--- name: pp-japan-theme-parks description: "Compare park dates and ride waits for Tokyo Disney Resort, Universal Studios Japan and Fuji-Q from source-backed data. Trigger phrases: `is Tokyo DisneySea sold out on`, `Tokyo Disney ticket price for`, `USJ opening hours this month`, `DisneySea wait times now`, `USJ wait times now`, `use japan-theme-parks`, `run japan-theme-parks`." author: "zjsng" license: "Apache-2.0" argument-hint: " [args] | install cli|mcp" allowed-tools: "Read Bash" metadata: openclaw: requires: bins: - japan-theme-parks-pp-cli install: - kind: go bins: [japan-theme-parks-pp-cli] module: github.com/mvanhorn/printing-press-library/library/travel/japan-theme-parks/cmd/japan-theme-parks-pp-cli --- # Japan Theme Parks — Printing Press CLI ## Prerequisites: Install the CLI This skill drives the `japan-theme-parks-pp-cli` binary. **You must verify the CLI is installed before invoking any command from this skill.** If it is missing, install it first: 1. Install via the Printing Press installer. It defaults binaries to `$HOME/.local/bin` on macOS/Linux and `%LOCALAPPDATA%\Programs\PrintingPress\bin` on Windows: ```bash npx -y @mvanhorn/printing-press-library install japan-theme-parks --cli-only ``` 2. Verify: `japan-theme-parks-pp-cli --version` 3. Ensure the reported install directory is on `$PATH` for the agent/runtime that will invoke this skill. If the `npx` install fails (no Node, offline, etc.), fall back to a direct Go install (requires Go 1.26.9 or newer). This installs into `$GOPATH/bin` (default `$HOME/go/bin`), so add that directory to `$PATH` instead: ```bash go install github.com/mvanhorn/printing-press-library/library/travel/japan-theme-parks/cmd/japan-theme-parks-pp-cli@latest ``` If `--version` reports "command not found" after install, the runtime cannot see the binary directory on `$PATH`. Do not proceed with skill commands until verification succeeds. `dates` shows Tokyo Disney Resort ticket sale status and price per ticket type with official TDR hours and third-party (ThemeParks.wiki) USJ and Fuji-Q hours for each date. `waits`, `snapshot` and `typical` turn Queue-Times live waits into a local history with honest sample sizes. Read-only: it never buys tickets. ## When to Use This CLI Use this CLI to choose a Tokyo Disneyland or Tokyo DisneySea date from official per-ticket sale status, price and hours; to see Universal Studios Japan and Fuji-Q hours for about the next month (third-party ThemeParks.wiki data); and to compare live Queue-Times waits with waits you recorded yourself. ## Anti-triggers Do not use this CLI for: - Buying, holding or adding tickets to a cart - USJ dated Studio Pass price or Express Pass availability (not public outside the queued web store) - Crowd forecasts for future dates ## Unique Capabilities ### Pick the date - **`dates`** — See, for each date, whether Tokyo Disneyland and DisneySea tickets are on sale, few left, sold out or not yet on sale, what each ticket costs, and the hours: official for TDL/TDS (published months only), third-party ThemeParks.wiki for USJ and Fuji-Q (about one month ahead). _Use it before recommending a park date; it gives sale status, price and hours with source fetch times instead of guesses. Beyond the sources' horizons it returns null with a reason._ ```bash japan-theme-parks-pp-cli dates --from 2026-11-13 --to 2026-11-15 --agent ``` ### Pick the rides - **`typical`** — See median and p75 waits per ride by weekday and hour from your own recorded snapshots, with sample counts and date span. _Use it to compare weekdays or hours for specific rides without inventing a crowd forecast. It is empty until snapshot has run on a schedule; thin cells show insufficient._ ```bash japan-theme-parks-pp-cli typical --park 275 --weekday sat --hour 10 ``` - **`snapshot`** — Record the current waits for the Japan parks into a local history that later commands read. _Run it from your own scheduler (see the cron example in the README) so typical and waits have history._ ```bash japan-theme-parks-pp-cli snapshot --park 274,275,284 ``` - **`waits`** — On the park day, see live waits next to the usual wait for this weekday and hour from your own snapshots, with sample counts. _Use it on the park day to see which rides are below their usual wait; the usual-wait columns appear only after snapshot has recorded history for this weekday and hour._ ```bash japan-theme-parks-pp-cli waits 275 --open-only --agent ``` ## Command Reference **parks** - `japan-theme-parks-pp-cli parks` — The five Japan parks with JA/EN names, Queue-Times id, timezone, official site, crowd-calendar link and which sources cover hours and tickets. **source** — Raw Queue-Times JSON (Powered