mvanhorn Shopper — Printing Press CLI
Prerequisites: Install the CLI
This skill drives the shopper-pp-cli binary. You must verify the CLI is installed before invoking any command from this skill. If it is missing, install it first:
- Install via the Printing Press installer. It defaults binaries to
$HOME/.local/binon macOS/Linux and%LOCALAPPDATA%\Programs\PrintingPress\binon Windows:npx -y @mvanhorn/printing-press-library install shopper --cli-only - Verify:
shopper-pp-cli --version - Ensure the reported install directory is on
$PATHfor 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:
go install github.com/mvanhorn/printing-press-library/library/commerce/shopper/cmd/shopper-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.
shopper-pp-cli covers all six Shopper storefronts (Compra Programada, Fresh, Pet, Compra Única, Now, Now Bebidas) with correct store/cluster scoping, full siteapi REST surface, browser-deep-link helpers for subscription mutations, and a local SQLite layer for offline product search, basket diffs, price tracking, and cross-store spend rollup.
When to Use This CLI
Use shopper-pp-cli when automating Shopper basket management, monitoring charge schedules, analyzing spend patterns across storefronts, or building agent workflows around the Shopper subscription cycle. Ideal for recurring-basket optimization, pre-cycle audit, and delivery-schedule awareness.
Anti-triggers
Do not use this CLI for:
- Do not use for placing orders or confirming checkout — use checkout open to hand off to the browser
- Do not use for adding or removing saved credit cards — card management requires browser session
- Do not use for ultra-fast delivery slot selection on now/now-bebidas — delivery slots for these stores require the browser checkout flow
- Do not use for cancelling orders — cancellation is not available via siteapi REST
Unique Capabilities
These capabilities aren't available in any other tool for this API.
Subscription intelligence
charge-calendar— Every upcoming cycle's charge date, edit-lock deadline, and delivery date in one timeline so you never miss an edit window or get surprised by a charge.Use when an agent needs to know whether the edit window is still open before modifying a recurring basket.
shopper-pp-cli charge-calendar --store programada --agentbasket diff— Compares your current recurring basket against a previous cycle's snapshot to show exactly what was added, dropped, or re-quantified before the template locks.Use when an agent needs to verify what changed in the basket since the last confirmed delivery cycle.
shopper-pp-cli basket diff --store programada --agentcashback optimize— Computes the cheapest set of items to add (or whether to wait) to cross the next cashback tier, favoring things you'll need anyway.Use when an agent is finalising a basket and wants to maximise cashback return before the edit window closes.
shopper-pp-cli cashback optimize --tier 2399 --store programada --agent
Local state that compounds
price-watch— Tracks the price history of the SKUs you actually buy and alerts when one rises or drops meaningfully versus your own purchase baseline.Use when an agent needs to know if a subscribed product has changed price significantly since the last order.
shopper-pp-cli price-watch --store programada --agentrestock predict— Predicts when you'll run out of each staple from your historical buying cadence and suggests what to add to the upcoming basket.Use when an agent needs to pre-populate a recurring basket with items likely running low before the next cycle.
shopper-pp-cli restock predict --store programada --agentcatalog drift— Flags products you buy that were discontinued, silently swapped, or kept their price while shrinking the pack, surfacing the real R$/kg or R$/L change.Use when an agent needs to audit whether the recurring basket still contains the same products as originally added.
shopper-pp-cli catalog drift --store programada --agent
Customer journey plumbing
checkout preview— Aggregates cart totals, next delivery date, charge date, minimum-order status, and accepted payment types into one pre-checkout view before you open the browser.Use when an agent needs to confirm basket readiness and charge schedule before directing the user to open the browser for final payment.
