agentmods.dev

joinly CLAUDE.md

Repository instructions for Claude Code, an AI coding assistant, in a Python project called Joinly. Joinly lets AI agents join and interact with video meetings such as Google Meet, Zoom, and Teams.

In plain words
What is it for?
Use it when working on Joinly, especially for installing its machine-learning files, linting and formatting Python code, type-checking, running tests, or launching its meeting agent.
Why use it?
It gives the coding assistant the project context and the commands used to install dependencies, check code, run tests, and start the software.

Instructions file

564 5mo ago A scan 1,261 tokens original MIT
View the source file joinly-ai/joinly
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/joinly-ai/joinly/claude-md
Clone the repo
git clone --depth 1 https://github.com/joinly-ai/joinly
Per session 1,261 This file is loaded in full into every session.
When invoked 1,261 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.01261 $0.01261
Opus 5 $0.00630 $0.00630
Sonnet 5 $0.00252 $0.00252
Haiku 4.5 $0.00126 $0.00126

Measured 2d ago against content hash 480cf3d55b47, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

joinly CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CLAUDE.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

joinly is a Python middleware that enables AI agents to join and participate in video meetings (Google Meet, Zoom, Teams). It exposes a FastMCP server providing meeting tools (join, leave, speak, transcribe, chat, snapshot, screen share) that any MCP-compatible AI client can use.

Build & Development Commands

# Install all dependencies (run from repo root)
uv sync --frozen

# Download required ML models (Silero VAD, Whisper, Kokoro TTS)
uv run scripts/download_assets.py

# Lint (ruff checks all rules by default)
uv run ruff check .
uv run ruff check --fix .    # autofix

# Format
uv run ruff format .

# Type check
uv run pyright

# Run tests (skips manual tests by default)
uv run pytest

# Run a single test
uv run pytest tests/test_meeting_transcription.py::TestTranscription::test_mcp_transcription -v

# Run manual/e2e tests (requires JOINLY_TEST_MEETING_URL env var)
uv run pytest -m manual

# Start as MCP server
uv run joinly --port 8000

# Start as client (built-in agent joins a meeting directly)
uv run joinly --client <MeetingURL>

Workspace Structure

This is a uv workspace with three packages:

Package Directory PyPI name Purpose
joinly joinly/ joinly Main MCP server + meeting automation
joinly-client client/joinly_client/ joinly-client Python client library + LLM conversational agent
joinly-common common/joinly_common/ joinly-common Shared Pydantic types used by both

Workspace sources are linked locally via [tool.uv.sources]. Each sub-package has its own pyproject.toml and is versioned/released independently (tags: v*, client-v*, common-v*).

Architecture

Core Design Patterns

  • Protocol-based DI: All major components (STT, TTS, VAD, MeetingProvider, controllers) are defined as Protocol classes in joinly/core.py. SessionContainer (joinly/container.py) resolves short string tokens (e.g. "whisper") to implementations by convention (joinly.services.stt.whisper.WhisperSTT).
  • ContextVar per-session state: Settings and Usage live in ContextVar so each MCP client connection gets isolated configuration. Settings can be overridden per-connection via the joinly-settings HTTP header.
  • EventBus pub/sub: Two event types ("segment", "utterance") in joinly/utils/events.py loosely couple the transcription pipeline to MCP resource subscriptions.
  • MCP as the public API: All meeting capabilities are MCP tools/resources defined in joinly/server.py. The client package connects via StreamableHttpTransport or directly to a FastMCP instance.

Read the full file on GitHub · 89 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 89 lines · 1,261 tokens per session scan A 480cf3d55b47

Subscribe to this mod's changes

joinly CLAUDE.md is an instructions file published in the GitHub repository joinly-ai/joinly (564 stars, last pushed 5mo ago), licensed MIT. It adds 1,261 tokens to every session, about $0.0063 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

agentic-aiai-agentmcpmeeting-assistanttranscription
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