watchers – skill DevOps & Hạ tầng cho agent AI
Thăm dò RSS, API JSON và GitHub với cơ chế loại bỏ trùng lặp bằng watermark.
Cài skill watchers bằng một lệnh
Chọn công cụ bạn đang dùng, copy lệnh và dán vào terminal. Skill sẽ nằm trong thư mục skills của công cụ đó và sẵn sàng dùng ở phiên làm việc tiếp theo.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/watchers-e7770.tgz | tar xz -C ~/.claude/skills
Gọi trong Claude Code: /watchers – rồi mô tả công việc bạn muốn làm.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/watchers-e7770.tgz | tar xz -C ~/.codex/skills
Gọi trong Codex: $watchers – rồi mô tả công việc bạn muốn làm.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/watchers-e7770.tgz | tar xz -C ~/.hermes/skills
Gọi trong Hermes Agent: /watchers – rồi mô tả công việc bạn muốn làm.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/watchers-e7770.tgz | tar xz -C ~/.deepcode/skills
Gọi trong DeepSeek: /watchers – rồi mô tả công việc bạn muốn làm.
Nội dung SKILL.md
Nội dung SKILL.md gốc bằng tiếng Anh.
Watchers
Poll external sources on an interval and react only to new items. Three ready-made scripts plus a shared watermark helper; wire them into a cron job (or run them ad-hoc from the terminal).
When to Use
- User wants to watch an RSS/Atom feed and be notified of new entries
- User wants to watch a GitHub repo's issues / pulls / releases / commits
- User wants to poll an arbitrary JSON endpoint and get notified on new items
- User asks for "a watcher for X" or "notify me when X changes"
Mental model
A watcher is just a script that:
1. Fetches data from the external source
2. Compares against a watermark file of previously-seen IDs
3. Writes the new watermark back
4. Prints new items to stdout (or nothing on no-change)
The scripts below handle all three. The agent runs them via the terminal tool — from a cron job, a webhook, or an interactive chat — and reports what's new.
Ready-made scripts
All three live in $HERMES_HOME/skills/devops/watchers/scripts/ once the skill is installed. Each reads WATCHER_STATE_DIR (defaults to $HERMES_HOME/watcher-state/) for its state file, keyed by the --name argument.
| Script | What it watches | Dedup key |
|---|---|---|
| watch_rss.py | RSS 2.0 or Atom feed URL | <guid> / <id> |
| watch_http_json.py | Any JSON endpoint returning a list of objects | Configurable id field |
| watch_github.py | GitHub issues / pulls / releases / commits for a repo | id / sha |
All three:
- First run records a baseline — never replays existing feed
- Watermark is a bounded ID set (max 500) to cap memory
- Output format:
## <title>\n<url>\n\n<optional body>per item - Empty stdout on no-new — the caller treats that as silent
- Non-zero exit on fetch errors
Usage
Run a watcher directly from the terminal tool:
python $HERMES_HOME/skills/devops/watchers/scripts/watch_rss.py \
--name hn --url https://news.ycombinator.com/rss --max 5Watch a GitHub repo (set GITHUB_TOKEN in ${HERMES_HOME:-~/.hermes}/.env to avoid the 60 req/hr anonymous rate limit):
python $HERMES_HOME/skills/devops/watchers/scripts/watch_github.py \
--name hermes-issues --repo NousResearch/hermes-agent --scope issuesPoll an arbitrary JSON API:
python $HERMES_HOME/skills/devops/watchers/scripts/watch_http_json.py \
--name api --url https://api.example.com/events \
--id-field event_id --items-path data.eventsWiring into cron
Ask the agent to schedule a cron job with a prompt like:
> Every 15 minutes, run watch_rss.py --name hn --url https://news.ycombinator.com/rss. If it prints anything, summarize the headlines and deliver them. If it prints nothing, stay silent.
The agent invokes the script via the terminal tool inside the cron job's agent loop; no changes to cron's built-in --script flag are needed.
State files
Every watcher writes $HERMES_HOME/watcher-state/<name>.json. Inspect:
cat $HERMES_HOME/watcher-state/hn.jsonForce a replay (next run treated as first poll):
rm $HERMES_HOME/watcher-state/hn.jsonWriting your own
All three scripts use the same template: load watermark, fetch, diff, save, emit. scripts/_watermark.py is the shared helper; import it to get atomic writes + bounded ID set + first-run baseline for free. See any of the three reference scripts for how little boilerplate it takes.
Common Pitfalls
1. Printing a "no new items" header every tick. Callers rely on empty stdout = silent. If you print anything on an empty delta, you spam the channel. The shipped scripts handle this; custom scripts must too.
2. Expecting the first run to emit items. It won't — first run records a baseline. If you need an initial digest, delete the state file after the first run or add a --prime-with-latest N flag in your own script.
3. Unbounded watermark growth. The shared helper caps at 500 IDs. Raise it for high-churn feeds; lower it on constrained filesystems.
4. Putting the state dir where the agent's sandbox can't write. $HERMES_HOME/watcher-state/ is always writable. Docker/Modal backends may not see arbitrary host paths.
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