---
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 without one auto-synthesizes a `playbook_candidate` from the session's journal, and the next session judges it via confirm/reject. Attach explicit playbook flags only when you already hold choreography worth recording verbatim - workarounds the CLI didn't surface (silently-dropped flags, undocumented params, pagination tricks, payload gotchas). Prefer the **integrated one-call form** - record the resource learning and the playbook in the same `teach` invocation:

```bash
# Common case: record both the resource learning AND the playbook in one call.
QUERY=$(cat /tmp/japan47go-question.txt)
japan47go-pp-cli teach \
  --query "$QUERY" \
  --resource-type services \
  --resource 2980022e-ef99-4115-95e5-be5227cdc74e \
  --playbook-file "/tmp/japan47go-playbook.json" \
  --playbook-notes-file "/tmp/japan47go-playbook-notes.md"
# (append shell `&` to background it)

# Alternate: playbook-only (no resource to record alongside).
QUERY=$(cat /tmp/japan47go-question.txt)
japan47go-pp-cli teach-playbook \
  --query "$QUERY" \
  --playbook-file "/tmp/japan47go-playbook.json" \
  --notes-file "/tmp/japan47go-playbook-notes.md"
```

Playbook files are JSON with `steps`, `entity_slots`, `expected_tool_calls`. Notes files are markdown carrying the gotchas verbatim. File-free callers (MCP-only agents) pass the same content inline: `--playbook-json` and `--playbook-notes` on the integrated `teach` form, `--playbook-json` and `--notes` on `teach-playbook`. On the integrated `teach` form, the playbook flags are optional - omit them entirely for a resource-only teach. On the standalone `teach-playbook` form, at least one of the playbook and notes flags must be set; both empty is rejected. Playbooks are keyed on the structural query family (entities stripped) so a recipe taught from one entity-shaped query applies to every other query of the same shape, with `slots_resolved` binding the live query's canonical at recall time.

When you DO find a playbook on a future recall, treat it as ground truth: replay the steps with `slots_resolved` substitutions, skip the discovery that the choreography already documents, and read `notes` before any step.

### Step 6: `playbook amend &` when your debug response identifies a correction

If your debug-protocol response identifies a concrete correction the notes or playbook should know — a workaround, an undocumented endpoint shape, a stale field name, observed schema drift, an empty-payload fallback — fire `playbook amend` BEFORE emitting your user-facing response. Same fire-and-forget posture as `teach`. Pass the query and note as argv/MCP arguments, or write each with a non-shell file tool and read them back (`QUERY=$(cat ...)`, `NOTE=$(cat ...)`). Do not interpolate either string into the command text:

```bash
QUERY=$(cat /tmp/japan47go-question.txt)
NOTE=$(cat /path/to/note.txt)
japan47go-pp-cli playbook amend \
  --query "$QUERY" \
  --add-note "$NOTE"
# (append shell `&` to background it)
```

What counts as worth amending: a behavior you OBSERVED this session that future-you would benefit from knowing. Examples worth amending:

- A workaround for a CLI surface that silently drops or misorders a flag.
- An undocumented endpoint shape (response wrapped in `{meta, results}`, payload nested two levels deeper than the docs claim).
- Observed schema drift (a field renamed, an index that shifted between seasons, a category label that the API now returns lower-cased).

What does NOT belong in notes:

- The year-specific or entity-specific answer to the user's question. That's the response, not a learning.
- Per-team / per-athlete / per-row data the playbook already retrieves at runtime.
- Statements that paraphrase what the existing notes already say.

The amend command appends to the family's existing notes with a timestamped marker (`[amend YYYY-MM-DDTHH:MMZ]: <text>`). Multiple amends accumulate; the audit trail is visible. If no playbook exists yet for the family, amend creates a notes-only one (so cold-start corrections still land).

#### PII discipline for amend notes

`playbook amend` notes are designed to potentially flow upstream as shared knowledge in future versions of the Printing Press. Keep them clean of user-identifying content so the upstream-contribution path stays open without retroactive scrubbing:

- **Do NOT embed** paths to user filesystems, personal API keys or tokens, user email addresses, user GitHub handles, or specific query histories tied to a single user.
- **Acceptable**: endpoint shapes, undocumented field names, API gotchas, observed schema drift, workarounds for CLI surfaces, generalizable pagination or retry tactics.

If a correction is only meaningful with user-specific context, it belongs in a personal note, not in the playbook amend.

### Measuring the loop

`japan47go-pp-cli learnings stats` reports recall hit rate, teach-to-reuse, playbook resolution rate, and candidate confirm/reject counts from the local `learn_events` table. Rates are null until they have a denominator; everything stays on this machine. Use it to check whether the loop is earning its keep for this CLI.

### Disabling learning

- `--no-learn` on a single command short-circuits both `recall` and the `teach` write path. Use for deterministic agent flows or tests that must not be affected by accumulated learnings.
- `JAPAN47GO_NO_LEARN=true` in the environment globally disables the pipeline.

## Agent Feedback

When you (or the agent) notice something off about this CLI, record it:

```
japan47go-pp-cli feedback "the --since flag is inclusive but docs say exclusive"
japan47go-pp-cli feedback --stdin < notes.txt
japan47go-pp-cli feedback list --json --limit 10
```

Entries are stored locally as `feedback.jsonl` under the resolved data dir. They are never POSTed unless `JAPAN47GO_FEEDBACK_ENDPOINT` is set AND either `--send` is passed or `JAPAN47GO_FEEDBACK_AUTO_SEND=true`. Default behavior is local-only.

