Briefing logo

Briefing

CommunityPopular
garrytan
briefing

Compile daily briefing with meeting context, active deals, and citation tracking

Overview

Publishergarrytan
Repositorygbrain
Skill namebriefing
Stars
30.1K
Forks
4.5K
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by garrytan on GitHub. Read the source before you install it.

Installation

Install the Briefing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/garrytan/gbrain.git /tmp/gbrain
mkdir -p .claude/skills
cp -r /tmp/gbrain/plugin-variants/gbrain-daily/skills/briefing .claude/skills/briefing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Briefing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Briefing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Briefing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Briefing Skill

Compile a daily briefing from brain context.

Filing rule: When the briefing creates or updates brain pages, follow skills/_brain-filing-rules.md.

Contract

  • Every fact in the briefing includes an inline [Source: slug, updated DATE] citation.
  • Meeting participants are resolved against the brain; gaps are explicitly flagged.
  • Active deals and action items include deadlines and recency context.
  • The briefing is read-only: no brain pages are created or modified unless the user explicitly requests it.
  • Stale alerts surface pages relevant to today's context, not just all stale pages.

Pre-Briefing Context Pull

Run these BEFORE composing the briefing sections. All four pulls are read-only.

0a. Salience scan. Surface pages with high emotional or activity salience:

bash
gbrain salience --days 7

Returns pages ranked by emotional weight and recent activity. Fold the top 5-10 into the briefing under a "High-Salience Pages" section — these are the entities and topics that are emotionally or operationally hot right now. Use this to prioritize which meetings/deals/people get the most briefing depth.

0b. Anomaly detection. Surface statistical anomalies in the brain:

bash
gbrain anomalies

Defaults to today against a 30-day baseline; widen with --lookback-days N or lower the threshold with --sigma 2. Flags cohorts (by tag, by type) whose activity broke from their normal cadence — sudden spikes in mentions or pages updating far off their usual rhythm. Add hits to an "Anomalies" section after the brain pulse.

0c. Personal recall. Check stored personal facts and preferences before composing:

bash
gbrain recall --query "current priorities and preferences" --json

Use recall to pull personal context — dietary preferences, communication preferences, prior commitments or promises made. This prevents the briefing from contradicting things the user has previously stated or decided.

0d. Hot memory pulse (v0.32). Before composing anything else, run:

bash
gbrain recall --since-last-run --supersessions --pending --rollup --json

Fold the result into the briefing under a "Brain pulse" section at the top:

  1. Contradictions resolved overnight — the --supersessions output. Lead with these because they're new corrections to your model of the world.
  2. Top mentionstop_entities from --rollup (top 5 entity slugs by fact count in the window).
  3. New facts since last briefing — group the facts array under each entity from the rollup; include kind, notability, and confidence.
  4. Pending consolidation footer — when pending_consolidation_count > 0, note N facts await dream-cycle consolidation so the operator can decide whether to run gbrain dream before reading further.

The --since-last-run flag advances ~/.gbrain/recall-cursors/<source>.json so the next briefing picks up exactly where this one left off. If you're running this as a cron job, pass --source <slug> or set GBRAIN_SOURCE explicitly — cron doesn't start in your repo-root cwd, so dotfile resolution may miss the right source. Thin-client installs (gbrain init --mcp-only) route through the remote brain transparently.

0e. Open loops (when google sources exist). Pull who is waiting on the user and what they promised:

bash
gbrain waiting --json

Fold the top counterparties (what's owed, due dates, evidence quotes, deep links) into the ACTION ITEMS section — these are real loop rows, not inferred follow-ups, so they outrank prose heuristics. waiting refuses on stale google sources (no successful sync in 24h) and names the exact fix — that's by design: run the sync it names, then retry (see skills/google-loops/SKILL.md).

