--- name: pp-etsy-seller-dashboard description: "Printing Press CLI for Etsy Seller Dashboard. Read-only Etsy Shop Manager demand, advertising, offsite attribution, and promotion intelligence" author: "horknfbr" license: "Apache-2.0" argument-hint: " [args] | install cli|mcp" allowed-tools: "Read Bash" metadata: openclaw: requires: bins: - etsy-seller-dashboard-pp-cli install: - kind: go bins: [etsy-seller-dashboard-pp-cli] module: github.com/mvanhorn/printing-press-library/library/ecommerce/etsy-seller-dashboard/cmd/etsy-seller-dashboard-pp-cli --- # Etsy Seller Dashboard — Printing Press CLI ## Prerequisites: Install the CLI This skill drives the `etsy-seller-dashboard-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 `$HOME/.local/bin` on macOS/Linux and `%LOCALAPPDATA%\Programs\PrintingPress\bin` on Windows: ```bash npx -y @mvanhorn/printing-press-library install etsy-seller-dashboard --cli-only ``` 2. Verify: `etsy-seller-dashboard-pp-cli --version` 3. Ensure the reported install directory is on `$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 1.26.5 or newer). This installs into `$GOPATH/bin` (default `$HOME/go/bin`), so add that directory to `$PATH` instead: ```bash go install github.com/mvanhorn/printing-press-library/library/ecommerce/etsy-seller-dashboard/cmd/etsy-seller-dashboard-pp-cli@latest ``` If `--version` reports "command not found" after install, the runtime cannot see the binary directory on `$PATH`. Do not proceed with skill commands until verification succeeds. Bring Marketplace Insights, Etsy Ads, Offsite Ads, and Sales & Discounts into one read-only CLI. Preserve short-lived observations in SQLite, compare aligned periods, and turn disconnected seller dashboards into deterministic listing-level decisions without inventing attribution or profit. ## When Not to Use This CLI Do not activate this CLI for requests that require creating, updating, deleting, publishing, commenting, upvoting, inviting, ordering, sending messages, booking, purchasing, or changing remote state. This printed CLI exposes read-only commands for inspection, export, sync, and analysis. ## Unsupported or Unobserved Data - Marketplace Insights country filters and keyword clicks/CTR are unavailable in the captured seller surface. - Etsy Ads search terms are unavailable; never infer keyword revenue from listing titles. - Promotion order count, item count, and average order value are optional and may be absent. - Etsy-side mutations are outside this CLI's scope. ## Unique Capabilities These capabilities aren't available in any other tool for this API. ### Cross-surface decisions - **`listing action-queue`** — Rank listing-level research and marketing review actions from all four synchronized Etsy surfaces. _Use this before a weekly catalog review to decide which listings need research, ad review, promotion review, or no intervention._ ```bash etsy-seller-dashboard-pp-cli listing action-queue --agent --select listing_id,action,reasons,observed_at ``` ### Marketing economics - **`economics reconcile`** — Reconcile onsite spend, offsite fees, attributed revenue, and promotion observations without inventing net profit. _Use this before changing marketing spend or comparing channel performance._ ```bash etsy-seller-dashboard-pp-cli economics reconcile --agent ``` ### Promotion analysis - **`promotion observed-lift`** — Compare one promotion window with an equal-length prior window across promotion, onsite-ad, and offsite observations. _Use this while reviewing an active or recently ended promotion._ ```bash etsy-seller-dashboard-pp-cli promotion observed-lift PROMOTION_ID --agent ``` ### Cross-channel acquisition - **`acquisition channel-gap`** — Find listings whose separately labeled onsite and offsite efficiency signals diverge. _Use this during weekly channel-allocation review to surface onsite-strong, offsite-strong, balanced, and insufficient-data listings._ ```bash etsy-seller-dashboard-pp-cli acquisition channel-gap --agent ``` ### Quota-aware research - **`quota allocate`** — Prioritize scarce Marketplace Insights searches where stale demand evidence affects the most consequential listing decisions. _Use this before spending the weekly Marketplace Insights allowance._ ```bash etsy-seller-dashboard-pp-cli quota allocate --agent ``` ### Search and acquisition - **`listing visibility-gap`** — Compare explicit listing-keyword visibility observations with onsite and offsite performance without fabricating keyword revenue. _Use this after demand, rank, and marketing snapshots sync to distinguish visibility gaps from acquisition-efficiency gaps._ ```bash etsy-seller-dashboard-pp-cli listing visibility-gap --agent ``` ### Historical monitoring - **`growth anomalies`** — Detect deterministic weekly outliers and coincident movements across all four synchronized surfaces. _Use this for recurring portfolio review when raw dashboard totals hide exceptions._ ```bash etsy-seller-dashboard-pp-cli growth anomalies --agent ``` ## HTTP Transport This CLI uses Chrome-compatible HTTP transport for browser-facing endpoints. It does not require a resident browser