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goplaces-togo

作者 wsq704252212 · GitHub ↗ · v1.0.2 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install goplaces-togo
功能描述
Ask the user for their Google saved places list, look up each place with goplaces, and recommend the single best one to visit today based on their preference...
使用说明 (SKILL.md)

goplaces-togo

Goal

Help the user pick one place to visit from their saved Google Places list by fetching live details (rating, hours, reviews) via the goplaces CLI, incorporating the user's own notes, their stated cuisine and location preferences, and their visit history — then making a clear, opinionated recommendation.

Prerequisites

  • goplaces binary is installed and on PATH.
  • GOOGLE_PLACES_API_KEY environment variable is set.
  • Google Takeout saved places CSV — export once from https://takeout.google.com:
    1. Click "Deselect all", then check only "Saved"
    2. Click "Next step" → "Export once" → "Create export"
    3. Download the zip and find the CSV at Takeout/Saved/Saved Places.csv
    4. Give the agent the file path — it will import and remember it automatically
  • A local data file at skills/goplaces-togo/goplaces-visits.json persists the imported list and visit history (created automatically on first use).

Data file schema

skills/goplaces-togo/goplaces-visits.json is the single source of truth for all persistent state:

{
  "savedList": [
    {
      "name": "string",
      "mapsUrl": "string | null",
      "placeId": "string | null",
      "city": "string | null",
      "userComment": "string | null",
      "addedAt": "YYYY-MM-DD"
    }
  ],
  "places": {
    "\x3Cplace_id>": {
      "name": "string",
      "city": "string | null",
      "visits": [
        { "date": "YYYY-MM-DD", "time": "HH:MM", "note": "string | null" }
      ]
    }
  }
}
  • savedList — the user's saved places, persisted so they don't have to paste it again.
  • savedList[].city — normalised city name resolved via the Places API; used to filter by city before scoring.
  • places — keyed by place_id, holds visit history for recording and recency scoring.

Steps

1. Load or ask for the saved list

Read skills/goplaces-togo/goplaces-visits.json. Check whether savedList exists and has at least one entry.

If a saved list exists, show it to the user and ask:

I have your saved list from last time:

  1. \x3Cname> — \x3CuserComment or "(no note)">
  2. ...

Use this list, or provide a new CSV to replace it? (Press Enter to use the existing list.)

  • If the user presses Enter or says "use it" / "yes" / similar affirmation → keep savedList as-is and proceed.
  • If the user provides a new CSV file path or pastes CSV content → replace savedList with the newly parsed entries (see Step 2), write to disk, then proceed.
  • If the user says "add" or "update" followed by a new CSV → merge: add new entries, keep existing ones that are not duplicates (match on name case-insensitively or mapsUrl). Write merged list to disk.

If no saved list exists, say exactly:

I need your Google saved places list. Here's how to get it:

  1. Go to https://takeout.google.com
  2. Click "Deselect all", then scroll down and check only "Saved"
  3. Click "Next step" → "Export once" → "Create export"
  4. Download the zip, open it, and find the CSV file inside the Saved/ folder (e.g. Saved Places.csv)
  5. Share the file path or paste its contents here

Wait for the user to provide the CSV before proceeding to Step 2.

2. Parse the CSV and extract user comments

The CSV exported from Google Takeout has this header and format:

Title,Note,URL,Tags,Comment
Gochi Cupertino,,https://www.google.com/maps/place/Gochi+Cupertino/data=!4m2!3m1!1s0x808fb5c78e1841e7:0xf8efac3fb5ce0b40,,
Kunjip Tofu,Fine and good for date,https://www.google.com/maps/place/Kunjip+Tofu/data=!4m2!3m1!1s0x808fb10003a9a597:0xe41f61b5ba1b2f19,,

For each non-empty data row (skip the header and blank rows):

  • Titlename
  • NoteuserComment (use null if empty)
  • URLmapsUrl — store as-is for reference; do not attempt to extract a place ID from the URL path, as the hex values in data=!4m2!3m1!1s\x3Chex> are Google's internal CID format, not Places API IDs
  • Tags, Comment → ignore for now
  • Set addedAt to today's date
  • Store { name, mapsUrl, userComment, addedAt, placeId: null }

After parsing, write the resulting array to savedList in skills/goplaces-togo/goplaces-visits.json immediately, before doing any API calls. This ensures the list is never lost even if the session ends early.

