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Standup

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thedotmack
standup

Facilitate a read-only standup across git worktrees, branches, or PRs to compare changes and produce one consolidation plan.

Overview

Publisherthedotmack
Repositoryclaude-mem
Skill namestandup
Stars
94.1K
Forks
8.3K
Bundled files
2
LicenseApache-2.0
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Standup 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/thedotmack/claude-mem.git /tmp/claude-mem
mkdir -p .claude/skills
cp -r /tmp/claude-mem/plugin/skills/standup .claude/skills/standup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Standup 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 Standup 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 Standup 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.

standup — facilitate a group chat between branch-agents

You're the facilitator. Each of the user's git worktrees (and any PRs they pick) joins a shared markdown chat as its own agent, and the agents reconcile their scattered work into ONE consolidated worktree. You convene the room, run the conversation in rounds, and carry the outcome back — the reconciling happens in the chat, between the agents.

The room is one shared file (default ~/.claude-mem/STANDUP.md): YAML front matter holds the goal + prompt; the body is the transcript. Writes are atomically locked, so agents speak at once. It is read-only — agents decide how the merge should go; nobody commits or merges inside the room. Real git work happens afterward via /do.

1. Fill the room

Two ways, mixable:

  • By recency (common) — worktrees active in a window:

    bash
    node "${CLAUDE_SKILL_DIR}/standup.mjs" worktrees --since <1h|4h|24h|7d|all> --json

    Active = a commit or an uncommitted/staged/untracked edit in the window. If the user didn't name a window, offer 1h / 4h / 24h / 7d / all.

  • By hand — specific branches and/or open PRs:

    bash
    node "${CLAUDE_SKILL_DIR}/standup.mjs" worktrees --json   # local branches
    node "${CLAUDE_SKILL_DIR}/standup.mjs" prs --json         # open PRs (via gh)

    Show one numbered list (worktrees + PRs, with age/title); their reply is the "checkbox." If prs errors (no gh / not GitHub), carry on worktrees-only.

Zero or one candidate isn't a standup — say so, offer to widen, stop. Otherwise echo the roster to confirm before you start.

2. Open the room

Set a goal + prompt that invite a conversation, not one-shot status reports:

bash
node "${CLAUDE_SKILL_DIR}/standup.mjs" open --force --agent facilitator \
  --goal "Collapse these branches/PRs into ONE consolidated worktree: what each changed, where they overlap, which becomes the target, and the merge order." \
  --prompt "Facilitated rounds. Round 1: introduce your branch and its state. Then resolve the conflicts the facilitator surfaces, round by round, until the room lands on one concrete plan (target worktree + merge order + conflict resolutions). Read-only: decide, don't merge. Register AGREE when you back the plan."

3. Run it as rounds

You drive the turns — if agents watch-loop on their own the room can stall with nothing decided. Each agent speaks once per round (read → post → return); you read between rounds and bring back whoever's still needed.

Spawned agents don't inherit CLAUDE_SKILL_DIR, so resolve it once and paste the real path into each brief:

bash
echo "${CLAUDE_SKILL_DIR}"

Round 1 — intros (everyone, one Task message so they run together). Brief each:

You're <branch> (a PR is pr-<number>) in a standup group chat. Read <skill-dir>/agent-brief.md and play your part by it. The room is ~/.claude-mem/STANDUP.md; speak with node "<skill-dir>/standup.mjs" post …, catch up with … read. Get your bearings (cd "<path>", git log --oneline origin/main..HEAD, git status --short, git diff --stat origin/main...HEAD; a PR uses gh pr view/diff <number>), then post ONE turn: your branch, its real state, and how it should fold in. Read-only. Then return.

Reconcile. Once they've returned, read the room and list the open items — overlaps, conflicts, competing implementations, undecided target/order. None? Skip to the close.

Resolution rounds (cap ~4). Per open item, re-spawn only the agents it implicates, with the specific question. Tell them to read --since <their-name> first, then post their position and --agree if convinced. read again, update the list. Repeat.

Close — you always write it. Stop when the list is empty, you hit the cap, or an agent errors (note "didn't report," don't block). Then write the SUMMATION yourself — don't wait for an agent to volunteer. Write it as plain prose a human can skim, not a field dump: which worktree is the target and why, the merge order in a sentence, and what's left for the human:

bash
node "${CLAUDE_SKILL_DIR}/standup.mjs" summation --agent facilitator \
  --text "Build on <worktree> — it's the only one with real code. Layer <branch>'s changes on top, then drop in the doc-only branches; skip <empty branch>. Your call before it's safe: <the one or two real decisions>. Done when it all sits in <target> and builds clean."

4. Brief the human in plain language

This is the payoff — don't hand them the raw SUMMATION, translate it. A human who didn't watch the room should understand the outcome without decoding paths, line counts, or commit hashes. Lead with the answer, then the few choices only they can make:

  • What you found — one plain line per branch: who has real code, who's just docs, who's empty.
  • The plan — target + merge order in a sentence or two.
  • Their call — only the decisions a human must make (which implementation wins, what to drop, anything risky), as concrete questions. Use AskUserQuestion for the clear-cut ones.

Keep git internals out unless they ask. Once they've settled the open calls, hand the plan to /do to perform the merges — don't merge anything yourself outside /do.

CLI

bash
node "${CLAUDE_SKILL_DIR}/standup.mjs" <command> [--flags]

Defaults: agent = git branch, file = ~/.claude-mem/STANDUP.md. Every write is atomically locked.

commandwhat it does
worktrees [--since 4h] [--json]worktrees newest-first; --since N{m,h,d,w} keeps those active in the window
prs [--since 4h] [--json]open GitHub PRs (via gh) newest-first
open --goal "…" --prompt "…" [--force]create the room (--force rotates an old one aside)
join [--message "…"]add yourself + say Hello
post --message "…" [--agree "…"]append a turn
agree --deliverable "…"append an AGREE turn
watch [--timeout SEC] [--interval SEC]block until someone else posts, print it (exit 2 on timeout)
read [--tail N] [--since AGENT]print the chat (or only turns after AGENT's last)
statusparticipants + AGREEs + consensus check
summation --text "…"write the SUMMATION, flip status: agreed

Each spawned agent plays its turns by agent-brief.md (bundled here) — the playbook for being one voice in the room.

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 Standup AI skill do?

Facilitate a read-only standup across git worktrees, branches, or PRs to compare changes and produce one consolidation plan.

Why use Standup on TypingMind?

Because you install it once and use it with any model. Standup 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 Standup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/thedotmack/claude-mem/tree/main/plugin/skills/standup. 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 Standup?

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 Standup?

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

Is the Standup AI skill free?

Yes. It is published on GitHub by thedotmack under the Apache-2.0 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.

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