--- name: pp-agoda description: "Search Agoda hotels with the true all-in price, and re-rank by what you will actually pay. Trigger phrases: `find hotels in Tokyo on agoda`, `what will this agoda hotel actually cost`, `cheapest dates to stay in Bangkok`, `which agoda hotel is cheapest all in`, `check agoda prices for these dates`, `use agoda`, `run agoda`." author: "Victor Wibisono" license: "Apache-2.0" argument-hint: " [args] | install cli|mcp" allowed-tools: "Read Bash" metadata: openclaw: requires: bins: - agoda-pp-cli install: - kind: go bins: [agoda-pp-cli] module: github.com/mvanhorn/printing-press-library/library/travel/agoda/cmd/agoda-pp-cli --- # Agoda — Printing Press CLI ## Prerequisites: Install the CLI This skill drives the `agoda-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 `$HOME/.local/bin` on macOS/Linux and `%LOCALAPPDATA%\Programs\PrintingPress\bin` on Windows: ```bash npx -y @mvanhorn/printing-press-library install agoda --cli-only ``` 2. Verify: `agoda-pp-cli --version` 3. Ensure the reported install directory is on `$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 `$PATH` instead: ```bash go install github.com/mvanhorn/printing-press-library/library/travel/agoda/cmd/agoda-pp-cli@latest ``` If `--version` reports "command not found" after install, the runtime cannot see the binary directory on `$PATH`. Do not proceed with skill commands until verification succeeds. Agoda returns both the advertised price and the true all-in price in the same response, but only ever shows you the advertised one. This CLI surfaces both, breaks out the hidden tax-and-fee delta, and re-sorts by real cost - which routinely changes which hotel is cheapest. It talks to Agoda over plain HTTP with no browser, no rendering service, and no API key, and it keeps a local price history so it can answer questions a stateless scraper cannot. ## When to Use This CLI Use this CLI when an agent needs real Agoda hotel prices, particularly when the question involves cost. It is the right tool for judging what a stay actually costs, comparing finalists, sweeping flexible dates for a price floor, and tracking price drops over time. Agoda's inventory is strongest in Asia-Pacific, so it is often the better source than a Booking.com or Google Hotels tool for destinations in that region. ## Anti-triggers Do not use this CLI for: - Do not use this CLI to complete a booking or take payment - it surfaces prices and deep links, and the reservation itself happens on Agoda. - Do not use it for flights, activities, airport transfers, or car rental; it is scoped to hotels only. - Do not use it to compare Agoda against other travel sites - it reads Agoda only, so a cross-OTA question needs a different tool. - Do not use it to cancel, modify, or refund an existing reservation. ## Unique Capabilities These capabilities aren't available in any other tool for this API. ### Honest pricing - **`hotels search`** — Shows what you will actually pay, not the teaser rate, with the hidden tax-and-fee delta broken out per property. _Reach for this instead of any scraped Agoda price. Quote the inclusive figure to a user; the advertised rate is not what they will be charged._ ```bash agoda-pp-cli hotels search Tokyo --checkin 2026-10-15 --nights 2 --adults 2 --currency USD --agent ``` - **`hotels rank`** — Re-sorts a destination's results by true all-in price instead of Agoda's teaser-price ranking. _Use this whenever the decision is about price. Ordinary search ordering inherits Agoda's advertised-price ranking and will mislead._ ```bash agoda-pp-cli hotels rank Tokyo --checkin 2026-10-15 --nights 2 --limit 10 --agent ``` - **`hotels fees`** — Flags properties whose tax-and-fee ratio is an outlier against the destination median. _Use before recommending a property. A hotel with a below-median advertised price and an above-median fee ratio is the classic bait pattern._ ```bash agoda-pp-cli hotels fees Tokyo --checkin 2026-10-15 --nights 2 --agent ``` ### Local state that compounds - **`prices cheapest`** — Returns the cheapest check-in dates across a flexible window for a destination. _Use for flexible-date travelers. Returns the price floor across a window rather than a single-date quote._ ```bash agoda-pp-cli prices cheapest Tokyo --window 2026-10-01..2026-11-30 --nights 3 --agent ``` - **`vip delta`** — Runs the same search signed-in and anonymous, then diffs per property to show what your VIP tier is actually worth. _Use when a user asks whether signing in or chasing a VIP tier is worth it. Reports the measured discount on a real search instead of marketing copy._ ```bash agoda-pp-cli vip delta Tokyo --checkin 2026-10-15 --nights 2 --agent ``` - **`watch run`** — Surfaces only watched properties whose latest true all-in price dropped meaningfully below their trailing median. _Schedule it. Returns empty most days and returns something worth acting on when a watched property actually drops._ ```bash agoda-pp-cli watch run --min-pct 7 --agent ``` - **`search`** — Full-text search over every property this CLI has already seen, with no network call. _Use after a few live searches to