Write what *surprised* you, not a bug report. Short, specific, one line: that is the part that compounds.

## Output Delivery

Every command accepts `--deliver <sink>`. The output goes to the named sink in addition to (or instead of) stdout, so agents can route command results without hand-piping. Three sinks are supported:

| Sink | Effect |
|------|--------|
| `stdout` | Default; write to stdout only |
| `file:<path>` | Atomically write output to `<path>` (tmp + rename). Binary-response commands write decoded payload bytes (not the base64 JSON envelope) and print a small JSON receipt on stdout; `--json`/`--csv` do not refuse when this sink is set. |
| `webhook:<url>` | POST the output body to the URL (`application/json`) |

Unknown schemes are refused with a structured error naming the supported set. Webhook failures return non-zero and log the URL + HTTP status on stderr.

## Named Profiles

A profile is a saved set of flag values, reused across invocations. Use it when a scheduled or recurring agent reuses the same saved flags while providing different input each run.

```
japan47go-pp-cli profile save briefing --json
japan47go-pp-cli --profile briefing services discover
japan47go-pp-cli profile list --json
japan47go-pp-cli profile show briefing
japan47go-pp-cli profile delete briefing --yes
```

Explicit flags always win over profile values; profile values win over defaults. `agent-context` lists all available profiles under `available_profiles` so introspecting agents discover them at runtime.

## Exit Codes

| Code | Meaning |
|------|---------|
| 0 | Success |
| 2 | Usage error (wrong arguments) |
| 3 | Resource not found |
| 5 | API error (upstream issue) |
| 7 | Rate limited (wait and retry) |
| 10 | Config error |

## Argument Parsing

Parse `$ARGUMENTS`:

1. **Empty, `help`, or `--help`** → show `japan47go-pp-cli --help` output
2. **Starts with `install`** → ends with `mcp` → MCP installation; otherwise → see Prerequisites above
3. **Anything else** → Direct Use (execute as CLI command with `--agent`)

## MCP Server Installation

1. Install the MCP server:
   ```bash
   go install github.com/mvanhorn/printing-press-library/library/travel/japan47go/cmd/japan47go-pp-mcp@latest
   ```
2. Register with Claude Code:
   ```bash
   claude mcp add japan47go-pp-mcp -- japan47go-pp-mcp
   ```
3. Verify: `claude mcp list`

## Direct Use

1. Check if installed: `which japan47go-pp-cli`
   If not found, offer to install (see Prerequisites at the top of this skill).
2. Match the user query to the best command from the Unique Capabilities and Command Reference above.
3. Execute with the `--agent` flag:
   ```bash
   japan47go-pp-cli services saved --agent
   ```
4. If ambiguous, drill into subcommand help: `japan47go-pp-cli services --help`.

## Evidence and completion

Use the four service workflows described in README.md. Native discovery covers guide/experience category pages and keyword search, default 1/hard 5 pages and default 10/hard 50 returned candidates. Inspect query matching total, scanned records, continuation and source routes. Listing candidates are uninspected; empty bounded windows are not absence evidence.

Generic framework live export does not support JAPAN47GO SSR HTML. It fails with source/parser exit 5 and emits no service records; this does not indicate closed, sold out or absent inventory. For reusable source data, use normalized `services discover`, `services inspect`, `services compare` or `services saved` output with `--json`.

Exact inspect/compare save only normalized decision evidence, never staffing counts, guide ages, profiles, personal contacts or raw source payloads. Japanese evidence and source URL are authoritative. Retrieval and source update clocks remain separate. Local reads create no cache files/tables; missing storage is explicitly empty. At most 200 latest observations are retained using instant-aware normal SQLite transactions.

Compare accepts 2..5 positional UUIDs or one comma-separated `--ids` string, including through MCP. `--on` and `--as-of` are exact YYYY-MM-DD dates; as-of defaults to current Japan date. A single notice rule yields a calendar deadline, while multiple rules stay ambiguous. A month subtracts calendar months and clamps the day to month end; cutoff hour and acceptance remain unknown. `--party` checks only explicit minimum participants. `--require-free` excludes paid/expense evidence and leaves missing/contradictory evidence unknown. Fee units remain null when absent and no total is invented.

Source closed=false is not opening-now evidence. Office closure text does not establish tour closure; old winter dates do not establish future seasons. Source date envelopes do not prove daily operation. `supported_by_published_rules` is only compatibility with supplied constraints. Availability remains unknown.

Use `--refresh` for forced live rechecks. `--data-source auto` falls back only on network failure, with saved timestamp and source-failure evidence; HTTP/parser errors stay errors. `local` conflicts with refresh/no-cache. Missing record exit 3, usage 2, source/parser 5, throttle 7; source failure never becomes empty success. Compare reports each partial failure; all failed reads error. A local save failure is warned explicitly.

A completed recommendation cites the Japanese name, source URL, observation time, practical request/fee/party terms and unresolved conditions. This source complements existing event/destination/booking tools; broad complete event recommendation is excluded.