Compare commits
2 Commits
| Author | SHA1 | Date | |
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a581d03a2b | ||
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69b30152b4 |
@@ -1,100 +0,0 @@
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# Issue #954 Verification — maps skill guest_house / camp_site / bakery
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Status: PASS
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## Drift noted
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Issue #954 asked for validation on `upstream/main` (commit `c5a814b23`).
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Fresh `forge/main` did not contain `skills/productivity/maps/`, so the forge branch was behind upstream for this feature cluster.
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This branch ports the upstream maps skill files into the forge checkout and adds regression coverage.
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## Automated verification
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Command:
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```bash
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pytest -q tests/skills/test_maps_client.py
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```
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Result:
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- 5 passed
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Coverage added:
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- maps skill files exist in the repo
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- `guest_house` category maps to `tourism=guest_house`
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- `camp_site` category maps to `tourism=camp_site`
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- `bakery` expands to both `shop=bakery` and `amenity=bakery`
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- dual-key bakery results dedupe correctly
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- skill documentation lists the new categories and supersedes `find-nearby`
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## Manual evidence
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### 1) guest_house lookup
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Command:
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```bash
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python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Bath, United Kingdom" --category guest_house --limit 3
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```
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Observed results:
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- Henrietta House — 390.3 m
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- The Windsor — 437.2 m
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- The Old Rectory Bed & Breakfast — 495.7 m
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All returned `tourism=guest_house` in the raw tags.
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### 2) camp_site lookup
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Command:
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```bash
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python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Yosemite Valley, California" --category camp_site --limit 5
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```
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Observed result:
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- Yellow Pine Administrative Campground — 90.3 m
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Returned `tourism=camp_site` in the raw tags.
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### 3) bakery lookup via `shop=bakery`
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Command:
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```bash
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python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Lawrenceville, New Jersey" --category bakery --radius 5000 --limit 10
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```
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Observed results:
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- The Gingered Peach — 713.8 m
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- WildFlour Bakery — 741.9 m
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Both returned `shop=bakery` in the raw tags.
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### 4) bakery lookup via `amenity=bakery`
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Command:
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```bash
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python3 skills/productivity/maps/scripts/maps_client.py nearby --near "20735 Stevens Creek Boulevard, Cupertino, CA" --category bakery --radius 600 --limit 5
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```
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Observed result:
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- Paris Baguette — 28.6 m
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Returned `amenity=bakery` in the raw tags (and also includes `shop=bakery`), proving the dual-key union query reaches amenity-tagged bakeries too.
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## Conclusion
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PASS.
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- `guest_house` resolves correctly
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- `camp_site` resolves correctly
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- `bakery` resolves through both supported keys
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- forge/main drift from upstream/main was real and is addressed on this branch
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@@ -57,7 +57,7 @@ CONFIGURABLE_TOOLSETS = [
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("moa", "🧠 Mixture of Agents", "mixture_of_agents"),
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("tts", "🔊 Text-to-Speech", "text_to_speech"),
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("skills", "📚 Skills", "list, view, manage"),
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("todo", "📋 Task Planning", "todo"),
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("todo", "📋 Task Planning", "todo, ultraplan"),
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("memory", "💾 Memory", "persistent memory across sessions"),
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("session_search", "🔎 Session Search", "search past conversations"),
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("clarify", "❓ Clarifying Questions", "clarify"),
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@@ -1,199 +0,0 @@
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---
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name: maps
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description: >
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Location intelligence — geocode a place, reverse-geocode coordinates,
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find nearby places (46 POI categories), driving/walking/cycling
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distance + time, turn-by-turn directions, timezone lookup, bounding
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box + area for a named place, and POI search within a rectangle.
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Uses OpenStreetMap + Overpass + OSRM. Free, no API key.
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version: 1.2.0
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author: Mibayy
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license: MIT
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metadata:
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hermes:
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tags: [maps, geocoding, places, routing, distance, directions, nearby, location, openstreetmap, nominatim, overpass, osrm]
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category: productivity
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requires_toolsets: [terminal]
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supersedes: [find-nearby]
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---
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# Maps Skill
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Location intelligence using free, open data sources. 8 commands, 44 POI
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categories, zero dependencies (Python stdlib only), no API key required.
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Data sources: OpenStreetMap/Nominatim, Overpass API, OSRM, TimeAPI.io.
