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Author SHA1 Message Date
Alexander Whitestone
a581d03a2b feat: integrate Ultraplan with tools and core toolsets for #840
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Lint / lint (pull_request) Failing after 14s
Refs #840
2026-04-22 11:13:47 -04:00
Alexander Whitestone
69b30152b4 wip: add failing Ultraplan integration coverage for #840
Refs #840
2026-04-22 11:08:33 -04:00
9 changed files with 274 additions and 1734 deletions

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@@ -1,100 +0,0 @@
# Issue #954 Verification — maps skill guest_house / camp_site / bakery
Status: PASS
## Drift noted
Issue #954 asked for validation on `upstream/main` (commit `c5a814b23`).
Fresh `forge/main` did not contain `skills/productivity/maps/`, so the forge branch was behind upstream for this feature cluster.
This branch ports the upstream maps skill files into the forge checkout and adds regression coverage.
## Automated verification
Command:
```bash
pytest -q tests/skills/test_maps_client.py
```
Result:
- 5 passed
Coverage added:
- maps skill files exist in the repo
- `guest_house` category maps to `tourism=guest_house`
- `camp_site` category maps to `tourism=camp_site`
- `bakery` expands to both `shop=bakery` and `amenity=bakery`
- dual-key bakery results dedupe correctly
- skill documentation lists the new categories and supersedes `find-nearby`
## Manual evidence
### 1) guest_house lookup
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Bath, United Kingdom" --category guest_house --limit 3
```
Observed results:
- Henrietta House — 390.3 m
- The Windsor — 437.2 m
- The Old Rectory Bed & Breakfast — 495.7 m
All returned `tourism=guest_house` in the raw tags.
### 2) camp_site lookup
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Yosemite Valley, California" --category camp_site --limit 5
```
Observed result:
- Yellow Pine Administrative Campground — 90.3 m
Returned `tourism=camp_site` in the raw tags.
### 3) bakery lookup via `shop=bakery`
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "Lawrenceville, New Jersey" --category bakery --radius 5000 --limit 10
```
Observed results:
- The Gingered Peach — 713.8 m
- WildFlour Bakery — 741.9 m
Both returned `shop=bakery` in the raw tags.
### 4) bakery lookup via `amenity=bakery`
Command:
```bash
python3 skills/productivity/maps/scripts/maps_client.py nearby --near "20735 Stevens Creek Boulevard, Cupertino, CA" --category bakery --radius 600 --limit 5
```
Observed result:
- Paris Baguette — 28.6 m
Returned `amenity=bakery` in the raw tags (and also includes `shop=bakery`), proving the dual-key union query reaches amenity-tagged bakeries too.
## Conclusion
PASS.
- `guest_house` resolves correctly
- `camp_site` resolves correctly
- `bakery` resolves through both supported keys
- forge/main drift from upstream/main was real and is addressed on this branch

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@@ -57,7 +57,7 @@ CONFIGURABLE_TOOLSETS = [
("moa", "🧠 Mixture of Agents", "mixture_of_agents"),
("tts", "🔊 Text-to-Speech", "text_to_speech"),
("skills", "📚 Skills", "list, view, manage"),
("todo", "📋 Task Planning", "todo"),
("todo", "📋 Task Planning", "todo, ultraplan"),
("memory", "💾 Memory", "persistent memory across sessions"),
("session_search", "🔎 Session Search", "search past conversations"),
("clarify", "❓ Clarifying Questions", "clarify"),

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@@ -1,199 +0,0 @@
---
name: maps
description: >
Location intelligence — geocode a place, reverse-geocode coordinates,
find nearby places (46 POI categories), driving/walking/cycling
distance + time, turn-by-turn directions, timezone lookup, bounding
box + area for a named place, and POI search within a rectangle.
Uses OpenStreetMap + Overpass + OSRM. Free, no API key.
version: 1.2.0
author: Mibayy
license: MIT
metadata:
hermes:
tags: [maps, geocoding, places, routing, distance, directions, nearby, location, openstreetmap, nominatim, overpass, osrm]
category: productivity
requires_toolsets: [terminal]
supersedes: [find-nearby]
---
# Maps Skill
Location intelligence using free, open data sources. 8 commands, 44 POI
categories, zero dependencies (Python stdlib only), no API key required.
