| name | algobot-cli |
| description | Use for anything AI/agent/conversational built on Algolia: algobot CLI, Agent Studio, RAG systems, conversational product discovery, genAI content generation from search results (carousels, descriptions, headers), chatbots or recommendation agents using Algolia as retrieval, config-as-code workflows, multi-environment deploy (dev/staging/prod), memory and personalization, MCP tool integrations, conversation history / GDPR retention, or adding a chat widget alongside InstantSearch. Trigger on: "algobot", "Agent Studio", "RAG with Algolia", "conversational experience", "AI agent" + Algolia, "genAI carousel", "chat widget", or building AI features on top of Algolia search. Do NOT use for raw index ops (records, synonyms, settings) — use algolia-cli. Do NOT use for pure frontend search UI (InstantSearch, autocomplete) with no AI/agent layer. |
| license | MIT |
| metadata | {"author":"algolia","version":"1.1"} |
Algobot CLI
Algolia Agent Studio is Algolia's platform for building AI agents — RAG systems, conversational experiences, genAI content generation — with Algolia search and recommendations as the retrieval backbone. algobot (npm install -g algobot-ai) is its CLI for creating, testing, and deploying agents.
When to Use Algobot vs Other Tools
| Need | Use |
|---|
| Build/manage AI agents on Algolia (RAG, chatbot, genAI UI) | algobot-cli (this skill) |
| Algolia search index ops (records, settings, synonyms) | algolia-cli |
| Search queries, analytics, recommendations | algolia-mcp |
Setup
npm install -g algobot-ai
algobot init
Or add a profile manually (CI-safe, non-interactive):
algobot profiles add --name prod --env prod
Non-Interactive Mode (Critical for Agents)
The TUI won't render in non-TTY environments (CI, scripts, agent subprocesses). Use these instead:
algobot ask "What is your return policy?"
algobot interactive --text "hello ||| list my orders ||| /context"
algobot agents list --jq '.[] | .name'
--jq is built-in — no need to install jq separately.
Core Commands
Agent Management
algobot agents list
algobot agents get <agent-id>
algobot agents create --name "Support Bot" --model gpt-4o
algobot agents update <agent-id> --name "New Name"
algobot agents publish <agent-id>
algobot agents unpublish <agent-id>
algobot agents delete <agent-id>
algobot agents copy <id> --from-env dev --to-env prod
Chatting with an Agent
algobot ask "Find wireless headphones under $100"
algobot --profile staging ask "hello"
algobot --verbose ask "debug this"
Profile / Environment Management
algobot profiles list
algobot profiles add --name dev --env dev
algobot profiles setdefault prod
algobot --profile prod agents list
algobot --env dev agents list
Config-as-Code Workflow
Version-control agent definitions with mustache templates — ideal for repeatable deployments across events, teams, or environments.
algobot agents scaffold <agent-id>
algobot --dry-run agents create --config agent-config.json --var event="Spring 2026"
algobot agents create --config agent-config.json --var event_name="Spring 2026"
algobot agents update <id> --config agent-config.json --var event_name="Summer 2026" --publish
{{key}} in JSON fields: JSON-safe escaping. In .md instructions: raw substitution.
Agent Studio Capabilities (via agent config)
Beyond basic chat, Agent Studio agents support:
- Tools: Algolia Search, Algolia Browse, Algolia Recommend, client-side tools, and MCP tools (connect CRMs, inventory systems, external APIs alongside Algolia). Manage with
algobot tools list/add/remove
- Memory: Semantic (facts/preferences) and episodic (past interactions) memory across sessions, using
algolia_memorize, algolia_ponder, and algolia_memory_search tools. Configure retrieval mode (preload vs preflight) in agent config.
- Conversation storage: Persistent history with configurable retention — see
algobot conversations for export/delete
- Experimental: Citation markers
[1][2] on responses, date injection, response caching — enable in agent config
Use algobot agents scaffold to inspect/edit these settings, algobot --dry-run to preview before applying.
Live Development
algobot agents watch patch.json
Global Flags
| Flag | Effect |
|---|
--env dev|staging|prod|local | Target environment |
--profile <name> | Use named profile |
--dry-run | Preview without mutating (API-enforced) |
--verbose | Full HTTP logs |
--jq '<expr>' | Filter JSON output |
--confirm | Skip exec tool confirmations |
Gotchas
- TUI requires TTY.
algobot with no args launches the TUI — hangs in scripts. Always use ask or --text in non-interactive contexts.
- Exit codes are 0/1 only in v2.0. Can't distinguish "not found" from "auth error" — parse stderr if needed.
--output json missing on most commands in v2.0. Use --jq or JSON-structured stdout.algobot init is interactive. Don't use in CI — use profiles add with flags instead.- Auth stored in
~/.algobot-cookie (AES-256-GCM). Inspect with algobot auth show.
--config auto-discovers agent-config.json in cwd. Explicit: --config path/to/config.json.- algobot = dev/deploy tool; REST API = production invocation. Use algobot to build and publish agents; call the Agent Studio completions API directly from your app. Don't guess the endpoint URL — run
algobot agents get <id> to retrieve it, or check the Agent Studio dashboard.
- Completions URL has no
/agent-studio prefix. Use agent-studio.<region>.algolia.com/1/agents/<id>/completions?stream=false&compatibilityMode=ai-sdk-4. compatibilityMode is required (omitting → 422). Response: { id, role, content } with content as a flat string.
agents create --provider <name> does not link the provider. Agent stays draft, publish 409s. After create, run algobot agents patch <id> --json patch.json with {"providerId": "<uuid>"}, then publish.
Reference Docs