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This skill supersedes the old `find-nearby` skill — all of find-nearby's
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functionality is covered by the `nearby` command below, with the same
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`--near "<place>"` shortcut and multi-category support.
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## When to Use
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- User sends a Telegram location pin (latitude/longitude in the message) → `nearby`
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- User wants coordinates for a place name → `search`
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- User has coordinates and wants the address → `reverse`
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- User asks for nearby restaurants, hospitals, pharmacies, hotels, etc. → `nearby`
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- User wants driving/walking/cycling distance or travel time → `distance`
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- User wants turn-by-turn directions between two places → `directions`
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- User wants timezone information for a location → `timezone`
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- User wants to search for POIs within a geographic area → `area` + `bbox`
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## Prerequisites
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Python 3.8+ (stdlib only — no pip installs needed).
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Script path: `~/.hermes/skills/maps/scripts/maps_client.py`
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## Commands
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```bash
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MAPS=~/.hermes/skills/maps/scripts/maps_client.py
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```
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### search — Geocode a place name
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```bash
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python3 $MAPS search "Eiffel Tower"
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python3 $MAPS search "1600 Pennsylvania Ave, Washington DC"
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```
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Returns: lat, lon, display name, type, bounding box, importance score.
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### reverse — Coordinates to address
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```bash
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python3 $MAPS reverse 48.8584 2.2945
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```
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Returns: full address breakdown (street, city, state, country, postcode).
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### nearby — Find places by category
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```bash
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# By coordinates (from a Telegram location pin, for example)
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python3 $MAPS nearby 48.8584 2.2945 restaurant --limit 10
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python3 $MAPS nearby 40.7128 -74.0060 hospital --radius 2000
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# By address / city / zip / landmark — --near auto-geocodes
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python3 $MAPS nearby --near "Times Square, New York" --category cafe
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python3 $MAPS nearby --near "90210" --category pharmacy
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# Multiple categories merged into one query
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python3 $MAPS nearby --near "downtown austin" --category restaurant --category bar --limit 10
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```
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46 categories: restaurant, cafe, bar, hospital, pharmacy, hotel, guest_house,
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camp_site, supermarket, atm, gas_station, parking, museum, park, school,
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university, bank, police, fire_station, library, airport, train_station,
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bus_stop, church, mosque, synagogue, dentist, doctor, cinema, theatre, gym,
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swimming_pool, post_office, convenience_store, bakery, bookshop, laundry,
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car_wash, car_rental, bicycle_rental, taxi, veterinary, zoo, playground,
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stadium, nightclub.
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Each result includes: `name`, `address`, `lat`/`lon`, `distance_m`,
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`maps_url` (clickable Google Maps link), `directions_url` (Google Maps
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directions from the search point), and promoted tags when available —
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`cuisine`, `hours` (opening_hours), `phone`, `website`.
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### distance — Travel distance and time
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```bash
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python3 $MAPS distance "Paris" --to "Lyon"
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python3 $MAPS distance "New York" --to "Boston" --mode driving
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python3 $MAPS distance "Big Ben" --to "Tower Bridge" --mode walking
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```
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Modes: driving (default), walking, cycling. Returns road distance, duration,
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and straight-line distance for comparison.
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### directions — Turn-by-turn navigation
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```bash
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python3 $MAPS directions "Eiffel Tower" --to "Louvre Museum" --mode walking
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python3 $MAPS directions "JFK Airport" --to "Times Square" --mode driving
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```
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Returns numbered steps with instruction, distance, duration, road name, and
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maneuver type (turn, depart, arrive, etc.).
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### timezone — Timezone for coordinates
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```bash
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python3 $MAPS timezone 48.8584 2.2945
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python3 $MAPS timezone 35.6762 139.6503
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```
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Returns timezone name, UTC offset, and current local time.
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### area — Bounding box and area for a place
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```bash
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python3 $MAPS area "Manhattan, New York"
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python3 $MAPS area "London"
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```
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Returns bounding box coordinates, width/height in km, and approximate area.
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Useful as input for the bbox command.
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### bbox — Search within a bounding box
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```bash
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python3 $MAPS bbox 40.75 -74.00 40.77 -73.98 restaurant --limit 20
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```
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Finds POIs within a geographic rectangle. Use `area` first to get the
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bounding box coordinates for a named place.