process for normal API calls. ## Recipes ### Prepare the weekly four-surface review ```bash etsy-seller-dashboard-pp-cli sync --shop-id 12345678 --resources marketplace-insights,ads,offsite-ads,promotions --since 30d ``` Refresh aligned observations before running any cross-surface local analysis. ### Choose listing review priorities ```bash etsy-seller-dashboard-pp-cli listing action-queue --agent --select listing_id,action,reasons,observed_at ``` Return deterministic action codes and supporting source timestamps without a live mutation. ### Reconcile marketing economics ```bash etsy-seller-dashboard-pp-cli economics reconcile --agent ``` Preserve Etsy Ads, Offsite Ads, and promotion attribution boundaries while exposing exact subtotals and exclusions. ### Find portfolio exceptions ```bash etsy-seller-dashboard-pp-cli growth anomalies --agent ``` Detect source-linked outliers from local history after the minimum observation window is met. ## Command Reference **ads** — Review read-only Etsy Ads listing and account performance - `etsy-seller-dashboard-pp-cli ads ` — List Etsy Ads performance by listing **marketplace-insights** — Research first-party Etsy search demand, competition, trends, and saved terms - `etsy-seller-dashboard-pp-cli marketplace-insights data ` — Fetch the current Marketplace Insights data payload - `etsy-seller-dashboard-pp-cli marketplace-insights overview` — Fetch the authenticated Marketplace Insights dashboard - `etsy-seller-dashboard-pp-cli marketplace-insights saved-searches ` — List saved Marketplace Insights search terms - `etsy-seller-dashboard-pp-cli marketplace-insights search ` — Run an authenticated Marketplace Insights search - `etsy-seller-dashboard-pp-cli marketplace-insights trending-categories ` — List trending Etsy marketplace categories - `etsy-seller-dashboard-pp-cli marketplace-insights trending-terms ` — List trending Etsy search terms **offsite-ads** — Review read-only Offsite Ads attribution, traffic, channels, listings, and fees - `etsy-seller-dashboard-pp-cli offsite-ads channels ` — List Offsite Ads click performance by external channel - `etsy-seller-dashboard-pp-cli offsite-ads listings ` — List Offsite Ads clicks, orders, and attributed revenue by listing - `etsy-seller-dashboard-pp-cli offsite-ads summary ` — Fetch Offsite Ads attributed revenue, fees, orders, and new buyers - `etsy-seller-dashboard-pp-cli offsite-ads traffic ` — Fetch Offsite Ads click series and an optional comparison period **promotions** — Review read-only Etsy sales, promo codes, bundles, and targeted offers - `etsy-seller-dashboard-pp-cli promotions ` — List promotions and available revenue statistics ### Finding the right command When you know what you want to do but not which command does it, ask the CLI directly: ```bash etsy-seller-dashboard-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. ## Auth Setup These are private Shop Manager surfaces protected by the seller's Etsy session and DataDome. Sign in to Etsy in local Chrome, then use the CLI auth flow to import session cookies at runtime. Credentials remain local; doctor detects missing or expired browser-session material. The CLI does not change ad status, Offsite Ads enrollment, or promotions. Run `etsy-seller-dashboard-pp-cli doctor` to verify setup. ## Agent Mode Add `--agent` to any command. Expands to: `--json --compact --no-input --no-color --yes`. - **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 etsy-seller-dashboard-pp-cli marketplace-insights search mock-value --agent --select id,name,status ``` - **Previewable** — `--dry-run` shows the request without sending - **Offline-friendly** — sync/search commands can use the local SQLite store when available - **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", "synced_at": "...", "reason": "..."}, "results": } ``` 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 ` for one invocation, or set `ETSY_SELLER_DASHBOARD_HOME=` to relocate all four path kinds under one root. - Use per-kind env vars only when a specific kind must diverge: `ETSY_SELLER_DASHBOARD_CONFIG_DIR`, `ETSY_SELLER_DASHBOARD_DATA_DIR`, `ETSY_SELLER_DASHBOARD_STATE_DIR`, `ETSY_SELLER_DASHBOARD_CACHE_DIR`. - Resolution order is per-kind env var, `--home`, `ETSY_SELLER_DASHBOARD_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 `etsy-seller-dashboard-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": { "etsy-seller-dashboard": { "command": "etsy-seller-dashboard-pp-mcp", "env": { "ETSY_SELLER_DASHBOARD_HOME": "/srv/etsy-seller-dashboard" } } } } ``` Fleet precedence: an inherited per-kind env var overrides an explicit `--home` for that kind. Use `ETSY_SELLER_DASHBOARD_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 `ETSY_SELLER_DASHBOARD_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 etsy-seller-dashboard-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": ["", "etsy-seller-dashboard-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 `etsy-seller-dashboard-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; `etsy-seller-dashboard-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 playbo