shopper-pp-cli checkout preview --store programada --agent
Command Reference
address — Saved delivery addresses with per-address available-store information
shopper-pp-cli address— List delivery addresses and which stores are available at each address
cart — Cart: view summary, add products, remove products
shopper-pp-cli cart add— Add a product to the cart or increase its quantityshopper-pp-cli cart list-summary— Show current basket: items, quantities, totals, cashback, and minimum-order statusshopper-pp-cli cart remove— Remove a product from the cart or decrease its quantity
catalog — Product catalog: search, departments, banners, suggestions
shopper-pp-cli catalog create-count— Count products matching a search query and optional filtersshopper-pp-cli catalog create-filters— Get available filter options for a search queryshopper-pp-cli catalog create-search— Search the product catalog by query with optional brand/type/metadata filtersshopper-pp-cli catalog get-view— Get details for a specific catalog bannershopper-pp-cli catalog list-banners— List promotional banners for the current storeshopper-pp-cli catalog list-departments— List product departments/categories for the current storeshopper-pp-cli catalog list-news— List new product arrivals for the current storeshopper-pp-cli catalog list-suggest— Get search suggestions for a query prefix
delivery — Delivery schedule: upcoming delivery date, edit-lock window, and reschedule calendar
shopper-pp-cli delivery list-calendar— Get delivery reschedule calendar — allowed date range and disabled daysshopper-pp-cli delivery list-summary— Show scheduled delivery date, current delivery status, and store message
features — Storefront configuration, feature toggles, and timer state
shopper-pp-cli features create-select— Select active store (sets session context; no-op for header-scoped reads)shopper-pp-cli features create-start— Start a named feature timershopper-pp-cli features create-view— Mark a feature toggle as viewedshopper-pp-cli features list-stores— List all available storefronts with store IDs, cluster IDs, payment parameters, and feature flagsshopper-pp-cli features list-tick— Get current timer stateshopper-pp-cli features list-toggle— Get active feature toggles for the current store
orders — Purchase history and spend — reads from GET /orders/orders (web 'Histórico de compras')
shopper-pp-cli orders— List past orders for the active store (newest-first, paginated by size)
session — Session and social-login validation
shopper-pp-cli session— Validate social-login session status
Freshness Contract
This printed CLI owns bounded freshness only for registered store-backed read command paths. In --data-source auto mode, those paths check sync_state and may run a bounded refresh before reading local data. --data-source local never refreshes. --data-source live reads the API and does not mutate the local store. Set SHOPPER_NO_AUTO_REFRESH=1 to skip the freshness hook without changing source selection.
Covered paths:
shopper-pp-cli addressshopper-pp-cli address getshopper-pp-cli address listshopper-pp-cli address searchshopper-pp-cli cartshopper-pp-cli cart getshopper-pp-cli cart listshopper-pp-cli cart searchshopper-pp-cli catalogshopper-pp-cli catalog getshopper-pp-cli catalog listshopper-pp-cli catalog searchshopper-pp-cli catalog-departmentsshopper-pp-cli catalog-departments getshopper-pp-cli catalog-departments listshopper-pp-cli catalog-departments searchshopper-pp-cli catalog-products-newsshopper-pp-cli catalog-products-news getshopper-pp-cli catalog-products-news listshopper-pp-cli catalog-products-news searchshopper-pp-cli catalog-search-suggestshopper-pp-cli catalog-search-suggest getshopper-pp-cli catalog-search-suggest listshopper-pp-cli catalog-search-suggest searchshopper-pp-cli deliveryshopper-pp-cli delivery getshopper-pp-cli delivery listshopper-pp-cli delivery searchshopper-pp-cli delivery-v2-calendarshopper-pp-cli delivery-v2-calendar getshopper-pp-cli delivery-v2-calendar listshopper-pp-cli delivery-v2-calendar searchshopper-pp-cli featuresshopper-pp-cli features getshopper-pp-cli features listshopper-pp-cli features searchshopper-pp-cli features-timer-tickshopper-pp-cli features-timer-tick getshopper-pp-cli features-timer-tick listshopper-pp-cli features-timer-tick searchshopper-pp-cli features-toggleshopper-pp-cli features-toggle getshopper-pp-cli features-toggle listshopper-pp-cli features-toggle searchshopper-pp-cli ordersshopper-pp-cli orders getshopper-pp-cli orders listshopper-pp-cli orders searchshopper-pp-cli sessionshopper-pp-cli session getshopper-pp-cli session listshopper-pp-cli session search
When JSON output uses the generated provenance envelope, freshness metadata appears at meta.freshness. Treat it as current-cache freshness for the covered command path, not a guarantee of complete historical backfill or API-specific enrichment.
Finding the right command
When you know what you want to do but not which command does it, ask the CLI directly:
shopper-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.