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## Working With Telegram Location Pins
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When a user sends a location pin, the message contains `latitude:` and
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`longitude:` fields. Extract those and pass them straight to `nearby`:
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```bash
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# User sent a pin at 36.17, -115.14 and asked "find cafes nearby"
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python3 $MAPS nearby 36.17 -115.14 cafe --radius 1500
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```
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Present results as a numbered list with names, distances, and the
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`maps_url` field so the user gets a tap-to-open link in chat. For "open
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now?" questions, check the `hours` field; if missing or unclear, verify
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with `web_search` since OSM hours are community-maintained and not always
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current.
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## Workflow Examples
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**"Find Italian restaurants near the Colosseum":**
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1. `nearby --near "Colosseum Rome" --category restaurant --radius 500`
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— one command, auto-geocoded
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**"What's near this location pin they sent?":**
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1. Extract lat/lon from the Telegram message
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2. `nearby LAT LON cafe --radius 1500`
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**"How do I walk from hotel to conference center?":**
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1. `directions "Hotel Name" --to "Conference Center" --mode walking`
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**"What restaurants are in downtown Seattle?":**
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1. `area "Downtown Seattle"` → get bounding box
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2. `bbox S W N E restaurant --limit 30`
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## Pitfalls
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- Nominatim ToS: max 1 req/s (handled automatically by the script)
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- `nearby` requires lat/lon OR `--near "<address>"` — one of the two is needed
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- OSRM routing coverage is best for Europe and North America
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- Overpass API can be slow during peak hours; the script automatically
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falls back between mirrors (overpass-api.de → overpass.kumi.systems)
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- `distance` and `directions` use `--to` flag for the destination (not positional)
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- If a zip code alone gives ambiguous results globally, include country/state
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## Verification
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```bash
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python3 ~/.hermes/skills/maps/scripts/maps_client.py search "Statue of Liberty"
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# Should return lat ~40.689, lon ~-74.044
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python3 ~/.hermes/skills/maps/scripts/maps_client.py nearby --near "Times Square" --category restaurant --limit 3
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# Should return a list of restaurants within ~500m of Times Square
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```
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File diff suppressed because it is too large
Load Diff
@@ -1,135 +0,0 @@
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"""Regression tests for the bundled maps skill."""
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from __future__ import annotations
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import importlib.util
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from pathlib import Path
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from types import SimpleNamespace
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SCRIPT_PATH = (
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Path(__file__).resolve().parents[2]
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/ "skills/productivity/maps/scripts/maps_client.py"
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)
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SKILL_PATH = (
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Path(__file__).resolve().parents[2]
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/ "skills/productivity/maps/SKILL.md"
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)
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def load_module():
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assert SCRIPT_PATH.exists(), f"missing maps client script: {SCRIPT_PATH}"
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spec = importlib.util.spec_from_file_location("maps_client_test", SCRIPT_PATH)
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module = importlib.util.module_from_spec(spec)
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assert spec.loader is not None
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spec.loader.exec_module(module)
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return module
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def test_maps_skill_files_exist():
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assert SCRIPT_PATH.exists()
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assert SKILL_PATH.exists()
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def test_category_tags_cover_guest_house_camp_site_and_dual_key_bakery():
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module = load_module()
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assert module.CATEGORY_TAGS["guest_house"] == ("tourism", "guest_house")
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assert module.CATEGORY_TAGS["camp_site"] == ("tourism", "camp_site")
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assert module.CATEGORY_TAGS["bakery"] == [
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("shop", "bakery"),
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("amenity", "bakery"),
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]
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assert module._tags_for("bakery") == [
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("shop", "bakery"),
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("amenity", "bakery"),
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]
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def test_build_overpass_queries_include_all_supported_tags():
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module = load_module()
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bakery_query = module.build_overpass_nearby(
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None,
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None,
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40.0,
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-74.0,
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500,
