---
name: pp-japan47go
description: "Find local guides and experiences with published request, fee and participant evidence. Trigger phrases: `check JAPAN47GO guide request deadline`, `compare Japanese volunteer guide expenses`, `find local guide minimum participants`, `use japan47go`, `run japan47go`."
author: "zjsng"
license: "Apache-2.0"
argument-hint: "<command> [args] | install cli|mcp"
allowed-tools: "Read Bash"
metadata:
  openclaw:
    requires:
      bins:
        - japan47go-pp-cli
    install:
      - kind: go
        bins: [japan47go-pp-cli]
        module: github.com/mvanhorn/printing-press-library/library/travel/japan47go/cmd/japan47go-pp-cli
---
<!-- GENERATED FILE — DO NOT EDIT.
     This file is a verbatim mirror of library/travel/japan47go/SKILL.md,
     regenerated post-merge by tools/generate-skills/. Hand-edits here are
     silently overwritten on the next regen. Edit the library/ source instead.
     See the repository agent guide, section "Generated artifacts: registry.json, cli-skills/". -->

# JAPAN47GO — Printing Press CLI

## Prerequisites: Install the CLI

This skill drives the `japan47go-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 `$HOME/.local/bin` on macOS/Linux and `%LOCALAPPDATA%\Programs\PrintingPress\bin` on Windows:
   ```bash
   npx -y @mvanhorn/printing-press-library install japan47go --cli-only
   ```
2. Verify: `japan47go-pp-cli --version`
3. Ensure the reported install directory is on `$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 1.26.6 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/japan47go/cmd/japan47go-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.

Discover a bounded Japanese shortlist, inspect local association conditions, and compare notice, party and fee rules before choosing a date. Saved observations retain their source and retrieval times; availability remains unknown.

## When to Use This CLI

Use for Japanese local guide-association request conditions and selected experiences where notice, party size, qualified fees or route durations matter. Inspect details before making a recommendation and cite the source with observation time.

## Anti-triggers

Do not use this CLI for:
- Bookings, payments or messages
- Live inventory, opening now or guaranteed operation
- Broad complete event recommendations or personal suitability

## Unique Capabilities

These capabilities aren't available in any other tool for this API.

### Local service decisions
- **`services discover`** — Find Japanese guide and experience candidates with honest page coverage.

  _Find Japanese guide and experience candidates with honest page coverage._

  ```bash
  japan47go-pp-cli services discover --query 妻籠 --kind guides --max-pages 1 --limit 3 --agent
  ```
- **`services inspect`** — Inspect bounded Japanese request, duration, fee and schedule facts.

  _Inspect bounded Japanese request, duration, fee and schedule facts._

  ```bash
  japan47go-pp-cli services inspect 2980022e-ef99-4115-95e5-be5227cdc74e --agent
  ```
- **`services compare`** — Check a requested date and party against explicit notice and participant rules.

  _Check a requested date and party against explicit notice and participant rules._

  ```bash
  japan47go-pp-cli services compare --ids 2980022e-ef99-4115-95e5-be5227cdc74e,0ad62a4e-2987-4e83-af63-7a6dd69e0d98 --on 2026-11-01 --as-of 2026-10-25 --party 1 --agent
  ```
- **`services compare`** — Compare fees without turning expense-based volunteer services into free tours.

  _Compare fees without turning expense-based volunteer services into free tours._

  ```bash
  japan47go-pp-cli services compare --ids 0ad62a4e-2987-4e83-af63-7a6dd69e0d98,c98eaa8d-a854-4494-88db-a04b6de17461 --require-free --agent
  ```

### Saved evidence
- **`services saved`** — Revisit saved normalized facts offline with original observation times.

  _Revisit saved normalized facts offline with original observation times._

  ```bash
  japan47go-pp-cli services saved --query 妻籠 --limit 3 --agent
  ```

## Command Reference

**services** — Local guide and experience evidence

- `japan47go-pp-cli services discover` — Discover bounded Japanese local service candidates
- `japan47go-pp-cli services inspect` — Inspect published local guide or experience facts


- `japan47go-pp-cli services compare` — Compare explicit notice, party and qualified fee requirements across 2..5 records
- `japan47go-pp-cli services saved` — Read normalized observations offline with fetch times

### Finding the right command

When you know what you want to do but not which command does it, ask the CLI directly:

```bash
japan47go-pp-cli which "<capability in your own words>"
```

`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

### Guide candidates

```bash
japan47go-pp-cli services discover --query 妻籠 --kind guides --max-pages 1 --limit 3 --agent
```

Carry source query and page coverage into the answer.

### Compact source conditions

```bash
japan47go-pp-cli services inspect 2980022e-ef99-4115-95e5-be5227cdc74e --agent --select id,name_ja,source_url,request,price,durations_minutes,observed_at
```

Keep decision facts and provenance visible.

### Short notice and single traveler

```bash
japan47go-pp-cli services compare --ids 2980022e-ef99-4115-95e5-be5227cdc74e,0ad62a4e-2987-4e83-af63-7a6dd69e0d98 --on 2026-11-01 --as-of 2026-10-25 --party 1 --agent
```

Published-rule compatibility does not imply an available guide.

### Saved evidence

```bash
japan47go-pp-cli services saved --query 妻籠 --limit 3 --agent
```

Use recorded fetch times rather than implying current facts.

