LingTai Repo Watch

This nested lingtai-dev-guide reference is a read-only developer workflow for sweeping the Lingtai-AI GitHub org. It lives here because it is LingTai-project-specific; it should not be installed as a kernel intrinsic capability for every agent.

Boundaries

• Read-only by default: do not comment, label, assign, close, merge, or edit

GitHub state unless the human explicitly asks for that side effect.

• Report facts with source URLs and timestamps.
• Prefer one concise digest over piecemeal alerts unless the human requested a

live monitor.

• If automating, store state locally and alert only on changes to avoid spam.

One-shot org sweep

Use gh from a clean shell with GitHub auth already configured.

bash
gh repo list Lingtai-AI --limit 100 \
  --json name,visibility,isArchived,pushedAt,url

gh search issues --owner Lingtai-AI --state open --limit 200 \
  --json number,title,repository,state,createdAt,updatedAt,author,labels,assignees,url

gh search prs --owner Lingtai-AI --state open --limit 200 \
  --json number,title,repository,state,isDraft,createdAt,updatedAt,author,labels,url

gh search prs --json does not support reviewDecision on all installed gh versions. If review-decision status is needed, fetch it separately for a small set of PRs with a command/API that supports that field; do not put reviewDecision in the broad gh search prs field list unless you have verified that local gh supports it.

Optional filters

For "non-self" monitoring, filter after fetching rather than hard-coding a single human into this workflow. Example for Jason's machine:

bash
# Conceptual filter after JSON fetch, not a GitHub write:
author.login != "huangzesen"

Digest shape

Group output in this order:

1. New or updated open PRs — ready vs draft, author, repo, age, URL.
2. Open issues — repo, title, author, labels, stale/updated time, URL.
3. Recently merged/closed items if the caller asked for recent activity.
4. Stale or blocked items — old open PRs, no assignee, labels implying bug or

release blocker.

1. No-action footer — say explicitly that no GitHub state was changed.

Keep each item compact:

text
<repo>#<num> — <title> · <author> · opened <relative date> · updated <relative date> · <url>

A full report adds a header (# LingTai org watch — <timestamp>, scope, filters, GitHub writes: none), a "Changes since last run" block (new / updated / closed-or-removed) when running statefully, and an artifact/state-paths footer.

Cron / LaunchAgent monitor pattern

When the human asks for ongoing monitoring:

1. Create a small script under the agent workspace (for example

workspace/lingtai_org_watch/monitor_lingtai_org.py).

1. Query open issues/PRs with the read-only commands above.
2. Store a JSON state file keyed by issue:<repo>#<num> and pr:<repo>#<num>.
3. Alert only on new, updated, or closed/removed items.
4. Install a macOS LaunchAgent or other host scheduler with explicit logs.
5. Record the script, state path, report path, and launchd plist in the agent's

durable stores.

Do not embed secrets in the script output or report. If a Telegram bot token is needed for local alerts, read it from the existing local secret file and never print it.

Validation

Before claiming the monitor is installed:

• Run the script once without state/notification and confirm gh exits 0.
• Run it once with state enabled and confirm a report file is written.
• If using launchd, launchctl print gui/$(id -u)/<label> should show the job

loaded and the latest exit status 0; stdout/stderr logs should be clean.

• Confirm future runs do not resend the baseline unless explicitly requested.