Sui Dev-Leads Ops Bot

Turns a Slack channel plus one Google Sheet (the "Open Questions" tab) into an always-organized developer-escalation tracker for Sui dev-relations leads.

Two entrypoints share the same sheet as the single source of truth, so IDs are consistent across every dev lead:

Run either, or both. See docs/mcp.md for the MCP tool guide and docs/operations.md for deployment and day-to-day ops.

Classification taxonomy

Every escalation is classified on two independent axes (plus a priority). Both are LLM-classified: the auto-tracker does it automatically; the MCP post_message tool auto-classifies but lets the human override. They are written to two sheet columns (Product, Type) the bot auto-adds; the legacy Escalated To column is left untouched. The lists live in src/sui_ops_bot/config.py.

• product (15): DeepBook, Walrus, Harbor, Seal, Nautilus, MemWal, Enoki, Slush, zkLogin, SDK, Bridge, Sui Core, Hashi, Program, Other

• type (5): Question, Open PR, Bug, Feature Request, Communication

• priority: High, Medium, Low

Related MCP server: Slack MCP Server

Quickstart

# 1. Install (editable, with the dev toolchain)
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

# 2. Configure
cp .env.example .env          # fill in the values
#   plus a Google service-account json at secrets/service_account.json

# 3. Validate config (no side effects beyond token/sheet checks)
python -m sui_ops_bot.slackbot --check
python -m sui_ops_bot.mcpserver --check

# 4. Run
python -m sui_ops_bot.slackbot          # auto-tracker (long-running)
python -m sui_ops_bot.mcpserver         # MCP over stdio (launched by the client)

--diag runs live read-only diagnostics for the auto-tracker (Slack identity, channel membership, one classify call, sheet access).

How it works

• Auto-log. A cheap local pre-filter drops chatter; substantive top-level messages go to Claude, which decides if a message is a new developer escalation and extracts the structured fields (summary, platform, product, type, priority). If yes, a row is appended and the bot posts an in-thread note with a deep link. React :x: to discard a false positive.

• Resolve, human-in-the-loop. A thread reply on a tracked message, or a :white_check_mark: on it, triggers Claude to judge resolution. If it looks resolved, the bot proposes closure and asks the owner to confirm with a :white_check_mark:; the confirming reaction closes the row. Nothing is ever auto-closed.

• Report. weekly_report (MCP) groups the open backlog by product and accepts product= / type= filters. The auto-tracker answers !status, !open, !aging in-channel.

The sheet holds the state: two classification columns (Product, Type) plus three infra columns (Slack Channel, Slack TS, Bot Refs) let the in-memory index be rebuilt on every boot, so redeploys on ephemeral hosts never lose tracking.

Layout

src/sui_ops_bot/   config, ids, logutil, classify, sheet, reports,
                   slack_client, slackbot (auto-tracker), mcpserver (MCP)
tests/             pytest on the pure logic (no network)
deploy/            Dockerfiles + docker-compose
docs/              MCP tool guide + operations
.claude/           SOP + git-standards + project context (CLAUDE.md at root)

Development

pytest            # unit tests on the pure logic (ids, taxonomy, reports)
ruff check .      # lint

The workflow (branch, TDD, review, ship) is documented in .claude/rules/SOP.md. Task tracking is GitHub Issues only.

Security

.env and everything under secrets/ are gitignored and must never be committed. All Slack, Anthropic, and MCP tokens plus the Google service-account json live only in the environment or a mounted file. The remote MCP HTTP endpoint refuses to start without MCP_HTTP_TOKEN and gates every request behind it.