Hand-written Extensions
These commands are declared by the spec author and require separate hand-written wiring; the generator does not emit Cobra registration for them. They are listed here for discoverability and are intentionally outside ## Command Reference so the verify-skill unknown-command check does not treat them as generator-owned paths.
shopper-pp-cli stores— List all available Shopper storefronts with IDs, cluster IDs, payment parameters, and capability flagsshopper-pp-cli checkout preview— Pre-checkout summary: basket totals, delivery date, charge date, min-order status, and accepted payment types (read-onlyshopper-pp-cli checkout open— Open the Shopper checkout page in the system browser (subscription-based payment via session login)shopper-pp-cli delivery reschedule [--store <store>]— Open the delivery reschedule calendar in the browser (POST /shop/minha-conta/alterar-data requires session cookie)shopper-pp-cli delivery skip— Open the skip-delivery page in the browser — subscription stores only (POST /shop/minha-conta/pular-entrega/ requiresshopper-pp-cli delivery suspend— Open the suspend-subscription page in the browser (POST /shop/minha-conta/suspender-entrega requires session cookie)shopper-pp-cli delivery boleto— Open the boleto-retrieval page in the browser to get the bank slip for the current ordershopper-pp-cli subscription pause— Open the subscription-pause page in the browser (POST /shop/carrinho/pause/ requires session cookie)shopper-pp-cli subscription resume— Open the subscription-resume page in the browser (POST /shop/carrinho/play/ requires session cookie)shopper-pp-cli payment cards— Show saved payment card count and open card-management in the browser (card add/delete is browser-required
Recipes
Check if the edit window is still open
shopper-pp-cli charge-calendar --store programada --agent --select next_delivery_date,edit_lock_date,charge_date
Returns the key dates for the next cycle; compare edit_lock_date to today to know if the basket can still be changed.
Find items to add for next cashback tier
shopper-pp-cli cashback optimize --store programada --agent
Computes the cheapest catalog additions to cross the next cashback threshold using your live cart and synced product data.
Cross-store spend rollup for last 12 months
shopper-pp-cli orders spend --agent --select store,month,total
Queries all 6 storefronts and returns a month-by-store spend matrix for budgeting analysis.
Detect if a subscribed product changed price
shopper-pp-cli price-watch --store programada --agent --select product_id,name,price_now,price_baseline,change_pct
Scans synced price history for products in your basket and flags meaningful price movements.
Pre-checkout summary with charge date
shopper-pp-cli checkout preview --store programada --agent --select total_amount,delivery_date,charge_date,min_order_met,payment_methods
Aggregates cart/delivery/payment data so an agent can confirm basket readiness before directing the user to open the checkout browser.
Auth Setup
Set SHOPPER_TOKEN to your Shopper JWT (from the siteapi Authorization header in browser DevTools). Run 'shopper-pp-cli doctor' to verify. The token is long-lived for the subscription cycle. Never store raw card numbers or CPF in config; card management always opens the browser.
Run shopper-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 —
--selectkeeps a subset of fields. Dotted paths descend into nested structures; arrays traverse element-wise. Critical for keeping context small on verbose APIs:shopper-pp-cli address --agent --select id,name,statusPreviewable —
--dry-runshows the request without sendingOffline-friendly — sync/search commands can use the local SQLite store when available
Non-interactive — never prompts, every input is a flag
Explicit retries — use
--idempotentonly when an already-existing create should count as success
Response envelope
Commands that read from the local store or the API wrap output in a provenance envelope:
{
"meta": {"source": "live" | "local", "synced_at": "...", "reason": "..."},
"results": <data>
}
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 setSHOPPER_HOME=<dir>to relocate all four path kinds under one root.Use per-kind env vars only when a specific kind must diverge:
SHOPPER_CONFIG_DIR,SHOPPER_DATA_DIR,SHOPPER_STATE_DIR,SHOPPER_CACHE_DIR.Resolution order is per-kind env var,
--home,SHOPPER_HOME, XDG (XDG_CONFIG_HOME,XDG_DATA_HOME,XDG_STATE_HOME,XDG_CACHE_HOME), then platform defaults.configcontains settings likeconfig.tomland profiles.datacontainscredentials.toml,data.db, cookies, and auth sidecars.statecontains persisted queries, jobs, andteach.log.cachecontains regenerable HTTP/cache files.Stored secrets live in
credentials.tomlunder the data dir. Existing legacyconfig.tomlsecrets are read for compatibility and leaveconfig.tomlon the first auth write.Run
shopper-pp-cli doctor --fail-on warnto surface path and credential-location warnings.agent-contextexposes a schema v4pathsblock for agents that need the resolved dirs.For MCP, pass relocation through the MCP host config. The MCP binary does not inherit CLI flags:
{ "mcpServers": { "shopper": { "command": "shopper-pp-mcp", "env": { "SHOPPER_HOME": "/srv/shopper" } } } }
Fleet precedence: an inherited per-kind env var overrides an explicit --home for that kind. Use SHOPPER_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 SHOPPER_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:
shopper-pp-cli recall "<user's question>" --agent
The response envelope:
{
"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>", "shopper-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:
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 <id>` only after the trial verified the behavior.