## Auth Setup

Public anonymous JAPAN47GO SSR pages; no API key or browser required. Provider reads only.

Run `japan47go-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 the service workflows and generated learning commands:

- `--json` — one JSON document on stdout (warnings 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
  japan47go-pp-cli services discover --agent --select id,name_ja,source_url
  ```
- **Previewable** — `--dry-run` shows the request without sending
- **Offline evidence** — services saved and services inspect/compare --data-source local read normalized recorded facts
- **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": "local"},
  "results": {"service": [], "returned": 0, "note": "No matching saved observations."}
}
```

Parse `.results` for data and `.meta.source` to know whether it's live or local. 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 <dir>` for one invocation, or set `JAPAN47GO_HOME=<dir>` to relocate all four path kinds under one root.
- Use per-kind env vars only when a specific kind must diverge: `JAPAN47GO_CONFIG_DIR`, `JAPAN47GO_DATA_DIR`, `JAPAN47GO_STATE_DIR`, `JAPAN47GO_CACHE_DIR`.
- Resolution order is per-kind env var, `--home`, `JAPAN47GO_HOME`, XDG (`XDG_CONFIG_HOME`, `XDG_DATA_HOME`, `XDG_STATE_HOME`, `XDG_CACHE_HOME`), then platform defaults.
- `config` contains runtime `config.json` settings and profiles. `data` holds the separate generated learning database. `state` contains persisted queries/jobs and `teach.log`. `cache` contains the bounded `japan47go-observations-v1.sqlite` service observations.
- Public source reads require no credentials. No secret file or TOML migration is part of the service workflow.
- Run `japan47go-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": {
      "japan47go": {
        "command": "japan47go-pp-mcp",
        "env": {
          "JAPAN47GO_HOME": "/srv/japan47go"
        }
      }
    }
  }
  ```

Fleet precedence: an inherited per-kind env var overrides an explicit `--home` for that kind. Use `JAPAN47GO_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 `JAPAN47GO_HOME`, or saved observations will remain 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 "<question>"` 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=$(cat /tmp/japan47go-question.txt)
japan47go-pp-cli recall "$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": "<normalized form>",
  "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": ["<trial command>", "japan47go-pp-cli learnings confirm 12"] }
  ],
  "playbook": {
    "query_family": "...",
    "playbook": {
      "steps": [ { "cmd": "<command with {slot} substitution>", "purpose": "..." } ],
      "entity_slots": ["$ENTITY"],
      "expected_tool_calls": 3
    },
    "slots_resolved": { "$ENTITY": { "token": "<live token>", "canonical": "<canonical>" } },
    "notes": "<workarounds + gotchas for this query family>"
  },
  "notes": "<duplicate surface for non-playbook callers>"
}
```

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. Candidate confirmation/rejection uses the numeric `candidates[].id`, which is separate from a service UUID. The example below assumes the returned candidate ID is 1; substitute the actual returned numeric ID:

```
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 1` only after the trial verified the behavior.
       Reject a wrong candidate with `learnings reject 1`.
    -> 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 `japan47go-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 1` prints the candidate's full payload before materializing it - check that the printed payload matches the behavior you verified. `learnings reject 1` tombstones the derivation signature so the same candidate does not resurface. The envelope carries only the few candidates worth acting on now; `japan47go-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:<canonical>` (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: `teach &` after finalizing your response - always

Teaching is unconditional. After resolving a query the store could not answer, background-teach the final resource mapping - no call-count threshold, no judging whether it was "worth" learning. The teach is the anchor of the loop: it triggers playbook synthesis for a family without a playbook, and same-referent phrasings fold into one family so near-duplicate teaches do not fragment the store. Fire it after assembling your user-facing response but BEFORE emitting it, with a shell `&` so the call returns immediately. Pass the query the same way as recall — argv/MCP, or file-then-`$QUERY`. Do not splice the question into the command text:

```bash
QUERY=$(cat /tmp/japan47go-question.txt)
japan47go-pp-cli teach --query "$QUERY" --resource-type services --resource 2980022e-ef99-4115-95e5-be5227cdc74e --resource 0ad62a4e-2987-4e83-af63-7a6dd69e0d98
# (append shell `&` to background it)
```

Silent on success. Errors only land in `teach.log` under the resolved state dir. Teach the **most specific** resource - if the user asked a broad question and you walked through parent records to find the specific answer, teach the leaf id, not the parent. The CLI uses seeded `entity_lookups` for cross-alias resolution at recall time, so a teach under one alias (e.g., "Niners") satisfies future queries under another alias (e.g., "49ers", "San Francisco") automatically.

PII rule: teach the structural question with identifiers stripped - never include names, emails, phone numbers, account ids, or other personal identifiers in taught queries or notes. The CLI scans teach queries for obvious email/phone shapes and warns, but does not block; strip before teaching rather than relying on the warning.

### Step 5: playbooks - optional flags, automatic synthesis

Before running either file-based example, write the playbook JSON to `/tmp/japan47go-playbook.json` and its Markdown notes to `/tmp/japan47go-playbook-notes.md` using the file-writing tool. The paths below refer to those existing files.

You do not need to decide whether a session "deserves" a playbook: a teach on a family wit