* feat(skills): add html-artifact skill, fold in sketch + architecture-diagram + concept-diagrams
Adds a unified `html-artifact` creative skill that produces self-contained,
single-file HTML artifacts — concept explainers, implementation plans,
status/incident reports, code-review walkthroughs, technical + educational
SVG diagrams, multi-variant design comparisons, and throwaway editors that
export their state back to the clipboard. Grounded in Anthropic's
html-effectiveness gallery (MIT); the house style (token block, serif/sans/
mono split, hand-rolled diffs, inline-SVG diagrams, graceful degradation) is
distilled from reading all 20 reference files.
Supersedes and removes three overlapping skills, folding their unique value in:
- sketch -> the fidelity dial (throwaway vs presentation) + the
multi-variant comparison layouts + the browser-vision
verify loop (references/fidelity-and-verify.md)
- architecture-diagram-> the dark "infra" token variant + double-rect masking +
semantic component palette (references/dark-tech.md,
templates/diagram.html infra mode)
- concept-diagrams -> the 9-ramp educational color system + the concept
archetype library (references/concept-archetypes.md,
the light design system in templates/diagram.html)
Structure:
- SKILL.md (description exactly 60 chars), 6 references, 3 templates
- templates verified by headless-Chrome render + vision inspection
- editor export logic (file://-safe clipboard, Promise-normalized) verified in node
Cross-references updated in claude-design (new disambiguation table row drawing
the design-taste vs information-artifact boundary), design-md, pretext, spike,
and kanban-video-orchestrator. Website skill docs + catalogs regenerated;
stale EN/zh-Hans per-skill pages pruned and i18n cross-refs fixed.
Not folded (intentionally orthogonal): excalidraw (.excalidraw JSON), p5js
(generative canvas), claude-design / popular-web-designs / design-md (visual
design taste / brand vocab / token spec).
* feat(skills): ship html-effectiveness gallery as fetched reference examples
Add scripts/fetch-examples.sh (idempotent clone/pull of Anthropic's MIT
html-effectiveness gallery) + references/examples.md mapping each of the 20
example files to a mode so the agent reads the right worked example. The clone
lands in references/examples/ and is gitignored (it's a 384KB upstream repo,
not vendored). SKILL.md workflow + reference list now point at it; falls back to
the distilled pattern references when offline.
* feat(skills): make reading a gallery example a required authoring step
Reading the matching html-effectiveness example is now workflow step 2 (was an
optional aside in step 3): fetch the gallery, read_file the file for your mode,
mirror its structure. Models skip optional steps; the examples are the ground
truth, so consulting one is mandatory. Added an 'Example' column to the
mode->build quick-reference table and a 'don't skip the example' pitfall.
Also dogfooded the skill: read 03-code-review-pr.html and 13-flowchart-diagram.html
raw and reconciled the distilled references against source — aligned diff-row tint
opacity to the source's 0.15 (was 0.18) and added the .ctx/.hunk rows in
house-style.md + base.html so they match 03-code-review-pr.html verbatim.
* docs(skills): explain the consolidation + bundled-vs-optional rationale
The supersession note only stated *what* was folded, not *why* the prune is
sound. Expand SKILL.md's intro into a 'Why this skill exists' section: the three
former skills emitted the same artifact and overlapped, so consolidating removes
which-one-do-I-load ambiguity; and the optional->bundled promotion of
concept-diagrams is footprint-safe because this skill has zero deps (only cost is
the 60-char description; everything else is progressive-disclosure). States the
bundling dividing line explicitly: zero install cost + broadly useful gets
bundled, real install cost (hyperframes: Node+FFmpeg+Chromium) stays optional.
Regenerated website per-skill page to match.
5 KiB
| title | sidebar_label | description |
|---|---|---|
| Watchers — Poll RSS, JSON APIs, and GitHub with watermark dedup | Watchers | Poll RSS, JSON APIs, and GitHub with watermark dedup |
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
Watchers
Poll RSS, JSON APIs, and GitHub with watermark dedup.
Skill metadata
| Source | Optional — install with hermes skills install official/devops/watchers |
| Path | optional-skills/devops/watchers |
| Version | 1.0.0 |
| Author | Hermes Agent |
| License | MIT |
| Platforms | linux, macos |
| Tags | cron, polling, rss, github, http, automation, monitoring |
Reference: full SKILL.md
:::info The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active. :::
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:
- Fetches data from the external source
- Compares against a watermark file of previously-seen IDs
- Writes the new watermark back
- 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 5
Watch 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 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
- 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.
- 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 Nflag in your own script. - Unbounded watermark growth. The shared helper caps at 500 IDs. Raise it for high-churn feeds; lower it on constrained filesystems.
- 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.