Poll RSS, JSON APIs, and GitHub with watermark dedup. An agent skill from Luciole-Studio/Misaka-Agent.

MITAuto-check: notesProductivity & Automation

Install Watchers

skills CLI
$ npx skills add Luciole-Studio/Misaka-Agent --skill watchers -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Luciole-Studio/Misaka-Agent watchers --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Luciole-Studio/Misaka-Agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/misaka/core/skills/assets/optional/devops/watchers .claude/skills/watchers && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
watchers
GitHub stars
171
Used in
2 other repos
Token cost
~1.1k tokens
SKILL.md length
543 words
Files
5 (incl. scripts)
Skills in repo
77
Repo updated
First seen
Licence
MIT

At a glance

Poll RSS, JSON APIs, and GitHub with watermark dedup. An agent skill from Luciole-Studio/Misaka-Agent.

  • Works in 4 steps: Fetches data from the external source → Compares against a watermark file of… → Writes the new watermark back → …
  • Productivity & Automation work in your project
  • SKILL.md covers When to Use, Mental model, Ready-made scripts and Usage, plus 4 more sections
  • Runs Python scripts from its folder; calls python; reaches news.ycombinator.com; needs GITHUB_TOKEN

What it does

Watchers is an agent skill from Luciole-Studio/Misaka-Agent. Poll RSS, JSON APIs, and GitHub with watermark dedup.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `scripts/_watermark.py`, `scripts/watch_github.py` and `scripts/watch_http_json.py`).

It sits in Productivity & Automation. It works with GitHub. The repository describes itself as: A multi-agent research system for the humanities and social sciences. The licence is MIT.

When your agent uses it

  • Productivity & Automation work in your project

Example prompts

  • “/watchers”

Requirements

  • Python 3
  • Docker
  • A credential in GITHUB_TOKEN

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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)

What it can do on your machine

Read from SKILL.md and the folder at commit 3bcf7a3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 4 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • news.ycombinator.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GITHUB_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Watchers loads about 1.1k tokens when it runs. Until then it costs about 16 tokens; SKILL.md has 543 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~16
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:65
    HUB_TOKEN` in `${HERMES_HOME:-~/.hermes}/.env` to avoid the 60 req/hr anonymous rate limit):

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Luciole-Studio/Misaka-Agent at commit 3bcf7a3, republished under its MIT licence (© Luciole-Studio). 543 words, ~1,123 tokens.

Download SKILL.mdSave it as .claude/skills/watchers/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
watchers
description
Poll RSS, JSON APIs, and GitHub with watermark dedup.
version
1.0.0
author
Hermes Agent
license
MIT
platforms
linux, macos

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
Show full SKILL.md (248 more words)Show less

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.

© Luciole-Studio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts) in misaka/core/skills/assets/optional/devops/watchers of Luciole-Studio/Misaka-Agent.

  • SKILL.md
  • scripts/_watermark.py
  • scripts/watch_github.py
  • scripts/watch_http_json.py
  • scripts/watch_rss.py

Open the folder on GitHubat commit 3bcf7a3

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in Luciole-Studio/Misaka-Agent, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Watchers next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Watchers compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Watchers this skillLuciole-Studio/Misaka-Agent1712 repos~1.1kAutomated safety check: NotesMIT
Connect Apps with ComposioComposioHQ/awesome-claude-skills77k3 repos~557Automated safety check: PassNone
Daily BriefingRion-Wu-tech/ai-daily-briefing173—~3.3kAutomated safety check: PassMIT
Superset Automatesuperset-sh/superset15k—~1.4kAutomated safety check: PassCustom licence
Composio Cloud Toolsquarqlabs/argus279—~543Automated safety check: PassApache-2.0
ClawdiClawdi-AI/clawdi103—~4.9kAutomated safety check: NotesMIT

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Works with

Questions about Watchers

What does Watchers do?

Poll RSS, JSON APIs, and GitHub with watermark dedup. An agent skill from Luciole-Studio/Misaka-Agent. Watchers is an agent skill from Luciole-Studio/Misaka-Agent. Poll RSS, JSON APIs, and GitHub with watermark dedup.

When should I use Watchers?

Watchers fits situations like: productivity & Automation work in your project.

How do I install Watchers in Claude Code?

Run `npx skills add Luciole-Studio/Misaka-Agent --skill watchers -a claude-code`. Or copy the skill folder (misaka/core/skills/assets/optional/devops/watchers in Luciole-Studio/Misaka-Agent) into .claude/skills/watchers in your project. Claude Code loads it when a task matches its description.

How do I install Watchers in Codex?

Run `npx skills add Luciole-Studio/Misaka-Agent --skill watchers -a codex`. Or copy the skill folder (misaka/core/skills/assets/optional/devops/watchers in Luciole-Studio/Misaka-Agent) into .agents/skills/watchers in your project. Codex loads it when a task matches its description.

Can I use Watchers in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Luciole-Studio/Misaka-Agent --skill watchers -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/watchers, .gemini/skills/watchers, .github/skills/watchers and .opencode/skills/watchers in your project.

What does Watchers need to run?

Going by SKILL.md and its folder, Watchers needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named GITHUB_TOKEN. Our summary lists: Python 3; Docker; A credential in GITHUB_TOKEN.

Does Watchers access the network?

SKILL.md names 1 domain. In commands or code: news.ycombinator.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Watchers safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Watchers use?

Watchers is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Watchers use?

About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Watchers?

Skills that share tags, products or a category with Watchers: Connect Apps with Composio (ComposioHQ/awesome-claude-skills, 77k stars), Daily Briefing (Rion-Wu-tech/ai-daily-briefing, 173 stars), Superset Automate (superset-sh/superset, 15k stars) and Composio Cloud Tools (quarqlabs/argus, 279 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Watchers?

Luciole-Studio (a GitHub organization) maintains it in Luciole-Studio/Misaka-Agent, which has 171 GitHub stars. The repository holds 77 skills in this directory. The repository was last updated on October 8, 2026.

Source: Luciole-Studio/Misaka-Agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.