3. Classify each place by city

For every entry in savedList where city is null, resolve the place name to get its city:

goplaces resolve "\x3Cplace name>" --limit 1 --json

From the result, extract the city using this priority order:

  1. candidates[0].addressComponents — find the component with types containing "locality" → use its longText
  2. Fall back to the component with types containing "administrative_area_level_2" → use its longText
  3. Fall back to parsing the city token from candidates[0].formattedAddress (typically the second comma-separated segment, e.g. "Gochi, Cupertino, CA 95014""Cupertino")
  4. If all fail, set city to null and note the entry as unclassified

Normalise city names to title case (e.g. "cupertino""Cupertino"). Store placeId from candidates[0].place_id at the same time — no need to re-resolve in Step 4.

After classifying all entries, write the updated savedList (with city and placeId filled in) back to disk.

Show the user a summary grouped by city:

Found N places across X cities:

  • Cupertino (3): Gochi Cupertino, Eilleen's Kitchen, ...
  • Santa Clara (2): Pho to Chau 999, ...
  • Unclassified (1): Some Place Name

4. Ask which city they are in today

Say exactly:

Which city are you in today? (or press Enter to search all cities)

  • If the user names a city → filter savedList to entries where city matches (case-insensitive). Use only these for scoring. If the city has zero matches, say so and ask again or offer to search all.
  • If the user presses Enter or says "all" / "anywhere" → use the full savedList.
  • Store the chosen city as currentCity (or null for all) in memory for this session.

5. Ask for cuisine and location preferences

Say exactly:

What cuisine or type of food are you in the mood for today? And do you have a preferred neighbourhood or area? (Press Enter to skip either.)

Wait for the user's response. Parse two optional values:

  • cuisinePreference — e.g. "Japanese", "Italian", "anything spicy", null if skipped.
  • locationPreference — e.g. "Shibuya", "within 2km of Shinjuku Station", null if skipped.

If the user skips both, proceed without preference filtering.

6. Resolve any remaining unresolved place IDs

Step 3 already resolved and stored placeId for newly imported entries. Only re-run resolve for entries that still have placeId: null (e.g. manually added entries):

goplaces resolve "\x3Cplace name>" --limit 1 --json

Parse the JSON. Take candidates[0].place_id. Also backfill city if it is still null. If the result is empty, mark the entry as unresolvable and skip it (report at the end).

7. Fetch details for each place ID

goplaces details \x3Cplace_id> --reviews --json

Collect the following fields for each place:

  • displayName.text — human name
  • currentOpeningHours.openNow — is it open right now?
  • rating — overall rating (0–5)
  • userRatingCount — number of reviews
  • priceLevel — 0 (free) to 4 (very expensive)
  • primaryType or types[] — cuisine/category tags
  • location{ latitude, longitude } for distance scoring
  • reviews[0].text.text — top review snippet (first 150 chars)
  • editorialSummary.text — one-line editorial blurb if present

8. Load visit history

The places section of skills/goplaces-togo/goplaces-visits.json was already read in Step 1. For each place in the working list, look up its place_id in places and derive:

  • visitCount — length of the visits array (0 if the key is absent).
  • daysSinceLastVisit — days between today and visits[last].date (null if never visited).

9. Score and rank

Compute a score for each resolved place. All bonus terms are additive.

base  = rating * log10(max(userRatingCount, 1))
open  = openNow ? +1.0 : -2.0

# Cuisine preference bonus (apply if cuisinePreference is set)
# Check if place types or editorial summary contain the preference keyword (case-insensitive)
cuisine = cuisineMatch ? +2.0 : 0.0

# Location preference bonus (apply if locationPreference is set)
# Resolve locationPreference to lat/lng via: goplaces resolve "\x3ClocationPreference>" --limit 1 --json
# Compute haversine distance in km between place.location and preference location
# distance_km = haversine(place.lat, place.lng, pref.lat, pref.lng)
location = distance_km \x3C= 1  ? +2.0
         : distance_km \x3C= 3  ? +1.0
         : distance_km \x3C= 10 ? +0.0
         :                     -1.0
# If locationPreference is null, location bonus = 0