Data sources: OpenStreetMap/Nominatim, Overpass API, OSRM, TimeAPI.io.
This skill supersedes the old `find-nearby` skill — all of find-nearby's
functionality is covered by the `nearby` command below, with the same
`--near "<place>"` shortcut and multi-category support.
## When to Use
- User sends a Telegram location pin (latitude/longitude in the message) → `nearby`
- User wants coordinates for a place name → `search`
- User has coordinates and wants the address → `reverse`
- User asks for nearby restaurants, hospitals, pharmacies, hotels, etc. → `nearby`
- User wants driving/walking/cycling distance or travel time → `distance`
- User wants turn-by-turn directions between two places → `directions`
- User wants timezone information for a location → `timezone`
- User wants to search for POIs within a geographic area → `area` + `bbox`
## Prerequisites
Python 3.8+ (stdlib only — no pip installs needed).
Script path: `~/.hermes/skills/maps/scripts/maps_client.py`
## Commands
```bash
MAPS=~/.hermes/skills/maps/scripts/maps_client.py
```
### search — Geocode a place name
```bash
python3 $MAPS search "Eiffel Tower"
python3 $MAPS search "1600 Pennsylvania Ave, Washington DC"
```
Returns: lat, lon, display name, type, bounding box, importance score.
### reverse — Coordinates to address
```bash
python3 $MAPS reverse 48.8584 2.2945
```
Returns: full address breakdown (street, city, state, country, postcode).
### nearby — Find places by category
```bash
# By coordinates (from a Telegram location pin, for example)
python3 $MAPS nearby 48.8584 2.2945 restaurant --limit 10
python3 $MAPS nearby 40.7128 -74.0060 hospital --radius 2000
# By address / city / zip / landmark — --near auto-geocodes
python3 $MAPS nearby --near "Times Square, New York" --category cafe
python3 $MAPS nearby --near "90210" --category pharmacy
# Multiple categories merged into one query
python3 $MAPS nearby --near "downtown austin" --category restaurant --category bar --limit 10
```
46 categories: restaurant, cafe, bar, hospital, pharmacy, hotel, guest_house,
camp_site, supermarket, atm, gas_station, parking, museum, park, school,
university, bank, police, fire_station, library, airport, train_station,
bus_stop, church, mosque, synagogue, dentist, doctor, cinema, theatre, gym,
swimming_pool, post_office, convenience_store, bakery, bookshop, laundry,
car_wash, car_rental, bicycle_rental, taxi, veterinary, zoo, playground,
stadium, nightclub.
Each result includes: `name`, `address`, `lat`/`lon`, `distance_m`,
`maps_url` (clickable Google Maps link), `directions_url` (Google Maps
directions from the search point), and promoted tags when available —
`cuisine`, `hours` (opening_hours), `phone`, `website`.
### distance — Travel distance and time
```bash
python3 $MAPS distance "Paris" --to "Lyon"
python3 $MAPS distance "New York" --to "Boston" --mode driving
python3 $MAPS distance "Big Ben" --to "Tower Bridge" --mode walking
```
Modes: driving (default), walking, cycling. Returns road distance, duration,
and straight-line distance for comparison.
### directions — Turn-by-turn navigation
```bash
python3 $MAPS directions "Eiffel Tower" --to "Louvre Museum" --mode walking
python3 $MAPS directions "JFK Airport" --to "Times Square" --mode driving
```
Returns numbered steps with instruction, distance, duration, road name, and
maneuver type (turn, depart, arrive, etc.).
### timezone — Timezone for coordinates
```bash
python3 $MAPS timezone 48.8584 2.2945
python3 $MAPS timezone 35.6762 139.6503
```
Returns timezone name, UTC offset, and current local time.
