agentleFS
Sign inStart free
tonydzitonydzi/second-brain-starter-kit/skills/granola-sync/SKILL.md

granola-sync

Skill6 starsChanged 2 months agoMITView on GitHub

Pull fresh meetings from Granola (summaries, transcripts, participants) into an Obsidian vault over the official API. Incremental and idempotent by note id and updated_at, so re-runs make no duplicates. Triggers: "/granola-sync", "pull granola", "refresh meetings".

  • Reads credentials

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run it: python $IMPORTS_ROOT/granola/granola_pull.py (options: --dry to count without writing, --limit N to cap).

    line 21
  2. Very specific:

    Read the stdout counters: DONE new=X updated=Y errors=Z state_total=N.

    line 22
  3. Distinctive:

    If new>0 — report the list of fresh meetings (titles/dates from the state or the new files).

    line 23

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

OBJECTIVE: Incrementally pull fresh meetings/calls from Granola into the vault (summary + full transcript + participants + a calendar match), on demand. Idempotent: the script downloads only what is new or changed (state.json: note id → updated_at).

CONTEXT:

  • Transport: the official Granola public API https://public-api.granola.ai/v1 (List Notes / Get Note ?include=transcript; page_size <= 30; 5 rps). Key: %WORKDIR%\secrets\granola.env (account owner.calendar@example.com, Workspace2, scopes personal+public, created 2026-07-02).
  • ⛔ The MCP transport is NO LONGER used for syncing (browser OAuth, it dies after ~10 days) — only for interactive questions, and only if re-authorized.
  • Engine (all the logic lives there, this skill is a thin wrapper): $IMPORTS_ROOT/granola/granola_pull.py. The same script does both backfill and increment.
  • Home for notes: $OBSIDIAN_VAULT/04-Projects/granola-meetings/ (auto_generated: true — never hand-edit, they get overwritten). Raw JSON: _imports\granola\raw\. Nightly task log: _imports\granola\pull.log.
  • ⚠️ Granola does NOT start recording by itself: it records only when a human opens the note or clicks the notification. "The app is running" is not "it is recording".

STEPS:

  1. BACKUP FIRST ([[vault-backup-rule]]): python $IMPORTS_ROOT/vault_backup.py BEFORE running anything.
  2. Run it: python $IMPORTS_ROOT/granola/granola_pull.py (options: --dry to count without writing, --limit N to cap).
  3. Read the stdout counters: DONE new=X updated=Y errors=Z state_total=N. errors>0 → look into it; usually network or 429 (the script retries by itself).
  4. If new>0 — report the list of fresh meetings (titles/dates from the state or the new files).
  5. Distill (if new>0): python $IMPORTS_ROOT/granola/call_distill.py — it breaks each new call into Commitments/Facts/Objections/Alpha with quotes → 04-Projects\granola-meetings\_distilled\ + commitments.jsonl. Counters: DONE distilled=M commitments=C errors=Z. (The nightly twin is the "Granola Call Distill" task at 03:50; it also eats the Fireflies raw files.)
  6. The RAG reindex picks it up overnight ([[reindex-routine]]); after the FIRST big backfill, run python $IMPORTS_ROOT/brain_embed_update.py manually. ⚠️ _distilled is not in the curated index yet (04-Projects is the evidence layer) — closed by task RUSL-1 (layer: essence).

CONSTRAINTS:

  • Windows cp1252: do not print non-ASCII to stdout (the script is already ASCII-only).
  • INCREMENTAL ONLY — never delete state.json (it would re-download everything).
  • Provenance: origin: mixed, authored_by: hybrid — NOT #anton-original (someone else's speech).
  • Tier-2: nothing goes outside; API reads and vault writes only.
  • A 401/403 from the API means the key was revoked: create a new one in the Granola desktop app (Settings → Connectors → Personal API keys, scopes Personal+Public) and update granola.env. I can do this myself through computer-use (verified 2026-07-02).

OUTPUT: the new/updated/errors counters + the period; if empty, "no new meetings". Finish with an "In plain words" recap.

RELATION (do not duplicate): the Fireflies rail (auto-recording, real speaker names) = skill [[fireflies-sync]]; access and history = memory [[granola-mcp-integration]]; the architecture decision = the vault note decision-granola-extraction-official-api; the post-call follow-up SOP = memory [[call-followup-group-sop]] (a separate pipeline); the FAAA sync goes the other way (finished follow-ups out of Telegram).

<!--kit-footer-->

Like this skill? It is one of 100 in second-brain-starter-kit: the second brain we built for ourselves and run every day at Palo Alto AI Research Lab. Install the whole set with npx skills add tonydzi/second-brain-starter-kit. Everything is open source and free, so take what you need.

Flagships worth a look on their own: secondop-panel (a second opinion from a panel of external models), claude-memory-tidy (stop your agent's memory from rotting), telegram-mcp-kit (your own Telegram over MCP in about 15 minutes).

Author: Anton Dziatkovskii, Palo Alto AI Research Lab. Telegram @tonydzi - WhatsApp +1 341 222 9178 - X @Tony_Stef_

Engineers: want to test-drive this setup? Message me. I hand out free starter seeds to engineers who test and report back, and custom skill requests are welcome.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free