Kibana Agent Builder
ElasticOfficialCreated by elastic
- Skill
- Tool integration
- Data and AI
- Apache-2.0
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The kibana-agent-builder skill provides a structured interface for creating, updating, and managing custom AI agents and tools directly within Kibana. It enables users to ground LLM responses in Elasticsearch data by defining scoped index searches, parameterized ES|QL queries, and workflow integrations. The skill emphasizes a discovery-first approach, requiring users to list existing resources before performing write operations to ensure system integrity and avoid configuration conflicts.
What it does
- Lists existing agents and custom tools to prevent duplicate resource creation.
- Creates custom index search tools scoped to specific index patterns.
- Defines parameterized ES|QL tools for fixed analytics and trend reporting.
- Configures AI agents with custom instructions and curated toolsets.
- Supports CRUD operations for both agents and tools via the elastic CLI.
- Executes and validates tools to ensure correct query behavior before deployment.
When to use it
- When you need to create a new AI agent grounded in specific Elasticsearch data.
- When you want to define reusable tools for agents to perform searches or analytics.
- When you need to inspect or modify existing agent configurations or tool definitions.
- When you need to verify the existence of agents or tools before performing updates.
Advantages
- Ensures agents are grounded in real-time data rather than relying on LLM memory.
- Reduces noise and token costs by scoping index searches to specific patterns.
- Provides a consistent, repeatable process for managing AI resources in Kibana.
- Allows for complex analytics through parameterized ES|QL tool definitions.
Usage examples
- “What agents are currently configured in Agent Builder?”
- The agent will list all existing agents by ID and name, providing a clear overview of the current environment.
- “Create a new tool to search the logs-app-* index.”
- The agent will verify if the tool exists, then create an index_search tool scoped to the specified pattern.
- “Create a sales-helper agent using the esql-sales-data tool.”
- The agent will confirm the tool exists, check for agent name conflicts, and register the new agent with the specified toolset.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/elastic/kibana-agent-builder/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip kibana-agent-builder.zip -d .agents/skills
Documentation by elastic
Kibana Agent Builder
Create, inspect, update, delete, and test Agent Builder tools and agents. Ground LLM responses in Elasticsearch data through scoped search tools, parameterized ES|QL, and workflow integrations.
<!-- begin-partial: preamble -->
Environment Configuration
This skill executes Elasticsearch operations through the elastic CLI. If the
elastic CLI is not installed, tell the user what it is needed for. Do
not guess credentials, call the HTTP API directly, or attempt other workarounds.
This skill references operations in HTTP-shorthand form (e.g., GET /, GET /_cat/indices, GET /{index}/_mapping,
GET /{index}/_settings/index.mode, POST /_query). The Operations table at the end of this document
maps each shorthand to the equivalent elastic CLI command — always use the CLI rather than calling the HTTP API
directly.
<!-- end-partial: preamble -->
Resource model
Agent Builder exposes three distinct resource kinds — do not conflate them:
| Kind | Purpose | Typical API |
|---|---|---|
| Tool | Reusable function an agent invokes to retrieve or act on data (index_search, esql, workflow) | POST kbn:/api/agent_builder/tools |
| Agent | LLM entity with instructions and a curated toolset | POST kbn:/api/agent_builder/agents |
| Chat / conversation | Ephemeral messaging session with an existing agent | POST kbn:/api/agent_builder/converse/async |
Creating a tool does not create an agent. Listing or chatting with an agent does not create a tool. When the user asks to "create an agent" or "create a tool," identify which resource they mean before calling a write API.
Built-in tools use the platform.core.* prefix (for example platform.core.search). Custom tools and agents are
user-defined. Read architecture-guide.md for built-in tool inventory, context
engineering, and security notes.
Process
Classify the task. Decide whether the user needs a tool, an agent, or chat with an existing agent. If they ask what already exists ("what agents are there?", "list agents"), treat the request as read-only discovery — answer from live data before proposing any create, update, or delete.
Discover existing resources before any write. When creating or updating:
Call
GET kbn:/api/agent_builder/toolsto list available tools (built-in and custom). Do not invent tool IDs.Call
GET kbn:/api/agent_builder/agentsto list existing agents and avoid duplicate IDs or names.
