# Pp Algolia > Every Algolia feature, plus offline search and a local database no other Algolia tool has. Trigger phrases: `search my Algolia index`, `list my Algolia indices`, `check Algolia API keys`, `find stale Algolia rules`, `compare Algolia index settings`. - Skill: `mvanhorn-printing-press-libra/pp-algolia` (Agent Skill) - Install (CLI): `npx skillmds add mvanhorn-printing-press-libra/pp-algolia` - Raw SKILL.md: https://api.skillmd.com/api/skills/mvanhorn-printing-press-libra/pp-algolia/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Integrations & APIs - License: Apache-2.0 - Author: mvanhorn (https://skillmd.com/u/mvanhorn-printing-press-libra) - Updated: 2026-09-09 - Page: https://skillmd.com/skills/mvanhorn-printing-press-libra/pp-algolia --- # Algolia — Printing Press CLI ## Prerequisites: Install the CLI This skill drives the `algolia-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 `$HOME/.local/bin` on macOS/Linux and `%LOCALAPPDATA%\Programs\PrintingPress\bin` on Windows: ```bash npx -y @mvanhorn/printing-press-library install algolia --cli-only ``` 2. Verify: `algolia-pp-cli --version` 3. Ensure the reported install directory is on `$PATH` for the agent/runtime that will invoke this skill. If the `npx` install fails before this CLI has a public-library category, install Node or use the category-specific Go fallback after publish. 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. The Algolia CLI manages indices, records, search, rules, synonyms, API keys, and settings from the terminal — with a local SQLite mirror, cross-index search, settings diffing, and relevance regression checks that the official CLI cannot offer. ## When to Use This CLI Use this CLI when you manage Algolia indices, records, rules, synonyms, or API keys from the terminal, or when you need offline access to your Algolia data for scripts, CI, and agent workflows. ## Anti-triggers Do not use this CLI for: - Do not use this CLI for Algolia Analytics or Recommend product APIs — those are separate products with their own hosts. - Do not use this CLI as a full dashboard replacement for complex merchandising visual workflows. ## Unique Capabilities These capabilities aren't available in any other tool for this API. ### Local state that compounds - **`find`** — Search across every synced index in one shot, with each hit labeled by its source index. _Use this when you need to know which of your indices contains a record, without issuing N API calls._ ```bash algolia-pp-cli find --query "dune" --limit 20 ``` - **`settings diff`** — Field-level comparison of settings between two indices (or a settings file vs an index). _Use this to verify prod/staging parity before a release instead of exporting and eyeballing JSON._ ```bash algolia-pp-cli settings diff algolia_movie_sample_dataset staging_movies ``` - **`rules stale`** — Find rules that reference attributes missing from the index's searchable attributes or that can never match. _Use this to find dead-weight relevance rules before they silently corrupt search results._ ```bash algolia-pp-cli rules stale --index algolia_movie_sample_dataset ``` - **`apikeys report`** — Audit all API keys: write-capable, unrestricted, and expired keys grouped by ACL, with last-use from synced logs. _Use this for key rotation audits to catch write-capable keys that have gone unused for months._ ```bash algolia-pp-cli apikeys report ``` - **`objects gaps`** — List records missing attributes required by the index's searchable settings — records search can never return. _Use this after catalog imports to find records that are silently unreachable by search._ ```bash algolia-pp-cli objects gaps --index algolia_movie_sample_dataset ``` - **`objects diff`** — Compare records of two indices (added/removed/changed by objectID) to verify prod/staging parity. _Use this to reconcile dev and prod copies after a copy/move operation instead of exporting and diffing files._ ```bash algolia-pp-cli objects diff algolia_movie_sample_dataset staging_movies ``` ### Agent-native plumbing - **`search check`** — Assert that a query returns expected objectIDs, with a typed exit code for CI pipelines. _Use this after every rule or synonym change to catch relevance regressions before they reach users._ ```bash algolia-pp-cli search check --index algolia_movie_sample_dataset --query "dune" --expect media-sample-data-438631 ``` - **`logs errors`** — Aggregate synced log entries by error code and link failed tasks for a digest of what went wrong. _Use this for weekly error triage to see error spikes and affected indices at a glance._ ```bash algolia-pp-cli logs errors --since 24h ``` ## Command Reference **clusters** — Multi-cluster operations. Multi-cluster operations are **deprecated**. If you have issues with your Algolia infrastructure due to large volumes of data, contact the Algolia support team. - `algolia-pp-cli clusters assign-user-id` — Assigns