### area — Bounding box and area for a place
```bash
python3 $MAPS area "Manhattan, New York"
python3 $MAPS area "London"
```
Returns bounding box coordinates, width/height in km, and approximate area.
Useful as input for the bbox command.
### bbox — Search within a bounding box
```bash
python3 $MAPS bbox 40.75 -74.00 40.77 -73.98 restaurant --limit 20
```
Finds POIs within a geographic rectangle. Use `area` first to get the
bounding box coordinates for a named place.
## Working With Telegram Location Pins
When a user sends a location pin, the message contains `latitude:` and
`longitude:` fields. Extract those and pass them straight to `nearby`:
```bash
# User sent a pin at 36.17, -115.14 and asked "find cafes nearby"
python3 $MAPS nearby 36.17 -115.14 cafe --radius 1500
```
Present results as a numbered list with names, distances, and the
`maps_url` field so the user gets a tap-to-open link in chat. For "open
now?" questions, check the `hours` field; if missing or unclear, verify
with `web_search` since OSM hours are community-maintained and not always
current.
## Workflow Examples
**"Find Italian restaurants near the Colosseum":**
1. `nearby --near "Colosseum Rome" --category restaurant --radius 500`
— one command, auto-geocoded
**"What's near this location pin they sent?":**
1. Extract lat/lon from the Telegram message
2. `nearby LAT LON cafe --radius 1500`
**"How do I walk from hotel to conference center?":**
1. `directions "Hotel Name" --to "Conference Center" --mode walking`
**"What restaurants are in downtown Seattle?":**
1. `area "Downtown Seattle"` → get bounding box
2. `bbox S W N E restaurant --limit 30`
## Pitfalls
- Nominatim ToS: max 1 req/s (handled automatically by the script)
- `nearby` requires lat/lon OR `--near "<address>"` — one of the two is needed
- OSRM routing coverage is best for Europe and North America
- Overpass API can be slow during peak hours; the script automatically
falls back between mirrors (overpass-api.de → overpass.kumi.systems)
- `distance` and `directions` use `--to` flag for the destination (not positional)
- If a zip code alone gives ambiguous results globally, include country/state
## Verification
```bash
python3 ~/.hermes/skills/maps/scripts/maps_client.py search "Statue of Liberty"
# Should return lat ~40.689, lon ~-74.044
python3 ~/.hermes/skills/maps/scripts/maps_client.py nearby --near "Times Square" --category restaurant --limit 3
# Should return a list of restaurants within ~500m of Times Square
```

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@@ -1,135 +0,0 @@
"""Regression tests for the bundled maps skill."""
from __future__ import annotations
import importlib.util
from pathlib import Path
from types import SimpleNamespace
SCRIPT_PATH = (
Path(__file__).resolve().parents[2]
/ "skills/productivity/maps/scripts/maps_client.py"
)
SKILL_PATH = (
Path(__file__).resolve().parents[2]
/ "skills/productivity/maps/SKILL.md"
)
def load_module():
assert SCRIPT_PATH.exists(), f"missing maps client script: {SCRIPT_PATH}"
spec = importlib.util.spec_from_file_location("maps_client_test", SCRIPT_PATH)
module = importlib.util.module_from_spec(spec)
assert spec.loader is not None
spec.loader.exec_module(module)
return module
def test_maps_skill_files_exist():
assert SCRIPT_PATH.exists()
assert SKILL_PATH.exists()
def test_category_tags_cover_guest_house_camp_site_and_dual_key_bakery():
module = load_module()
assert module.CATEGORY_TAGS["guest_house"] == ("tourism", "guest_house")
assert module.CATEGORY_TAGS["camp_site"] == ("tourism", "camp_site")
assert module.CATEGORY_TAGS["bakery"] == [
("shop", "bakery"),
("amenity", "bakery"),
]
assert module._tags_for("bakery") == [
("shop", "bakery"),
("amenity", "bakery"),
]
def test_build_overpass_queries_include_all_supported_tags():
