingest
slug: minutes-ingest
category: Automation
description: Minutes Ingest extracts structured facts from meeting notes and updates person profiles, a chronological log, and an index in a knowledge base. Use it when asked to ingest meetings, update a knowledge base, or sync meeting data to a wiki.
github: "https://github.com/silverstein/minutes/tree/main/.opencode/skills/minutes-ingest"
language: Rust
stars: 1439
forks: 154
install: "npx degit https://github.com/silverstein/minutes/tree/main/.opencode/skills/minutes-ingest ~/.claude/skills/minutes-ingest"
installs_to: ~/.claude/skills/minutes-ingest
source_path: .opencode/skills/minutes-ingest/SKILL.md
collection_size: 23
category_size: 1523
collection_url: "https://dirskills.com/collections/silverstein/minutes"
added: 2026-08-19T07:27:21.215Z
last_synced: 2026-08-19T07:27:21.215Z
canonical_url: "https://dirskills.com/skills/minutes-ingest"
---

# Minutes Ingest

Minutes Ingest extracts structured facts from meeting notes and updates person profiles, a chronological log, and an index in a knowledge base. Use it when asked to ingest meetings, update a knowledge base, or sync meeting data to a wiki.

**Install:**

```bash
npx degit https://github.com/silverstein/minutes/tree/main/.opencode/skills/minutes-ingest ~/.claude/skills/minutes-ingest
```

## README

# /minutes-ingest

Process meetings through the knowledge extraction pipeline to update person profiles, append to the knowledge log, and maintain the index.

## Prerequisites

The `[knowledge]` section must be configured in `~/.config/minutes/config.toml`:

```toml
[knowledge]
enabled = true
path = "/path/to/knowledge/base"
adapter = "wiki"  # or "para", "obsidian"
engine = "none"   # or "agent" for LLM extraction
min_confidence = "strong"
```

If not configured, explain what's needed and offer to help set it up.

## How to run

### Single meeting
```bash
minutes ingest ~/meetings/2026-04-03-strategy-call.md
```

### All normal meetings (backfill)
```bash
minutes ingest --all
```

### Preview without writing (recommended first time)
```bash
minutes ingest --all --dry-run
```

## What it does

1. **Reads** each meeting's YAML frontmatter (decisions, action_items, entities, intents)
2. **Extracts** structured facts with confidence levels and source provenance
3. **Updates** person profiles in the knowledge base (adapter-dependent format)
4. **Appends** to `log.md` with a timestamped entry for each ingested meeting
5. **Skips** facts that already exist (deduplication) or are below the confidence threshold
6. **Excludes** meetings designated `sensitivity: restricted` from automated knowledge-base ingestion

## Safety guarantees

- **`engine = "none"` (default)**: Only extracts from parsed YAML frontmatter. No LLM involved, zero hallucination risk.
- **Confidence thresholds**: Facts below `min_confidence` are counted as "skipped" but never written.
- **Provenance**: Every fact records which meeting it came from and when.
- **Deduplication**: Facts whose text already appears in a person's profile are skipped.
- **Dry-run**: Always suggest `--dry-run` first if the user hasn't used ingest before.

## Interpreting the output

```
Ingesting 73 meeting(s) into knowledge base at /path/to/kb
  2026-04-03-strategy.md — 4 written, 1 skipped — Mat, Dan
  2026-04-05-standup.md — 2 written, 0 skipped — Alice
  SKIP 2026-03-18-test.md: no frontmatter

Done. 6 fact(s) written, 1 skipped, 1 error(s), 3 people updated.
```

- **written**: facts that passed confidence threshold and didn't already exist
- **skipped**: facts below confidence threshold (logged, not written)
- **SKIP**: files that couldn't be parsed (no frontmatter, invalid YAML, etc.)

## Gotchas

- **Meetings without summarization have no structured data** — If a meeting was recorded before summarization was enabled, its frontmatter won't have `action_items` or `decisions`. The ingest will correctly extract 0 facts. This is expected, not an error.
- **`engine = "agent"` requires an AI CLI** — If the user wants richer LLM-based extraction from transcript body text, they need `claude`, `codex`, `gemini`, `opencode`, or `pi` on PATH.
- **PARA adapter writes `items.json`** — If the user's knowledge base uses the PARA format, facts go into `areas/people/{slug}/items.json` with atomic fact schema (id, status, supersededBy).
- **First run should be dry-run** — Always suggest `minutes ingest --all --dry-run` before the first real run so the user can see what would be extracted.