or moves a user ID to a cluster. - `algolia-pp-cli clusters batch-assign-user-ids` — Assigns multiple user IDs to a cluster. **You can't move users with this operation**. - `algolia-pp-cli clusters get-top-user-ids` — Get the IDs of the 10 users with the highest number of records per cluster. - `algolia-pp-cli clusters get-user-id` — Returns the user ID data stored in the mapping. - `algolia-pp-cli clusters has-pending-mappings` — To determine when the time-consuming process of creating a large batch of users or migrating users from one cluster to - `algolia-pp-cli clusters list` — Lists the available clusters in a multi-cluster setup. - `algolia-pp-cli clusters list-user-ids` — Lists the userIDs assigned to a multi-cluster application. - `algolia-pp-cli clusters remove-user-id` — Deletes a user ID and its associated data from the clusters. - `algolia-pp-cli clusters search-user-ids` — Since it can take a few seconds to get the data from the different clusters, the response isn't real-time. **dictionaries** — Manage your dictionaries. Customize language-specific settings, such as stop words, plurals, or word segmentation. Dictionaries are application-wide. - `algolia-pp-cli dictionaries get-dictionary-languages` — Lists supported languages with their supported dictionary types and number of custom entries. - `algolia-pp-cli dictionaries get-dictionary-settings` — Retrieves the languages for which standard dictionary entries are turned off. - `algolia-pp-cli dictionaries set-dictionary-settings` — Turns standard stop word dictionary entries on or off for a given language. **indexes** — Manage indexes - `algolia-pp-cli indexes add-or-update-object` — If a record with the specified object ID exists, the existing record is replaced. - `algolia-pp-cli indexes delete-index` — Deletes an index and all its settings. - Deleting an index doesn't delete its analytics data. - `algolia-pp-cli indexes delete-object` — Deletes a record by its object ID. To delete more than one record, use the [`batch` operation](https://www.algolia. - `algolia-pp-cli indexes get-object` — Retrieves one record by its object ID. To retrieve more than one record, use the [`objects` operation](https://www. - `algolia-pp-cli indexes get-objects` — Retrieves one or more records, potentially from different indices. - `algolia-pp-cli indexes list-indices` — Lists all indices in the current Algolia application. - `algolia-pp-cli indexes multiple-batch` — Adds, updates, or deletes records in multiple indices with a single API request. - `algolia-pp-cli indexes save-object` — Adds a record to an index or replaces it. - `algolia-pp-cli indexes search` — Runs multiple search queries against one or more indices in a single API request. **keys** — Manage keys - `algolia-pp-cli keys add-api` — Creates a new API key with specific permissions and restrictions. - `algolia-pp-cli keys delete-api` — Deletes the API key. - `algolia-pp-cli keys get-api` — Gets the permissions and restrictions of an API key. - `algolia-pp-cli keys list-api` — Lists all API keys associated with your Algolia application, including their permissions and restrictions. - `algolia-pp-cli keys update-api` — Replaces the permissions of an existing API key. Any unspecified attribute resets that attribute to its default value. **logs** — Manage logs - `algolia-pp-cli logs` — The request must be authenticated by an API key with the [`logs` ACL](https://www.algolia. **security** — Manage security - `algolia-pp-cli security append-source` — Adds a source to the list of allowed sources. - `algolia-pp-cli security delete-source` — Deletes a source from the list of allowed sources. - `algolia-pp-cli security get-sources` — Retrieves all allowed IP addresses with access to your application. - `algolia-pp-cli security replace-sources` — Replaces the list of allowed sources. **task** — Manage task - `algolia-pp-cli task ` — Checks the status of a given application task. ### Finding the right command When you know what you want to do but not which command does it, ask the CLI directly: ```bash algolia-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 ### Verify a relevance change ```bash algolia-pp-cli search check --index algolia_movie_sample_dataset --query "dune" --expect media-sample-data-438631 ``` Assert that a query still returns an expected hit — run in CI after every rule or synonym change. ### Find dead rules ```bash algolia-pp-cli rules stale --index algolia_movie_sample_dataset ``` Surface rules that reference removed attributes or can never match. ### Compare prod and staging settings ```bash algolia-pp-cli settings diff algolia_movie_sample_dataset staging_movies ``` See exactly which settings differ between two indices before a release. ### Cross-index lookup ```bash algolia-pp-cli find --query "dune" --select index,objectID,title --limit 10 ``` Find which synced index contains a record and narrow the output with --select. ### Audit API keys ```bash algolia-pp-cli apikeys report ``` Get a permission matrix of write-capable, unrestricted, and expired keys. ## Auth Setup Algolia uses two credentials: your Application ID (ALGOLIA_APPLICATION_ID) and an API key (ALGOLIA_API_KEY), sent as x-algolia-application-id and x-algolia-api-key headers. Find both in the Algolia dashboard under Settings > API Keys. Export them before running the CLI. Run `algolia-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 algolia-pp-cli clusters list --agent ``` - **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 - **Explicit retries** — use `--idempotent` only when an already-existing create should count as success, and use `--ignore-missing` only when a missing delete target should count as success ### 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 `ALGOLIA_HOME=` to relocate all four path kinds under one root. - Use per-kind env vars only when a specific kind must diverge: `ALGOLIA_CONFIG_DIR`, `ALGOLIA_DATA_DIR`, `ALGOLIA_STATE_DIR`, `ALGOLIA_CACHE_DIR`. - Resolution order is per-kind env var, `--home`, `ALGOLIA_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 `algolia-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": { "algolia": { "command": "algolia-pp-mcp", "env": { "ALGOLIA_HOME": "/srv/algolia" } } } } ``` Fleet precedence: an inherited per-kind env var overrides an explicit `--home` for that kind. Use `ALGOLIA_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 `ALGOLIA_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 algolia-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": ["", "algolia-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 `algolia-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; `algolia-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. - `lookup_refresh_available` (top-level): an entity in the query has no lookup row yet, but synced data could provide one. Run `algolia-pp-cli sync` to 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: ```bash algolia-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-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. algolia-pp-cli teach \ --query "" \ --resource \ --playbook-file ~/playbooks/.json \ --playbook-notes-file ~/playbooks/-notes.md # (append shell `&` to background it) # Alternate: playbook-only (no resource to record alongside). algolia-pp-cli teach-playbook \ --query "" \ --playbook-file ~/playbooks/.json \ --notes-file ~/playbooks/-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`. ```bash algolia-pp-cli playbook amend \ --query "" \ --add-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]: `). 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 `algolia-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. - `ALGOLIA_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: ``` algolia-pp-cli feedback "the --since flag is inclusive but docs say exclusive" algolia-pp-cli feedback --stdin < notes.txt algolia-pp-cli feedback list --json --limit 10 ``` Entries are stored locally as `feedback.jsonl` under the resolved data dir. They are never POSTed unless `ALGOLIA_FEEDBACK_ENDPOINT` is set AND either `--send` is passed or `ALGOLIA_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 `. 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:` | Atomically write output to `` (tmp + rename) | | `webhook:` | 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. ``` algolia-pp-cli profile save briefing --json algolia-pp-cli --profile briefing clusters list algolia-pp-cli profile list --json algolia-pp-cli profile show briefing algolia-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. ## Async Jobs For endpoints that submit long-running work, the generator detects the submit-then-poll pattern (a `job_id`/`task_id`/`operation_id` field in the response plus a sibling status endpoint) and wires up three extra flags on the submitting command: | Flag | Purpose | |------|---------| | `--wait` | Block until the job reaches a terminal status instead of returning the job ID immediately | | `--wait-timeout` | Maximum wait duration (default 10m, 0 means no timeout) | | `--wait-interval` | Initial poll interval (default 2s; grows with exponential backoff up to 30s) | Use async submission without `--wait` when you want to fire-and-forget; use `--wait` when you want one command to return the finished artifact. ## 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`: 1. **Empty, `help`, or `--help`** → show `algolia-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/developer-tools/algolia/cmd/algolia-pp-mcp@latest ``` 2. Register with Claude Code: ```bash claude mcp add algolia-pp-mcp -- algolia-pp-mcp ``` 3. Verify: `claude mcp list` ## Direct Use 1. Check if installed: `which algolia-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 algolia-pp-cli [subcommand] [args] --agent ``` 4. If ambiguous, drill into subcommand help: `algolia-pp-cli --help`.