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10,
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tag_pairs=module._tags_for("bakery"),
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)
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assert 'node["shop"="bakery"]' in bakery_query
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assert 'way["shop"="bakery"]' in bakery_query
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assert 'node["amenity"="bakery"]' in bakery_query
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assert 'way["amenity"="bakery"]' in bakery_query
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guest_house_query = module.build_overpass_nearby(
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None,
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None,
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40.0,
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-74.0,
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500,
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10,
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tag_pairs=module._tags_for("guest_house"),
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)
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assert 'node["tourism"="guest_house"]' in guest_house_query
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assert 'way["tourism"="guest_house"]' in guest_house_query
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camp_site_bbox = module.build_overpass_bbox(
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None,
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None,
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39.0,
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-75.0,
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41.0,
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-73.0,
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10,
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tag_pairs=module._tags_for("camp_site"),
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)
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assert 'node["tourism"="camp_site"]' in camp_site_bbox
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assert 'way["tourism"="camp_site"]' in camp_site_bbox
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|
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def test_cmd_nearby_dedupes_dual_tag_bakery_results(monkeypatch, capsys):
|
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module = load_module()
|
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|
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duplicate_bakery = {
|
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"elements": [
|
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{
|
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"type": "node",
|
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"id": 101,
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"lat": 40.0,
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"lon": -74.0,
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"tags": {"name": "Wild Flour", "shop": "bakery"},
|
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},
|
||||
{
|
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"type": "node",
|
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"id": 101,
|
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"lat": 40.0,
|
||||
"lon": -74.0,
|
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"tags": {"name": "Wild Flour", "amenity": "bakery"},
|
||||
},
|
||||
]
|
||||
}
|
||||
|
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monkeypatch.setattr(module, "overpass_query", lambda query: duplicate_bakery)
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args = SimpleNamespace(
|
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lat="40.0",
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lon="-74.0",
|
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near=None,
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category="bakery",
|
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category_list=[],
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radius=500,
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limit=10,
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)
|
||||
|
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module.cmd_nearby(args)
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out = capsys.readouterr().out
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assert '"count": 1' in out
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assert '"Wild Flour"' in out
|
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|
||||
|
||||
def test_skill_doc_lists_new_categories_and_supersession():
|
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text = SKILL_PATH.read_text(encoding="utf-8")
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assert "guest_house" in text
|
||||
assert "camp_site" in text
|
||||
assert "bakery" in text
|
||||
assert "supersedes: [find-nearby]" in text
|
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@@ -294,22 +294,32 @@ class TestBuiltinDiscovery:
|
||||
"tools.browser_tool",
|
||||
"tools.clarify_tool",
|
||||
"tools.code_execution_tool",
|
||||
"tools.crisis_tool",
|
||||
"tools.cronjob_tools",
|
||||
"tools.delegate_tool",
|
||||
"tools.file_tools",
|
||||
"tools.homeassistant_tool",
|
||||
"tools.image_generation_tool",
|
||||
"tools.local_inference_tool",
|
||||
"tools.memory_tool",
|
||||
"tools.mixture_of_agents_tool",
|
||||
"tools.process_registry",
|
||||
"tools.rl_training_tool",
|
||||
"tools.scavenger_fixer",
|
||||
"tools.send_message_tool",
|
||||
"tools.session_search_tool",
|
||||
"tools.skill_manager_tool",
|
||||
"tools.skills_tool",
|
||||
"tools.sovereign_router",
|
||||
"tools.sovereign_scavenger",
|
||||
"tools.sovereign_teleport",
|
||||
"tools.static_analyzer",
|
||||
"tools.symbolic_verify",
|
||||
"tools.terminal_tool",
|
||||
"tools.todo_tool",
|
||||
"tools.tts_tool",
|
||||
"tools.ultraplan",
|
||||
"tools.verify_tool",
|
||||
"tools.vision_tools",
|
||||
"tools.web_tools",
|
||||
}
|
||||
|
||||
81
tests/tools/test_ultraplan_tool.py
Normal file
81
tests/tools/test_ultraplan_tool.py
Normal file
@@ -0,0 +1,81 @@
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import json
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from pathlib import Path
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from toolsets import resolve_toolset
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from tools.registry import registry
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def test_create_action_saves_markdown_and_json(tmp_path):
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from tools.ultraplan import ultraplan_tool
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result = json.loads(
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ultraplan_tool(
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action="create",
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mission="Daily autonomous planning",
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streams=[
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{
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"id": "A",
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"name": "Backlog burn",
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"phases": [
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{"id": "A1", "name": "Triage", "artifact": "issue list"},
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{"id": "A2", "name": "Ship", "dependencies": ["A1"], "artifact": "PR"},
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],
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}