Phases

  1. Today's meetings. For each meeting on the calendar:
    • Search gbrain for each participant by name
    • Read their pages from gbrain for compiled_truth context
    • Summarize: who they are, recent timeline, relationship to you
  2. Active deals. List deal pages in gbrain filtered to active status:
    • Deadlines approaching in the next 7 days
    • Recent timeline entries (last 7 days)
  3. Time-sensitive threads. Open items from timeline entries:
    • Items with deadlines in the next 48 hours
    • Follow-ups that are overdue
  4. Recent changes. Pages updated in the last 24 hours:
    • What changed and why (read timeline entries from gbrain)
  5. People in play. List person pages in gbrain sorted by recency:
    • Updated in last 7 days
    • Have high activity (many recent timeline entries)
  6. Stale alerts. From gbrain health check:
    • Pages flagged as stale that are relevant to today's meetings

GBrain-Native Context Loading

Before generating any briefing, load context from gbrain systematically.

Before a meeting

For every attendee on the calendar invite:

  • gbrain search "<attendee name>" -- find their brain page
  • gbrain get <slug> -- load compiled truth, recent timeline, relationship context
  • If no page exists, note the gap ("No brain page for alice-example -- consider enrichment")

Before an email reply

Before drafting or triaging any email:

  • gbrain search "<sender name>" -- load sender context
  • Read their compiled truth to understand who they are, what they care about, and your relationship history. This turns a cold reply into an informed one.

Daily briefing queries

Run these queries to populate the briefing sections:

  • gbrain query "active deals status" -- deal pipeline snapshot
  • gbrain query "meetings this week" -- recent meeting pages with insights
  • gbrain query "pending commitments follow-ups" -- open threads and action items
  • gbrain list --type person --sort updated_desc --limit 10 -- people in play

Output Format

DAILY BRIEFING -- [date]
========================

MEETINGS TODAY
- [time] [meeting name]
  Participants: [name] (slug: people/name, [key context])

ACTIVE DEALS
- [deal name] -- [status], deadline: [date]
  Recent: [latest timeline entry]

ACTION ITEMS
- [item] -- due [date], related to [slug]

RECENT CHANGES (24h)
- [slug] -- [what changed]

PEOPLE IN PLAY
- [name] -- [why they're active]

Back-Linking During Briefing

If the briefing creates or updates any brain pages (e.g., new meeting prep pages, updated entity pages), the back-linking iron law applies: every entity mentioned must have a back-link from their page. See skills/_brain-filing-rules.md.

Citation in Briefings

When presenting facts from brain pages, include inline citations:

  • "Jane is CTO of Acme [Source: people/jane-doe, updated 2026-04-01]"
  • This lets the user trace any claim back to the brain page and assess freshness

Anti-Patterns

  • Briefing without brain queries. Never generate a briefing from memory alone; always query gbrain for current data.
  • Uncited facts. Every claim must include [Source: slug, updated DATE]. A fact without a citation is unverifiable.
  • Stale context presented as current. If a page hasn't been updated in 30+ days, flag the staleness explicitly rather than presenting it as fresh.
  • Modifying brain pages unprompted. The briefing is read-only by default. Do not create or update pages unless the user explicitly requests it.
  • Ignoring coverage gaps. When a meeting participant has no brain page, say so. Silence about gaps hides ignorance.

Tools Used

  • Search gbrain by name (query)
  • Read a page from gbrain (get_page)
  • List pages in gbrain by type (list_pages)
  • Check gbrain health (get_health)
  • View timeline entries in gbrain (get_timeline)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Briefing AI skill do?

Compile daily briefing with meeting context, active deals, and citation tracking

Why use Briefing on TypingMind?

Because you install it once and use it with any model. Briefing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Briefing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/garrytan/gbrain/tree/master/plugin-variants/gbrain-daily/skills/briefing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Briefing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Briefing?

As many as you like. As long as a model supports skills, you can use Briefing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Briefing AI skill free?

Yes. It is published on GitHub by garrytan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