Minutes Ingest Agent Skill

Extract facts from meetings and update your knowledge base — person profiles, chronological log, and index. Use when the user asks "ingest my meetings", "update my knowledge base", "extract facts from meetings", "sync meetings to wiki", "backfill knowledge", or wants their PARA/Obsidian/wiki profiles updated from conversation data.

949 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

1405

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/silverstein/minutes --skill minutes-ingest

The instruction itself

10 sections, as written by the author

/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:

[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

minutes ingest ~/meetings/2026-04-03-strategy-call.md

All normal meetings (backfill)

minutes ingest --all

Preview without writing (recommended first time)

minutes ingest --all --dry-run

What it does

Reads each meeting's YAML frontmatter (decisions, action_items, entities, intents)
Extracts structured facts with confidence levels and source provenance
Updates person profiles in the knowledge base (adapter-dependent format)
Appends to log.md with a timestamped entry for each ingested meeting
Skips facts that already exist (deduplication) or are below the confidence threshold
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.

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3k tokens

How to use it

Copy the folder

Take silverstein/minutes-ingest from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.