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],
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base_dir=str(tmp_path),
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)
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)
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assert result["success"] is True
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assert Path(result["file_path"]).exists()
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assert Path(result["json_path"]).exists()
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assert "Work Streams" in Path(result["file_path"]).read_text(encoding="utf-8")
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def test_load_action_returns_saved_plan(tmp_path):
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from tools.ultraplan import ultraplan_tool
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created = json.loads(
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ultraplan_tool(
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action="create",
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date="20260422",
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mission="Mission from saved plan",
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base_dir=str(tmp_path),
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)
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)
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loaded = json.loads(
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ultraplan_tool(
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action="load",
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date="20260422",
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base_dir=str(tmp_path),
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)
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)
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assert created["success"] is True
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assert loaded["success"] is True
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assert loaded["plan"]["mission"] == "Mission from saved plan"
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assert loaded["file_path"].endswith("ultraplan_20260422.md")
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def test_cron_spec_returns_daily_schedule_and_prompt():
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from tools.ultraplan import ultraplan_tool
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result = json.loads(ultraplan_tool(action="cron_spec"))
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assert result["success"] is True
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assert result["schedule"] == "0 6 * * *"
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assert "Ultraplan" in result["prompt"]
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assert "ultraplan_YYYYMMDD.md" in result["prompt"]
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def test_registry_registers_ultraplan_tool():
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import tools.ultraplan # noqa: F401
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entry = registry.get_entry("ultraplan")
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assert entry is not None
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assert entry.toolset == "todo"
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def test_default_toolsets_include_ultraplan():
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assert "ultraplan" in resolve_toolset("todo")
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assert "ultraplan" in resolve_toolset("hermes-cli")
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@@ -290,6 +290,9 @@ def load_ultraplan(date: str, base_dir: Path = None) -> Optional[Ultraplan]:
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return None
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DEFAULT_ULTRAPLAN_SCHEDULE = "0 6 * * *"
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def generate_daily_cron_prompt() -> str:
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"""Generate the prompt for the daily ultraplan cron job."""
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return """Generate today's Ultraplan.
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@@ -298,9 +301,9 @@ Steps:
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1. Check open Gitea issues assigned to you
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2. Check open PRs needing review
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3. Check fleet health status
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4. Decompose work into parallel streams
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5. Generate ultraplan_YYYYMMDD.md
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6. File Gitea issue with the plan
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4. Decompose work into parallel streams with concrete phases and artifacts
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5. Use the ultraplan tool to save ~/.timmy/cron/ultraplan_YYYYMMDD.md and the matching JSON sidecar
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6. Optionally file a Gitea issue with the plan summary
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Output format:
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- Mission statement
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@@ -308,3 +311,176 @@ Output format:
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- Dependency map
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- Success metrics
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"""
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def generate_daily_cron_job_spec(schedule: str = DEFAULT_ULTRAPLAN_SCHEDULE) -> Dict[str, str]:
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"""Return a reusable cron job spec for daily Ultraplan generation."""
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return {
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"name": "Daily Ultraplan",
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"schedule": schedule,
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"prompt": generate_daily_cron_prompt(),
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"path_pattern": "~/.timmy/cron/ultraplan_YYYYMMDD.md",
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}
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def _resolve_base_dir(base_dir: Optional[str | Path]) -> Path:
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"""Normalize the requested Ultraplan base directory."""
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if base_dir is None:
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return Path.home() / ".timmy" / "cron"
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return Path(base_dir).expanduser()
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def ultraplan_tool(
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action: str,
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date: Optional[str] = None,
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mission: str = "",
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streams: Optional[List[Dict[str, Any]]] = None,
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metrics: Optional[Dict[str, Any]] = None,
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notes: str = "",
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base_dir: Optional[str] = None,
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) -> str:
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"""Create/load Ultraplan artifacts and expose a daily cron spec."""