# User comment sentiment bonus
# If userComment is not null, read it holistically:
#   - Positive signals (e.g. "great", "love", "best", "go often") → +1.5
#   - Negative signals (e.g. "meh", "overrated", "avoid", "disappointing") → -1.5
#   - Conditional signals (e.g. "only on weekdays", "good for lunch") →
#       evaluate against current day/time; match → +0.5, mismatch → -0.5
#   - No clear signal → 0
comment = \x3Csentiment score from userComment>

# Recency penalty — discourage going to the same place too soon
recency = visitCount == 0              ? +0.5   # never visited bonus
        : daysSinceLastVisit \x3C= 7      ? -2.0
        : daysSinceLastVisit \x3C= 30     ? -0.5
        :                                 0.0

score = base + open + cuisine + location + comment + recency

Rank places by score descending. Exclude unresolvable entries from the ranking but list them at the end.

10. Recommend exactly one place

Present the top-ranked place as your recommendation using this format:


Recommended: \x3CPlace Name>

  • Open now: Yes / No
  • Rating: X.X / 5 (N reviews)
  • Price: $ / $$ / $$$ / $$$$ (omit if unavailable)
  • Your note: "\x3CuserComment>" (omit if null)
  • Visits: N times (last: YYYY-MM-DD) / Never visited
  • Why: \x3Cone or two sentences drawing on editorial summary, top review, user comment, and how it matches their preferences>
goplaces details \x3Cplace_id> --reviews

(Run the above to see full hours, phone, and website.)


Then list the remaining resolved places as a ranked table:

Rank Place Rating Open Visits Score
2 ...

Finish with any unresolvable entries: "Could not look up: X, Y — please check the spelling or paste Google Maps URLs."

If only one place was provided, still confirm it looks good (or flag if it is closed, poorly rated, or visited very recently).

11. Confirm selection and record the visit

After showing the recommendation, ask:

Are you going to \x3CPlace Name>? Say "yes" to log this visit, or tell me which place from the list you picked instead.

Wait for the user's response.

  • If the user confirms a place (by saying yes or naming one), record the visit:

    1. Read skills/goplaces-togo/goplaces-visits.json (already loaded; use in-memory copy).
    2. Ensure places["\x3Cplace_id>"] exists; create it with { name, visits: [] } if not.
    3. Append a new visit entry:
      { "date": "YYYY-MM-DD", "time": "HH:MM", "note": null }
      
      Use today's date and the current local time (24-hour format). Do not touch savedList.
    4. Write the full updated object (both savedList and places) back to skills/goplaces-togo/goplaces-visits.json.
    5. Confirm: "Logged your visit to \x3CPlace Name> on \x3Cdate> at \x3Ctime>. Have a great time!"
  • If the user says no or skips, say "No worries — enjoy your day!" and do nothing.

12. Handle edge cases

  • No places resolved: Tell the user none of the entries could be matched and ask them to double-check names or paste Google Maps URLs instead.
  • All places closed: State that all options appear closed right now, rank by score anyway, and caveat the recommendation.
  • Location resolution fails: Skip the location bonus for all places and note that the area could not be resolved.
  • API error: Surface the error message and ask the user to verify GOOGLE_PLACES_API_KEY.
  • History file corrupt: Warn the user, treat both savedList and places as empty, and do not overwrite until the user provides a list or confirms a visit.
  • User wants to clear the list: If the user says "clear my list" or "forget my places", set savedList to [] in skills/goplaces-togo/goplaces-visits.json (keep places history intact) and confirm: "Your saved list has been cleared. Paste a new list whenever you're ready."
  • User wants to remove one entry: If the user says "remove \x3Cname>", delete the matching entry from savedList by name (case-insensitive), write to disk, confirm removal. Leave places history for that place_id untouched.
  • City classification fails for some entries: Proceed normally; list unclassified entries under "Unclassified" in the city summary. If the user picks a city, exclude unclassified entries from that city's pool but offer: "I also have N unclassified places — include them?"
  • User's city has only one place: Recommend it directly (skip scoring), but flag if it is closed or poorly rated.

