Install
openclaw skills install unformal-notificationsGet notified when someone completes an Unformal Pulse — via a scheduled Claude Code routine (hourly), a local desktop listener (real-time macOS notifications...
openclaw skills install unformal-notificationsThree ways to get notified about new responses on your Unformal Pulse. Pick one — or combine.
Trigger on any of these:
POST /api/v1/signupGET /api/v1/pulses or the Studio URLBest for: always-on monitoring that shows up in your Claude Code desktop sidebar alongside your other routines. Runs locally, can use your local secrets files, and you pick the schedule visually in the desktop UI.
Ask Claude:
"Create a Claude Code desktop routine called
unformal-new-responsesthat checks for new completed responses on my Unformal Pulse<PULSE_ID>using API key<API_KEY>. It should track the last-seen timestamp in~/.unformal/last-seen, only fetch new responses since that marker, and give me a concise digest (sentiment + summary + key quotes) or say 'No new responses' if there are none."
Creates a directory at ~/.claude/scheduled-tasks/<routine-name>/ containing a single SKILL.md file with:
---
name: unformal-new-responses
description: Check for new completed responses on active Unformal Pulses
---
1. Load secrets: `source /path/to/load-secrets.sh` (optional — if keys are
in a local env file, use it; otherwise embed API key inline)
2. Read marker: `SINCE=$(cat ~/.unformal/last-seen 2>/dev/null || echo 0)`
3. Fetch new responses:
```bash
TMP=$(mktemp)
curl -fsS "https://unformal.ai/api/v1/pulses/<PULSE_ID>/conversations?completedSince=$SINCE" \
-H "Authorization: Bearer <API_KEY>" > "$TMP"
python3 << PYEOF
import json
with open("$TMP") as f:
d = json.load(f)
items = d.get("data", [])
completed = [c for c in items if c.get("status") == "completed"]
if not completed:
print("NONE")
else:
print("FOUND " + str(len(completed)))
for c in completed:
echo = c.get("echo") or {}
print("---")
print("id: " + str(c.get("id", "")))
print("sentiment: " + str(echo.get("sentimentScore", "?")) + "/10")
print("summary: " + (echo.get("summary") or "(no summary)")[:300])
for q in (echo.get("keyQuotes") or [])[:3]:
print("quote: " + str(q)[:200])
PYEOF
python3 -c "import time; print(int(time.time()*1000))" > ~/.unformal/last-seen
### Setting the schedule
After creating the SKILL.md file, the routine appears in the Claude Code desktop sidebar under "Routines". **Set the cron schedule from the desktop UI** — click the routine and pick Daily / Weekdays / Custom / etc. The schedule is stored by the desktop app; the SKILL.md only defines the task.
### Key points
- Runs locally on your machine (unlike remote triggers) — has access to `~/` and local secrets
- Does NOT appear in [claude.ai/code/scheduled](https://claude.ai/code/scheduled) (that's the remote triggers UI — a separate system)
- Minimum cadence is whatever the desktop UI allows (typically 1 minute+)
- You can edit the SKILL.md anytime; changes take effect on next run
---
## Option B — Local desktop listener (real-time macOS notifications)
**Best for**: live in-session awareness while you're actively working. Runs on your machine, shows native OS notifications the second a response comes in.
### One-time install
```bash
mkdir -p ~/bin
curl -fsS https://unformal.ai/unformal-listen.sh > ~/bin/unformal-listen
chmod +x ~/bin/unformal-listen
export UNFORMAL_API_KEY=unf_xxx # add to ~/.zshrc for persistence
unformal-listen # lists your Pulses
unformal-listen <pulse_id> # starts listening
Leave it running in a spare terminal tab. Every completion:
notify-send fallback)~/.unformal/inbox/<timestamp>.jsonBest for: one-off lookups. The user asks "any new responses?" and you query the API right there.
# Responses completed in the last hour
SINCE=$(python3 -c "import time; print(int(time.time()*1000) - 3600000)")
curl -fsS "https://unformal.ai/api/v1/pulses/<PULSE_ID>/conversations?completedSince=$SINCE" \
-H "Authorization: Bearer $UNFORMAL_API_KEY" | \
jq '[.data[] | select(.status=="completed")] | sort_by(.completedAt) | reverse'
For "since last check" semantics with a local marker file:
mkdir -p ~/.unformal
LAST=$(cat ~/.unformal/last-seen 2>/dev/null || echo 0)
curl -fsS "https://unformal.ai/api/v1/pulses/<PULSE_ID>/conversations?completedSince=$LAST" \
-H "Authorization: Bearer $UNFORMAL_API_KEY"
python3 -c "import time; print(int(time.time()*1000))" > ~/.unformal/last-seen
Summarize the newest events from the inbox:
ls -t ~/.unformal/inbox/*.json 2>/dev/null | head -5 | while read f; do
cat "$f" | jq -r '{
completedAt: .completedAt,
summary: (.echo.summary // .summary // "no summary"),
sentiment: .echo.sentimentScore,
quotes: (.echo.keyQuotes // [] | .[0:2])
}'
done
Fall back to the on-demand API call (Option C above).
mkdir -p ~/.unformal/processed
mv ~/.unformal/inbox/*.json ~/.unformal/processed/ 2>/dev/null || true
Each file in ~/.unformal/inbox/ (and each element of the API .data[] array) looks like:
{
"conversationId": "k17abc...",
"pulseId": "k97xyz...",
"echo": {
"fields": {"budget_range": "$10k-20k", "timeline": "Q3"},
"summary": "Strong fit. Mid-size agency ready to pilot.",
"keyQuotes": ["We spend 3 hours weekly on status reports"],
"sentimentScore": 7
},
"completedAt": "2026-04-17T10:32:01Z",
"metadata": {"duration": 240, "messageCount": 12}
}
unformal-api — create and manage Pulses (use first if no Pulse exists yet)schedule skill — for Option A remote triggers