When the user only asks what agents exist, stop after
GET kbn:/api/agent_builder/agents. Enumerate each agent's id and name. If the list is empty, say so plainly — do not fabricate agents. Only proceed to creation when the user explicitly asks to create one and you have confirmed the target id is unused.Choose the tool type (for tool tasks). Match intent to the narrowest tool type:
Open-ended search over a known index pattern →
index_searchwith a specific pattern (for examplecustomer-feedback-*), never*or all-indices scope unless the user explicitly requires it.Fixed analytics, aggregations, or parameterized queries →
esqlwith?paramplaceholders and aparamsobject (use{}when there are no parameters).Multi-step automation beyond retrieval →
workflowreferencing an existing workflow id.
For ES|QL syntax and query design, follow the
elasticsearch-esqlskill. For workflow YAML, follow thekibana-workflowsskill.Build the tool payload. Required fields:
id,type,description,configuration. Optional:tags.API constraints (violations return 400):
POST accepts only
id,type,description,configuration,tags.nameis not valid on tools.Index search configuration uses
"pattern", not"index".ES|QL tools require
"params"even when empty:"params": {}.Each param accepts only
typeanddescription— notdefaultoroptional. Hard-code defaults in the query.PUT on tools accepts only
description,configuration, andtags.idandtypeare immutable.
Index search example (scoped pattern):
{ "id": "customer_feedback_search", "type": "index_search", "description": "Searches customer feedback and support tickets in the customer-feedback indices.", "configuration": { "pattern": "customer-feedback-*" } }ES|QL example (parameterized, with LIMIT):
{ "id": "feedback_sentiment_trend", "type": "esql", "description": "Returns positive vs negative feedback counts by product category over a lookback window.", "configuration": { "query": "FROM customer-feedback-* | WHERE @timestamp >= NOW() - ?lookback_days::integer * 1d | STATS positive = COUNT(*) WHERE sentiment == \"positive\", negative = COUNT(*) WHERE sentiment == \"negative\" BY product_category | SORT negative DESC | LIMIT 20", "params": { "lookback_days": { "type": "integer", "description": "Number of days to look back, e.g. 7, 30, 90" } } } }Create and verify the tool. Call
POST kbn:/api/agent_builder/toolswith the payload. Confirm success by callingGET kbn:/api/agent_builder/tools/{toolId}and reporting the created id, type, description, and configuration back to the user — do not claim success without a live API response.Optionally validate ES|QL tools with
POST kbn:/api/agent_builder/tools/_execute, passingtool_idandtool_params. Always include| LIMIT Nin ES|QL queries to control token use.Build the agent payload (for agent tasks). Required fields:
id,name,description,configuration. Configuration must includeinstructionsand atoolsarray withtool_idsdrawn from Step 2 — only IDs returned byGET kbn:/api/agent_builder/tools.Derive a stable
idfrom the name (lowercase, hyphens, alphanumeric). Check Step 2's agent list for conflicts before posting.{ "id": "customer-feedback-agent", "name": "Customer Feedback Analyst", "description": "Analyzes customer sentiment and feedback trends.", "configuration": { "instructions": "Always use tools to retrieve data. Never answer data questions from memory.", "tools": [ { "tool_ids": ["customer_feedback_search", "platform.core.search"] } ] } }Agent update constraints: PUT accepts only
description,configuration, andtags(plus avatar/labels when applicable). Do not send immutable fields likeid,name, ortypeon update — they cause 400 errors.Create and verify the agent. Call
POST kbn:/api/agent_builder/agents. Confirm withGET kbn:/api/agent_builder/agentsorGET kbn:/api/agent_builder/agents/{agentId}. Report the live response.Update or delete (when requested). Confirm destructive actions with the user first.
Update tool:
PUT kbn:/api/agent_builder/tools/{toolId}Delete tool:
DELETE kbn:/api/agent_builder/tools/{toolId}Update agent:
PUT kbn:/api/agent_builder/agents/{agentId}Delete agent:
DELETE kbn:/api/agent_builder/agents/{agentId}
Chat (when requested). Chat is not agent or tool creation. Use
POST kbn:/api/agent_builder/converse/asyncwith an existingagent_idand user input. Expect multi-step reasoning and tool calls; allow sufficient time for streaming completion.