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from tools.registry import tool_error, tool_result
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action = (action or "").strip().lower()
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resolved_base_dir = _resolve_base_dir(base_dir)
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try:
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if action == "create":
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plan = create_ultraplan(date=date, mission=mission, streams=streams or [])
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if metrics:
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plan.metrics = metrics
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if notes:
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plan.notes = notes
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md_path = save_ultraplan(plan, base_dir=resolved_base_dir)
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json_path = resolved_base_dir / f"ultraplan_{plan.date}.json"
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return tool_result(
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success=True,
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action="create",
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date=plan.date,
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file_path=str(md_path),
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json_path=str(json_path),
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plan=plan.to_dict(),
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)
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if action == "load":
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plan_date = date or datetime.now().strftime("%Y%m%d")
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plan = load_ultraplan(plan_date, base_dir=resolved_base_dir)
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if plan is None:
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return tool_error(
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f"No Ultraplan found for {plan_date}",
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success=False,
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action="load",
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date=plan_date,
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)
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return tool_result(
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success=True,
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action="load",
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date=plan.date,
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file_path=str(resolved_base_dir / f"ultraplan_{plan.date}.md"),
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json_path=str(resolved_base_dir / f"ultraplan_{plan.date}.json"),
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plan=plan.to_dict(),
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markdown=plan.to_markdown(),
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)
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if action == "cron_spec":
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spec = generate_daily_cron_job_spec()
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return tool_result(success=True, action="cron_spec", **spec)
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return tool_error(
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f"Unknown Ultraplan action: {action}",
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success=False,
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action=action,
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)
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except Exception as e:
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return tool_error(f"Ultraplan {action or 'tool'} failed: {e}", success=False, action=action)
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ULTRAPLAN_SCHEMA = {
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"name": "ultraplan",
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"description": (
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"Create or load daily Ultraplan planning artifacts under ~/.timmy/cron/ and "
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"return a reusable cron spec for autonomous planning. Use this when you want "
|
||||
"a concrete markdown/json plan file with streams, phases, dependencies, and metrics."
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),
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"parameters": {
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||||
"type": "object",
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||||
"properties": {
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||||
"action": {
|
||||
"type": "string",
|
||||
"enum": ["create", "load", "cron_spec"],
|
||||
"description": "Operation to perform",
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||||
},
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"date": {
|
||||
"type": "string",
|
||||
"description": "Plan date as YYYYMMDD. Defaults to today for create/load.",
|
||||
},
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||||
"mission": {
|
||||
"type": "string",
|
||||
"description": "High-level mission statement for today's plan.",
|
||||
},
|
||||
"streams": {
|
||||
"type": "array",
|
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"description": "Optional work streams with phases/artifacts/dependencies for create.",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {"type": "string"},
|
||||
"name": {"type": "string"},
|
||||
"phases": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {"type": "string"},
|
||||
"name": {"type": "string"},
|
||||
"description": {"type": "string"},
|
||||
"artifact": {"type": "string"},
|
||||
"dependencies": {
|
||||
"type": "array",
|
||||
"items": {"type": "string"},
|
||||
},
|
||||
},
|
||||
"required": ["name"],
|
||||
},
|
||||
},
|
||||
},
|
||||
"required": ["name"],
|
||||
},
|
||||
},
|
||||
"metrics": {
|
||||
"type": "object",
|
||||
"description": "Optional success metrics to store on the plan.",
|
||||
"additionalProperties": True,
|
||||
},
|
||||
"notes": {
|
||||
"type": "string",
|
||||
"description": "Optional free-form notes appended to the saved plan.",
|
||||
},
|
||||
"base_dir": {
|
||||
"type": "string",
|
||||
"description": "Optional override for the Ultraplan storage directory.",
|
||||
},
|
||||
},
|
||||
"required": ["action"],
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
from tools.registry import registry
|
||||
|
||||
registry.register(
|
||||
name="ultraplan",
|
||||
toolset="todo",
|
||||
schema=ULTRAPLAN_SCHEMA,
|
||||
handler=lambda args, **_kw: ultraplan_tool(
|
||||
action=args.get("action", ""),
|
||||
date=args.get("date"),
|
||||
mission=args.get("mission", ""),
|
||||
streams=args.get("streams"),
|
||||
metrics=args.get("metrics"),
|
||||
notes=args.get("notes", ""),
|
||||
base_dir=args.get("base_dir"),
|
||||
),
|
||||
emoji="🗺️",
|
||||
)
|
||||
|
||||
@@ -47,7 +47,7 @@ _HERMES_CORE_TOOLS = [
|
||||
# Text-to-speech
|
||||
"text_to_speech",
|
||||
# Planning & memory
|
||||
"todo", "memory",
|
||||
"todo", "ultraplan", "memory",
|
||||
# Session history search
|
||||
"session_search",
|
||||
# Clarifying questions
|
||||
@@ -157,8 +157,8 @@ TOOLSETS = {
|
||||
},
|
||||
|
||||
"todo": {
|
||||
"description": "Task planning and tracking for multi-step work",
|
||||
"tools": ["todo"],
|
||||
"description": "Task planning and tracking for multi-step work, including daily Ultraplan artifacts",
|
||||
"tools": ["todo", "ultraplan"],
|
||||
"includes": []
|
||||
},
|
||||
|
||||
|
||||
Reference in New Issue
Block a user