module = load_module()
bakery_query = module.build_overpass_nearby(
None,
None,
40.0,
-74.0,
500,
10,
tag_pairs=module._tags_for("bakery"),
)
assert 'node["shop"="bakery"]' in bakery_query
assert 'way["shop"="bakery"]' in bakery_query
assert 'node["amenity"="bakery"]' in bakery_query
assert 'way["amenity"="bakery"]' in bakery_query
guest_house_query = module.build_overpass_nearby(
None,
None,
40.0,
-74.0,
500,
10,
tag_pairs=module._tags_for("guest_house"),
)
assert 'node["tourism"="guest_house"]' in guest_house_query
assert 'way["tourism"="guest_house"]' in guest_house_query
camp_site_bbox = module.build_overpass_bbox(
None,
None,
39.0,
-75.0,
41.0,
-73.0,
10,
tag_pairs=module._tags_for("camp_site"),
)
assert 'node["tourism"="camp_site"]' in camp_site_bbox
assert 'way["tourism"="camp_site"]' in camp_site_bbox
def test_cmd_nearby_dedupes_dual_tag_bakery_results(monkeypatch, capsys):
module = load_module()
duplicate_bakery = {
"elements": [
{
"type": "node",
"id": 101,
"lat": 40.0,
"lon": -74.0,
"tags": {"name": "Wild Flour", "shop": "bakery"},
},
{
"type": "node",
"id": 101,
"lat": 40.0,
"lon": -74.0,
"tags": {"name": "Wild Flour", "amenity": "bakery"},
},
]
}
monkeypatch.setattr(module, "overpass_query", lambda query: duplicate_bakery)
args = SimpleNamespace(
lat="40.0",
lon="-74.0",
near=None,
category="bakery",
category_list=[],
radius=500,
limit=10,
)
module.cmd_nearby(args)
out = capsys.readouterr().out
assert '"count": 1' in out
assert '"Wild Flour"' in out
def test_skill_doc_lists_new_categories_and_supersession():
text = SKILL_PATH.read_text(encoding="utf-8")
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",
}

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@@ -0,0 +1,81 @@
import json
from pathlib import Path
from toolsets import resolve_toolset
from tools.registry import registry
def test_create_action_saves_markdown_and_json(tmp_path):
from tools.ultraplan import ultraplan_tool
result = json.loads(
ultraplan_tool(
action="create",
mission="Daily autonomous planning",
streams=[
{
"id": "A",
"name": "Backlog burn",
"phases": [
{"id": "A1", "name": "Triage", "artifact": "issue list"},
{"id": "A2", "name": "Ship", "dependencies": ["A1"], "artifact": "PR"},
],
}
],
base_dir=str(tmp_path),
)
)
assert result["success"] is True
assert Path(result["file_path"]).exists()
assert Path(result["json_path"]).exists()
assert "Work Streams" in Path(result["file_path"]).read_text(encoding="utf-8")
def test_load_action_returns_saved_plan(tmp_path):
from tools.ultraplan import ultraplan_tool
created = json.loads(
ultraplan_tool(
action="create",
date="20260422",
mission="Mission from saved plan",
base_dir=str(tmp_path),
)
)
loaded = json.loads(
ultraplan_tool(
action="load",
date="20260422",
base_dir=str(tmp_path),
)
)
assert created["success"] is True
assert loaded["success"] is True
assert loaded["plan"]["mission"] == "Mission from saved plan"
assert loaded["file_path"].endswith("ultraplan_20260422.md")
def test_cron_spec_returns_daily_schedule_and_prompt():
from tools.ultraplan import ultraplan_tool
result = json.loads(ultraplan_tool(action="cron_spec"))
assert result["success"] is True
assert result["schedule"] == "0 6 * * *"
assert "Ultraplan" in result["prompt"]
assert "ultraplan_YYYYMMDD.md" in result["prompt"]
def test_registry_registers_ultraplan_tool():
import tools.ultraplan # noqa: F401
entry = registry.get_entry("ultraplan")
assert entry is not None
assert entry.toolset == "todo"
def test_default_toolsets_include_ultraplan():
assert "ultraplan" in resolve_toolset("todo")
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]:
return None
DEFAULT_ULTRAPLAN_SCHEDULE = "0 6 * * *"
def generate_daily_cron_prompt() -> str:
"""Generate the prompt for the daily ultraplan cron job."""
return """Generate today's Ultraplan.