answer property questions without spending a request or waiting on the network._ ```bash agoda-pp-cli search "shinjuku" --agent ``` ### Agent-native plumbing - **`compare`** — Puts finalist properties side by side on true all-in price, hidden fee share, review score, star rating, and free-cancellation deadline. _Use once the choice is narrowed to finalists, instead of re-reading two detail pages and eyeballing the difference._ ```bash agoda-pp-cli compare 936623 788273 --destination Tokyo --checkin 2026-10-15 --nights 2 --agent ``` ## Command Reference **destinations** — Resolve a destination name to the numeric city id every Agoda search requires - `agoda-pp-cli destinations` — Resolve a free-text destination (city, area, landmark) to an Agoda city id **reviews** — Guest reviews for a property, paginated and sortable - `agoda-pp-cli reviews` — List guest reviews for a property by Agoda hotel id ### Finding the right command When you know what you want to do but not which command does it, ask the CLI directly: ```bash agoda-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. ## Recipes ### What will this actually cost ```bash agoda-pp-cli hotels search Tokyo --checkin 2026-10-15 --nights 2 --adults 2 --currency USD --agent --select results.name,results.price_all_in,results.price_advertised,results.hidden_pct ``` Returns just the four fields that matter for a cost decision, keeping the deeply nested Agoda payload out of the agent's context. ### The cheapest hotel is not the one listed cheapest ```bash agoda-pp-cli hotels rank Tokyo --checkin 2026-10-15 --nights 2 --limit 10 --agent ``` Re-sorts by all-in cost; properties with above-average fee loads drop down the list and genuinely cheaper stays surface. ### Find the price floor for a flexible trip ```bash agoda-pp-cli prices cheapest Tokyo --window 2026-10-01..2026-11-30 --nights 3 --agent ``` Sweeps a two-month window in one pass and returns the cheapest check-in dates rather than a single-date quote. ### Spot the resort-fee trap ```bash agoda-pp-cli hotels fees Tokyo --checkin 2026-10-15 --nights 2 --agent ``` Ranks properties by how much of their true cost is tax and fees, flagging outliers against the destination median. ### Is signing in worth anything here ```bash agoda-pp-cli vip delta Tokyo --checkin 2026-10-15 --nights 2 --agent ``` Issues the same search authenticated and anonymous and reports the measured per-property discount. ## Auth Setup Public hotel search, destination lookup, property detail, and reviews need no credentials at all - they replay over ordinary HTTP. Only member-priced and account surfaces (saved properties, AgodaVIP tier, vip delta) need a logged-in session: copy the Cookie header from a signed-in agoda.com browser tab and export it as AGODA_COOKIE (AGODA_SESSION_COOKIE is also accepted), and subsequent authenticated calls replay with it. Run `agoda-pp-cli doctor` to verify setup. ## Agent Mode Add `--agent` to any command. Expands to: `--json --compact --no-input --no-color`. - **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 agoda-pp-cli reviews --agent --select hotelReviewId,rating,reviewComments ``` - **Previewable** — `--dry-run` shows the request without sending - **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 ## Paths and state Agents should treat the CLI's path resolver as part of the runtime contract: - Use `--home ` for one invocation, or set `AGODA_HOME=` to relocate all four path kinds under one root. - Use per-kind env vars only when a specific kind must diverge: `AGODA_CONFIG_DIR`, `AGODA_DATA_DIR`, `AGODA_STATE_DIR`, `AGODA_CACHE_DIR`. - Resolution order is per-kind env var, `--home`, `AGODA_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 `credentials.toml`, `data.db`, cookies, and auth sidecars. `state` contains persisted queries, jobs, and `teach.log`. `cache` contains regenerable HTTP/cache files. - Stored secrets live in `credentials.toml` under the data dir. Existing legacy `config.toml` secrets are read for compatibility and leave `config.toml` on the first auth write. - Run `agoda-pp-cli doctor --fail-on warn` to surface path and credential-location 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": { "agoda": { "command": "agoda-pp-mcp", "env": { "AGODA_HOME": "/srv/agoda" } } } } ``` Fleet precedence: an inherited per-kind env var overrides an explicit `--home` for that kind. Use `AGODA_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 `AGODA_HOME`, or `doctor` will not find credentials 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, run: ```bash agoda-pp-cli recall "" --agent ``` 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": ["", "agoda-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 `agoda-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; `agoda-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: `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: ```bash agoda-pp-cli teach --query "" --resource-type --resource --resource # (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 You do not need to decide whether a session "deserves" a playbook: a teach on a family without one auto