Reject a wrong candidate with `learnings reject <id>`.
-> 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 `shopper-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 <id> prints the candidate's full payload before materializing it - check that the printed payload matches the behavior you verified. learnings reject <id> tombstones the derivation signature so the same candidate does not resurface. The envelope carries only the few candidates worth acting on now; shopper-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 atconfidence<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 viaentity_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 acandidatessection. Handle it via the candidates branch in Step 2 before anything else.lookup_refresh_available(top-level): an entity in the query has no lookup row yet, but synced data could provide one. Runshopper-pp-cli syncto refresh entity lookups.- 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:
shopper-pp-cli teach --query "<user's question>" --resource-type <type> --resource <id1> --resource <id2>
# (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-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:
# Common case: record both the resource learning AND the playbook in one call.
shopper-pp-cli teach \
--query "<user's question>" \
--resource <id> \
--playbook-file ~/playbooks/<shape>.json \
--playbook-notes-file ~/playbooks/<shape>-notes.md
# (append shell `&` to background it)
# Alternate: playbook-only (no resource to record alongside).
shopper-pp-cli teach-playbook \
--query "<user's question>" \
--playbook-file ~/playbooks/<shape>.json \
--notes-file ~/playbooks/<shape>-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.
shopper-pp-cli playbook amend \
--query "<exact recall query string>" \
--add-note "<your concrete correction>"
# (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
shopper-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-learnon a single command short-circuits bothrecalland theteachwrite path. Use for deterministic agent flows or tests that must not be affected by accumulated learnings.SHOPPER_NO_LEARN=truein the environment globally disables the pipeline.
Agent Feedback
When you (or the agent) notice something off about this CLI, record it:
shopper-pp-cli feedback "the --since flag is inclusive but docs say exclusive"
shopper-pp-cli feedback --stdin < notes.txt
shopper-pp-cli feedback list --json --limit 10
Entries are stored locally as feedback.jsonl under the resolved data dir. They are never POSTed unless SHOPPER_FEEDBACK_ENDPOINT is set AND either --send is passed or SHOPPER_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) |
webhook:<url> |
POST the output body to the URL (application/json or application/x-ndjson when --compact) |
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.
shopper-pp-cli profile save briefing --json
shopper-pp-cli --profile briefing address
shopper-pp-cli profile list --json
shopper-pp-cli profile show briefing
shopper-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 |
| 4 | Authentication required |
| 5 | API error (upstream issue) |
| 7 | Rate limited (wait and retry) |
| 10 | Config error |
Argument Parsing
Parse $ARGUMENTS:
- Empty,
help, or--help→ showshopper-pp-cli --helpoutput - Starts with
install→ ends withmcp→ MCP installation; otherwise → see Prerequisites above - Anything else → Direct Use (execute as CLI command with
--agent)
MCP Server Installation
- Install the MCP server:
go install github.com/mvanhorn/printing-press-library/library/commerce/shopper/cmd/shopper-pp-mcp@latest - Register with Claude Code:
claude mcp add shopper-pp-mcp -- shopper-pp-mcp - Verify:
claude mcp list
Direct Use
- Check if installed:
which shopper-pp-cliIf not found, offer to install (see Prerequisites at the top of this skill). - Match the user query to the best command from the Unique Capabilities and Command Reference above.
- Execute with the
--agentflag:shopper-pp-cli <command> [subcommand] [args] --agent - If ambiguous, drill into subcommand help:
shopper-pp-cli <command> --help.