by Queue-Times.com, https://queue-times.com/). Prefer parks, waits, dates, snapshot and typical for normalized output. - `japan-theme-parks-pp-cli source parks` — List every Queue-Times park group and park (raw; prefer the parks command for Japan parks). - `japan-theme-parks-pp-cli source queue-times` — Raw live queue times for one Queue-Times park id (prefer the waits command). **dates** - `japan-theme-parks-pp-cli dates` — See, for each date, whether Tokyo Disneyland and DisneySea tickets are on sale, few left, sold out or not yet on sale, what each ticket costs, and the opening hours for TDL, TDS, USJ and Fuji-Q. **snapshot** - `japan-theme-parks-pp-cli snapshot` — Record the current waits for the Japan parks into a local history that later commands read. **typical** - `japan-theme-parks-pp-cli typical` — See median and p75 waits per ride by weekday and hour from your own recorded snapshots, with sample counts and date span. **waits** - `japan-theme-parks-pp-cli waits` — On the park day, see live waits next to the usual wait for this weekday and hour from your own snapshots, with sample counts. ### Finding the right command When you know what you want to do but not which command does it, ask the CLI directly: ```bash japan-theme-parks-pp-cli which "" ``` `which` resolves a natural-language capability query to the best matching command from this CLI's curated feature index. Exit code `0` means at least one match; exit code `2` means no confident match — fall back to `--help` or use a narrower query. `--json` (and other machine formats) keep that exit-2 contract and write `{"matches":[]}` on stdout so agents can inspect the envelope without treating a miss as success. ## Recipes ### Which DisneySea dates are still on sale ```bash japan-theme-parks-pp-cli dates --park tds --from 2026-11-01 --to 2026-11-30 --status on-sale,few-left --agent --select results.date,results.tickets ``` Keep only DisneySea dates with a ticket on sale or few left; months TDR has not published yet return no rows. ### Record waits from cron ```bash japan-theme-parks-pp-cli snapshot --park 274,275,284,337,285 ``` Append one snapshot per park to the local history. ### Usual Saturday morning waits ```bash japan-theme-parks-pp-cli typical --park 275 --weekday sat --hour 10 ``` Median and p75 per ride with sample count and date span. Needs earlier snapshot runs; cells under --min-samples (default 6) show insufficient. ## Source credits and honesty rules - When you show waits, say "Powered by Queue-Times.com" and link https://queue-times.com/. - When you show USJ or Fuji-Q hours, say they come from ThemeParks.wiki (third-party, not official), say "Powered by ThemeParks.wiki" and link https://themeparks.wiki/. Do not redistribute or bulk-export that schedule. - `null` values come with a reason field (`unknown_reason`, `tickets_unknown_reason`). Repeat the reason; do not fill in a guess. - `sale_opens_at` with `observed: false` is the published TDR rule, not an observation. - `typical` numbers are your local recorded samples, not a forecast. Always give `samples`, `distinct_days` and the first/last date. ## Auth Setup No authentication required. Run `japan-theme-parks-pp-cli doctor` to verify setup. ## Agent Mode Add `--agent` to any command. Expands to: `--json --compact --no-input --no-color`. Global format flags share one contract on promoted, novel, and `--deliver` paths: - `--json` — one JSON document on stdout (warnings and hints go to stderr) - `--compact` — keep identity/status/timestamp fields; does not change the document vs stream shape - `--csv` / `--plain` — tabular rows (collection envelopes unwrap to the row array) - `--quiet` — one identity value per row, no envelope - **Pipeable** — JSON on stdout, errors on stderr - **Filterable** — `--select` keeps a subset of fields. Dotted paths descend into nested structures; arrays traverse element-wise. Critical for keeping context small on verbose APIs: ```bash japan-theme-parks-pp-cli dates 2026-11-14 --park tds --agent --select results.date,results.one_day_passport_status ``` - **Previewable** — `--dry-run` shows the request without sending - **Local history** — `typical` and the usual-wait columns of `waits` read only the SQLite history that `snapshot` writes - **Non-interactive** — never prompts, every input is a flag - **Read-only** — do not use this CLI for create, update, delete, publish, comment, upvote, invite, order, send, or other mutating requests ### Response envelope Commands that read from the local store or the API wrap output in a provenance envelope: ```json { "meta": { "source": "live | local | computed | dry-run", "generated_at": "2026-10-09T02:33:36Z", "timezone": "Asia/Tokyo", "sources": [{"name": "queue-times.com", "url": "...", "fetched_at": "...", "attribution": "Powered by Queue-Times.com", "attribution_url": "https://queue-times.com/"}], "fetch_failures": [{"source": "api.themeparks.wiki", "error": "..."