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Watchers

OrganizationPopular
NousResearch
watchers

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

Overview

PublisherNousResearch
Repositoryhermes-agent
Skill namewatchers
Stars
250.4K
Forks
53.5K
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NousResearch on GitHub. Read the source before you install it.

Installation

Install the Watchers AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NousResearch/hermes-agent/tree/main/optional-skills/devops/watchers
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NousResearch/hermes-agent.git /tmp/hermes-agent
mkdir -p .claude/skills
cp -r /tmp/hermes-agent/optional-skills/devops/watchers .claude/skills/watchers
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Watchers in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Watchers on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Watchers is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

bash
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_HOME:-~/.hermes}/.env to avoid the 60 req/hr anonymous rate limit):

bash
python $HERMES_HOME/skills/devops/watchers/scripts/watch_github.py \
  --name hermes-issues --repo NousResearch/hermes-agent --scope issues

Poll an arbitrary JSON API:

bash
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:

bash
cat $HERMES_HOME/watcher-state/hn.json

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

bash
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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Watchers AI skill do?

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

Why use Watchers on TypingMind?

Because you install it once and use it with any model. Watchers is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Watchers in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NousResearch/hermes-agent/tree/main/optional-skills/devops/watchers. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Watchers?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Watchers?

As many as you like. As long as a model supports skills, you can use Watchers with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Watchers AI skill free?

Yes. It is published on GitHub by NousResearch under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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