@@ -298,9 +301,9 @@ Steps:
1. Check open Gitea issues assigned to you
2. Check open PRs needing review
3. Check fleet health status
4. Decompose work into parallel streams
5. Generate ultraplan_YYYYMMDD.md
6. File Gitea issue with the plan
4. Decompose work into parallel streams with concrete phases and artifacts
5. Use the ultraplan tool to save ~/.timmy/cron/ultraplan_YYYYMMDD.md and the matching JSON sidecar
6. Optionally file a Gitea issue with the plan summary
Output format:
- Mission statement
@@ -308,3 +311,176 @@ Output format:
- Dependency map
- Success metrics
"""
def generate_daily_cron_job_spec(schedule: str = DEFAULT_ULTRAPLAN_SCHEDULE) -> Dict[str, str]:
"""Return a reusable cron job spec for daily Ultraplan generation."""
return {
"name": "Daily Ultraplan",
"schedule": schedule,
"prompt": generate_daily_cron_prompt(),
"path_pattern": "~/.timmy/cron/ultraplan_YYYYMMDD.md",
}
def _resolve_base_dir(base_dir: Optional[str | Path]) -> Path:
"""Normalize the requested Ultraplan base directory."""
if base_dir is None:
return Path.home() / ".timmy" / "cron"
return Path(base_dir).expanduser()
def ultraplan_tool(
action: str,
date: Optional[str] = None,
mission: str = "",
streams: Optional[List[Dict[str, Any]]] = None,
metrics: Optional[Dict[str, Any]] = None,
notes: str = "",
base_dir: Optional[str] = None,
) -> str:
"""Create/load Ultraplan artifacts and expose a daily cron spec."""
from tools.registry import tool_error, tool_result
action = (action or "").strip().lower()
resolved_base_dir = _resolve_base_dir(base_dir)
try:
if action == "create":
plan = create_ultraplan(date=date, mission=mission, streams=streams or [])
if metrics:
plan.metrics = metrics
if notes:
plan.notes = notes
md_path = save_ultraplan(plan, base_dir=resolved_base_dir)
json_path = resolved_base_dir / f"ultraplan_{plan.date}.json"
return tool_result(
success=True,
action="create",
date=plan.date,
file_path=str(md_path),
json_path=str(json_path),
plan=plan.to_dict(),
)
if action == "load":
plan_date = date or datetime.now().strftime("%Y%m%d")
plan = load_ultraplan(plan_date, base_dir=resolved_base_dir)
if plan is None:
return tool_error(
f"No Ultraplan found for {plan_date}",
success=False,
action="load",
date=plan_date,
)
return tool_result(
success=True,
action="load",
date=plan.date,
file_path=str(resolved_base_dir / f"ultraplan_{plan.date}.md"),
json_path=str(resolved_base_dir / f"ultraplan_{plan.date}.json"),
plan=plan.to_dict(),
markdown=plan.to_markdown(),
)
if action == "cron_spec":
spec = generate_daily_cron_job_spec()
return tool_result(success=True, action="cron_spec", **spec)
return tool_error(
f"Unknown Ultraplan action: {action}",
success=False,
action=action,
)
except Exception as e:
return tool_error(f"Ultraplan {action or 'tool'} failed: {e}", success=False, action=action)
ULTRAPLAN_SCHEMA = {
"name": "ultraplan",
"description": (
"Create or load daily Ultraplan planning artifacts under ~/.timmy/cron/ and "
"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."
),
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": ["create", "load", "cron_spec"],
"description": "Operation to perform",
},
"date": {
"type": "string",
"description": "Plan date as YYYYMMDD. Defaults to today for create/load.",
},
"mission": {
"type": "string",
"description": "High-level mission statement for today's plan.",
},
"streams": {
"type": "array",
"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="🗺️",
)

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@@ -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": []
},