}], "notes": ["..."] }, "results": "" } ``` Parse `.results` for data, `.meta.source` to know whether it is live, local or computed, and `.meta.sources[]` for the fetch time and the credit to show. A non-empty `fetch_failures` means part of the data is missing (the matching fields are null with a reason). A human-readable `N results (live)` summary is printed to stderr only when stdout is a terminal AND no machine-format flag (`--json`, `--csv`, `--compact`, `--quiet`, `--plain`, `--select`) is set — piped/agent consumers and explicit-format runs get pure JSON on stdout. ## Paths and state Agents should treat the CLI's path resolver as part of the runtime contract: - Use `--home ` for one invocation, or set `JAPAN_THEME_PARKS_HOME=` to relocate all four path kinds under one root. - Use per-kind env vars only when a specific kind must diverge: `JAPAN_THEME_PARKS_CONFIG_DIR`, `JAPAN_THEME_PARKS_DATA_DIR`, `JAPAN_THEME_PARKS_STATE_DIR`, `JAPAN_THEME_PARKS_CACHE_DIR`. - Resolution order is per-kind env var, `--home`, `JAPAN_THEME_PARKS_HOME`, XDG (`XDG_CONFIG_HOME`, `XDG_DATA_HOME`, `XDG_STATE_HOME`, `XDG_CACHE_HOME`), then platform defaults. - `config` contains settings like `config.toml` and profiles. `data` contains durable local data such as `data.db`. `state` contains the learning journal and `teach.log`. `cache` contains regenerable HTTP/cache files. - Run `japan-theme-parks-pp-cli doctor --fail-on warn` to surface path warnings. `agent-context` exposes a schema v4 `paths` block for agents that need the resolved dirs. - For MCP, pass relocation through the MCP host config. The MCP binary does not inherit CLI flags: ```json { "mcpServers": { "japan-theme-parks": { "command": "japan-theme-parks-pp-mcp", "env": { "JAPAN_THEME_PARKS_HOME": "/srv/japan-theme-parks" } } } } ``` Fleet precedence: an inherited per-kind env var overrides an explicit `--home` for that kind. Use `JAPAN_THEME_PARKS_HOME` or per-kind vars as durable fleet levers, and use `--home` only for a single invocation. Relocation is not reversible by unsetting env vars; move files manually before clearing `JAPAN_THEME_PARKS_HOME`, or `doctor` will not find files left under the former root. ## Automatic learning This CLI ships a self-capturing learning loop. The CLI does its own bookkeeping: every invocation is journaled locally, a failed flag followed by a corrected retry auto-derives a `flag_alias` candidate, and a `teach` on a query family without a playbook auto-synthesizes a `playbook_candidate` from the session's journal. Your job is judgment only: `recall` first, act on surfaced candidates, `teach` the final answer, `playbook amend` when you observe a correction. You never record failures by hand. ### Step 1: `recall` before any discovery Before list/search/drill commands on a new user question, pass the question as an argv or MCP tool argument to `recall --agent`. Do not interpolate user-controlled text into a shell command line. Quoted `recall ""` breaks on an apostrophe, which is ordinary English. A quoted heredoc breaks when a body line equals the delimiter, and that delimiter is published in these docs. Write the question with a non-shell file-writing tool, then read it back as data: ```bash # Write the question verbatim with your file-writing tool (no shell involved). # Command substitution on a file only ever yields data — the shell never # parses the file's bytes as syntax. QUERY=$(cat /path/to/question.txt) japan-theme-parks-pp-cli recall "$QUERY" --agent ``` Prefer MCP: pass the question as the tool's query argument. `"$QUERY"` after a file read is argv-safe; putting the question itself in the command text is not. The response envelope: ```json { "query": "...", "normalized": "", "query_entities": ["..."], "found": true | false, "match_score": 0.0, "results": [ { "resource_id": "...", "resource_type": "...", "venue": "...", "confidence": 2, "entity_match": "exact|partial|unknown", "source": "taught|preseed|pattern", "warnings": ["..."] } ], "mismatches": [ /* only when --debug-mismatches */ ], "warnings": [ /* top-level */ ], "candidates": [ { "id": 12, "class": "flag_alias | playbook_candidate", "summary": "...", "sightings": 3, "last_seen": "...", "rationale": "...", "next_action": ["", "japan-theme-parks-pp-cli learnings confirm 12"] } ], "playbook": { "query_family": "...", "playbook": { "steps": [ { "cmd": "", "purpose": "..." } ], "entity_slots": ["$ENTITY"], "expected_tool_calls": 3 }, "slots_resolved": { "$ENTITY": { "token": "", "canonical": "" } }, "notes": "" }, "notes": "" } ``` Empty-store short-circuit: if the store has no learnings, playbooks, or candidates yet (recall finds nothing and `learnings list` and `learnings candidates` are both empty), skip recall for the rest of this session instead of taxing every query; resume recall-first once something has been taught. ### Step 2: decision tree Read `candidates`, `playbook`, `notes`, `results[0]`, and warnings in that order: ``` if Candidates present (warnings include "candidates_present"): -> candidates are try-then-confirm, never facts. Follow each candidate's two-step next_action verbatim: run the trial command first, then run `learnings confirm ` only after the trial verified the behavior. Reject a wrong candidate with `learnings reject `. -> NEVER re-teach something recall surfaced as a candidate; confirm or reject that candidate instead of teaching a duplicate. -> candidates ride alongside playbooks and resource hits, not instead of them; continue with the branches below after acting on them. if Playbook present: -> READ Playbook.notes verbatim FIRST (workarounds + gotchas the CLI surface doesn't expose) -> replay Playbook.steps in order, substituting Playbook.slots_resolved entries for the entity slot tokens. If a step's slot is unresolved, fall back to discovery for that step only. -> the Playbook's expected_tool_calls is a budget; if you find yourself running materially more, record the divergence via `japan-theme-parks-pp-cli playbook amend` at end-of-session. elif Notes present (no Playbook): -> read Notes verbatim before any discovery step; they carry known gotchas for this query family even when no structured choreography exists yet. elif Found AND Results[0].EntityMatch == "exact" AND Results[0].Confidence >= 2: -> skip discovery; fetch live data for Results[*].ResourceID in parallel elif Found AND Results[0].EntityMatch == "partial": -> candidate hint, NOT a hit; read the resource title to validate before trusting elif (any row in Mismatches[] when --debug-mismatches was passed): -> treat as cold start; the stored learning is for a different entity (different canonical resolved from query_entities) else: // Found == false, no playbook, no notes -> cold start; run discovery normally; teach the answer afterward (Step 4). If the family has no playbook yet, that teach auto-synthesizes a playbook candidate from this session's journal - you do not need to record one by hand. ``` Playbook and Notes are orthogonal to the per-resource path. A recall response can carry both a Playbook AND a `Results[]` hit - use both: the Playbook tells you which choreography to run; the resource hits short-circuit specific steps. Default to skipping `mismatches`; pass `--debug-mismatches` only when investigating cold-start surprises. Candidate judgment details: `learnings confirm ` prints the candidate's full payload before materializing it - check that the printed payload matches the behavior you verified. `learnings reject ` tombstones the derivation signature so the same candidate does not resurface. The envelope carries only the few candidates worth acting on now; `japan-theme-parks-pp-cli learnings candidates` lists the full open set. Graceful degradation: if `learnings confirm` is an unknown command, you are driving an older binary - ignore the candidates guidance and follow the rest of the protocol. ### Step 3: always read `warnings` - `low_confidence`: row exists at `confidence<2`. Treat as a hint, not a skip-discovery hit. - `resource_not_in_store`: the local store doesn't have the resource the learning points at. The match validator couldn't classify entities — direct-fetch and re-evaluate. - `cross_alias_match` (per-result): the row was taught under a different alias and matched the live query's canonical via `entity_lookups` (e.g., a "USA" teach satisfying a "United States" recall). Trust the resource_id. - `similar_shape_different_entity:` (top-level): a structurally matching row exists but its canonical entity differs from the live query's. Treated as cold start; the warning carries the conflicting canonical as a hint, but the row is NOT promoted into Results. - `ambiguous_alias` (top-level): a single query entity resolved to multiple canonicals (e.g., "Cards" → Arizona Cardinals + St. Louis Cardinals). Surface the ambiguity from context before committing to a resource. - `candidates_present` (top-level): the envelope carries a `candidates` section. Handle it via the candidates branch in Step 2 before anything else. - Top-level `no_learnings_for_query_family`: the table had no rows above the Jaccard floor. Pure cold start. ### Step 4: `teac