Skill Market

watchers

Poll RSS, JSON APIs, and GitHub with watermark dedup.

GitHub
githubcommunityaiai-agentai-agentsanthropicchatgptclaude
0.0
0 installs245.9K GitHub starsby NousResearch

Skill Introduction

Overview
Poll RSS, JSON APIs, and GitHub with watermark dedup.

Core value

Turns reusable Testing know-how into an installable skill, helping users complete github, community, ai, ai-agent work faster.

Target users

  • Developers, testers, and maintainers who handle Testing tasks in Focus Code.
  • Teams that already trust workflows or content from NousResearch.
  • Users who want standardized prompts, steps, or conventions instead of repeating setup work.

Best practices

  • Read the skill content first to confirm required inputs, expected outputs, and dependencies.
  • Try it on a small task before relying on it for critical work.
  • Add project-specific constraints such as coding style, target platform, test expectations, and delivery format.
  • For external sources, verify the source link, version, and recent maintenance activity.

Best use cases

  • Tasks related to github, community, ai, ai-agent that need a reusable execution flow.
  • Converting a community repo, team convention, or personal workflow into day-to-day assistance.
  • Starting from a proven skill instead of writing prompts or procedures from scratch.

Limits and boundaries

  • Results depend on the quality of the original skill content and may need human correction.
  • It does not replace code review, tests, security review, or professional judgment.
  • External tools, APIs, account permissions, and local dependencies still need separate setup.

Differentiation

  • Structured around Testing, making it easier to discover and reuse than loose prompt snippets.
  • Marked as GitHub, which helps users judge trust and maintenance expectations.
  • Keeps the original source link available for repository, documentation, or discussion follow-up.
  • Tagged with github, community, ai, ai-agent, so it can be filtered by concrete task intent.

Install and use

Install
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focus install watchers-33cd67
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Detail Preview

SKILL.md

Primary filemarkdown5 KB

name: watchers description: Poll RSS, JSON APIs, and GitHub with watermark dedup. version: 1.0.0 author: Hermes Agent license: MIT platforms: [linux, macos] metadata: hermes: tags: [cron, polling, rss, github, http, automation, monitoring] category: devops requires_toolsets: [terminal] related_skills: []

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.

ScriptWhat it watchesDedup key
watch_rss.pyRSS 2.0 or Atom feed URL<guid> / <id>
watch_http_json.pyAny JSON endpoint returning a list of objectsConfigurable id field
watch_github.pyGitHub issues / pulls / releases / commits for a repoid / 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 5

Watch a GitHub repo (set GITHUB_TOKEN in ~/.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 issues

Poll 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.events

Wiring 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.json

Force a replay (next run treated as first poll):

rm $HERMES_HOME/watcher-state/hn.json

Writing 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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