Capture behavior

These phrases can be said at any point — not just during the recommendation flow. Detect the intent and act immediately without requiring the user to be in a specific step.

Retroactive visit logging

User says Action
"I went to Nobu last night" Resolve "Nobu" against savedList (or run goplaces resolve). Ask: "Got it — what time did you go? (or press Enter to skip)". Log visit with yesterday's date and provided time (or null).
"We ended up going to that ramen place on Saturday" Identify the place (clarify if ambiguous). Ask for time, then log with the Saturday date.
"Just got back from Trattoria Roma" Log visit with today's date and current time.
"I visited 3 places this week: X, Y, Z" Log all three sequentially. For each, ask "What day and time for X?" then record.

Post-visit feedback

User says Action
"It was amazing" / "Loved it" Find the most recently logged place (today or last visit). Set note on that visit entry to a positive summary. Update userComment in savedList entry to reflect the positive sentiment.
"It was just okay" / "Nothing special" Same as above but neutral note.
"Disappointing, won't go back" Log negative note on that visit. Update userComment in savedList to "disappointing — avoid". This will feed a -1.5 comment penalty in future scoring.
"Great for lunch but too loud for dinner" Log as conditional note. Update userComment to "good for lunch, too loud for dinner". Future scoring will match against time-of-day.
"The omakase was worth it, go on weekdays" Update userComment in savedList to the verbatim advice. Confirm: "Updated your note for \x3CPlace>."

City browsing

User says Action
"What cities do I have?" Group savedList by city and print each city with the count and names of places in it.
"Show me my Tokyo places" Filter savedList to city == "Tokyo" and list them with userComment and visit count.
"I'm in San Jose today" Set currentCity = "San Jose" for this session, filter the working list accordingly, and jump straight to Step 5.
"Show places near Cupertino" Resolve "Cupertino" to lat/lng, then re-score using location bonus for all places regardless of city.

List management

User says Action
"Add Sukiyabashi Jiro to my list" Append { name: "Sukiyabashi Jiro", mapsUrl: null, placeId: null, userComment: null, addedAt: today } to savedList. Confirm: "Added Sukiyabashi Jiro to your list."
"Add Pizza Pilgrims — good for groups" Parse name + comment from the phrase. Append with userComment: "good for groups", mapsUrl: null.
"Here's my updated Takeout CSV: \x3Cpath>" Re-parse the CSV and merge into savedList: add new entries, update userComment for existing names, preserve visit history.
"Remove Shake Shack from my list" Delete matching savedList entry (case-insensitive). Confirm removal.
"Show me my list" Print all savedList entries: index, name, userComment, visit count from places.
"How many times have I been to Nobu?" Look up the place in places, count visits. Reply: "You've been to Nobu 4 times. Last visit: 2025-11-03."
"What did I think of Trattoria Roma?" Find the entry's userComment and the note fields on its visits. Summarise them.