Guidelines
Discover before create. Always list agents (and tools when relevant) before creating resources. When asked "what agents exist?", answer that question first — read-only — even if the user also mentions wanting a new agent later.
Scope index search narrowly. Prefer
customer-feedback-*over*. Broad patterns increase noise, token cost, and RBAC surface area.Write descriptive tool descriptions. The agent selects tools based on descriptions alone — include when to use each tool and example trigger phrases.
Minimize toolsets. Every assigned tool adds tokens to the agent system prompt on every turn.
Validate ES|QL before deployment. Execute the tool after creation when parameters or query shape are non-trivial.
Use aggregations and KEEP. Prefer summary stats over raw document dumps for analytics questions.
Examples
Create an index search tool (eval pattern)
User: "Create a custom Agent Builder tool that searches the customer-feedback-* index. Use the tool id 'eval-feedback-search'."
List tools — confirm
eval-feedback-searchdoes not already exist.Choose
index_searchscoped tocustomer-feedback-*(not*).POST the tool with id, description, and
configuration.pattern.GET the tool by id and confirm creation to the user.
Answer "what agents already exist?" before creating
User: "I want to create a new agent in Kibana Agent Builder. What agents already exist?"
Call
GET kbn:/api/agent_builder/agents— read-only.Enumerate existing agent ids and names (or state that none exist).
Do not create, update, or delete anything in this step.
Only if the user then asks to create, pick an unused id informed by the list above.
Create an agent after discovery
User: "Create a sales-helper agent using the esql-sales-data tool."
List tools — confirm
esql-sales-dataexists.List agents — confirm no conflicting id.
POST agent with instructions and selected tool IDs.
GET agent to verify and report back.
References
architecture-guide.md — Built-in tools, context engineering, token optimization, MCP/A2A integration, permissions
use-cases.md — Playbooks for customer feedback, marketing campaign, and contract analysis agents with example tool and agent payloads
Operations
| HTTP API (shorthand) | elastic CLI command |
|---|---|
GET kbn:/api/agent_builder/tools | elastic kb agent-builder get-agent-builder-tools |
POST kbn:/api/agent_builder/tools | elastic kb agent-builder post-agent-builder-tools --id '<id>' --type '<type>' --description '<desc>' --configuration '<json>' |
GET kbn:/api/agent_builder/tools/{toolId} | elastic kb agent-builder get-agent-builder-tools-toolid --tool-id '<toolId>' |
PUT kbn:/api/agent_builder/tools/{toolId} | elastic kb agent-builder put-agent-builder-tools-toolid --tool-id '<toolId>' [--description '<desc>'] [--configuration '<json>'] |
DELETE kbn:/api/agent_builder/tools/{toolId} | elastic kb agent-builder delete-agent-builder-tools-toolid --tool-id '<toolId>' [--force] |
POST kbn:/api/agent_builder/tools/_execute | elastic kb agent-builder post-agent-builder-tools-execute --tool-id '<toolId>' --tool-params '<json>' |
GET kbn:/api/agent_builder/agents | elastic kb agent-builder get-agent-builder-agents |
POST kbn:/api/agent_builder/agents | elastic kb agent-builder post-agent-builder-agents --id '<id>' --name '<name>' --description '<desc>' --configuration '<json>' |
GET kbn:/api/agent_builder/agents/{agentId} | elastic kb agent-builder get-agent-builder-agents-id --id '<agentId>' |
PUT kbn:/api/agent_builder/agents/{agentId} | elastic kb agent-builder put-agent-builder-agents-id --id '<agentId>' [--description '<desc>'] [--configuration '<json>'] |
DELETE kbn:/api/agent_builder/agents/{agentId} | elastic kb agent-builder delete-agent-builder-agents-id --id '<agentId>' |
POST kbn:/api/agent_builder/converse/async | elastic kb agent-builder post-agent-builder-converse-async --agent-id '<agentId>' --input '<message>' |
Files
- ATTRIBUTION.mdAdded by AutoGineer969 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md13.2 KiB
- references/architecture-guide.md9.5 KiB
- references/use-cases.md11.9 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
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Attribution and licence
- Created by
- elastic
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- Elastic (Official)
- Source
- elastic/agent-skills · skills/kibana/kibana-agent-builder · commit 09d879d
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
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