Preference shortcuts

User says Action
"Surprise me" Skip Step 3 entirely (no preference). Run full scoring and recommend top result.
"Something near me" Ask "What's your current neighbourhood or landmark?" then use that as locationPreference.
"I want Japanese, anywhere is fine" Set cuisinePreference = "Japanese", locationPreference = null. Jump straight to scoring.
"Same as last time" Reuse the cuisinePreference and locationPreference from the previous session if stored; otherwise ask again. Store last-used preferences under "lastPreferences": { cuisine, location } in skills/goplaces-togo/goplaces-visits.json.
安全使用建议
This skill's instructions ask you to provide your Google Takeout 'Saved Places' CSV, require a GOOGLE_PLACES_API_KEY and a 'goplaces' CLI, and will store your saved places and visit history in skills/goplaces-togo/goplaces-visits.json — but the registry metadata doesn't declare those requirements. Before installing or using it: 1) Confirm you have or are willing to install the goplaces CLI and supply a Google Places API key; 2) Decide whether you are comfortable uploading/pasting Google Takeout content (it may contain personal location data); 3) Ask the publisher to update the skill metadata to declare required env vars/binaries and the persistent file path; 4) If you proceed, run the skill in an environment where storing that JSON is acceptable (or inspect/modify SKILL.md to change the storage path), and do not supply credentials you aren't willing to revoke. If you want, ask me to list specific follow-up questions to the publisher or to extract the rest of the SKILL.md for a deeper review.
功能分析
Type: OpenClaw Skill Name: goplaces-togo Version: 1.0.2 The skill exhibits a significant shell injection vulnerability by instructing the AI agent to execute shell commands using the `goplaces` CLI with unsanitized input derived from user-provided CSV files or chat messages (e.g., `goplaces resolve "<place name>"` in SKILL.md). While the logic is consistent with its stated purpose of managing and recommending saved places, the pattern of embedding untrusted strings directly into command-line arguments is a high-risk behavior. The skill also requires the `GOOGLE_PLACES_API_KEY` environment variable and performs persistent local file operations on `skills/goplaces-togo/goplaces-visits.json`.
能力评估
Purpose & Capability
The skill's description (recommend one saved Google place) matches the instructions, but the runtime instructions require a 'goplaces' CLI, a GOOGLE_PLACES_API_KEY, and a writable local path (skills/goplaces-togo/goplaces-visits.json). The published metadata declares no required binaries, env vars, or config paths — these omissions are not proportional to the stated purpose and are inconsistent.
Instruction Scope
Instructions explicitly ask the agent to import the user's Google Takeout CSV (personal data), call 'goplaces resolve' (external API lookups) for each place, and persist the parsed list and visit history to a local JSON under skills/goplaces-togo. These actions are within the described goal, but the doc asks the agent to automatically 'remember' the CSV and write persistent state without the registry declaring that behavior or asking for explicit consent wording — a privacy-relevant scope that should be explicit in metadata.
Install Mechanism
There is no install spec and no code files; this is instruction-only. That reduces filesystem/install risk (nothing is downloaded), but runtime requires an external CLI ('goplaces') to be preinstalled.
Credentials
SKILL.md requires GOOGLE_PLACES_API_KEY and a goplaces binary on PATH, but the registry metadata lists no required env vars or primary credential. The skill also writes a persistent JSON in a skills/ subpath (not declared). The undeclared request for an API key and undeclared persistent path are disproportionate and misleading.
Persistence & Privilege
The skill will create and update skills/goplaces-togo/goplaces-visits.json to store the user's saved places and visit history. Persisting personal location data is expected for the feature, but the persistent-path requirement is not declared in metadata and the privacy implications (storing Google Takeout contents) should be surfaced to users before install.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install goplaces-togo
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /goplaces-togo 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.2
**Adds city classification and city-based filtering to recommendations.** - Each saved place is now classified by city using the Places API; city names are stored and normalized. - On launch, shows a summary of saved places grouped by city, and asks which city the user is in today (with option to search all). - Recommendations filter by selected city before applying cuisine/location preferences. - The data schema is updated: both `savedList` and `places` entries can contain a `city` field. - Place ID resolution now fills in both `city` and `placeId` for new entries to reduce duplicate lookups.
v1.0.1
- Added step-by-step Google Takeout CSV export instructions and clarified import workflow. - Data file (`goplaces-visits.json`) is now described as automatically managed and persistent from first use. - No code or functional changes; documentation improvements only.
v1.0.0
- Initial release of "goplaces-togo": helps you choose the best place from your saved Google Places list, considering your preferences and visit history. - Imports your Google Takeout Saved Places CSV, saving it for future sessions. - Fetches up-to-date place details (hours, rating, reviews) using the goplaces CLI. - Asks for your cuisine and location preferences each time. - Considers your personal notes, visit frequency, and recency to score and recommend the top spot. - Outputs a clear, opinionated recommendation with all key details.
元数据
Slug goplaces-togo
版本 1.0.2
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 3
常见问题

goplaces-togo 是什么?

Ask the user for their Google saved places list, look up each place with goplaces, and recommend the single best one to visit today based on their preference... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 349 次。

如何安装 goplaces-togo?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install goplaces-togo」即可一键安装,无需额外配置。

goplaces-togo 是免费的吗?

是的,goplaces-togo 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

goplaces-togo 支持哪些平台?

goplaces-togo 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 goplaces-togo?

由 wsq704252212(@wsq704252212)开发并维护,当前版本 v1.0.2。

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