kibana-streams

elastic/agent-skills · updated Apr 8, 2026

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$npx skills add https://github.com/elastic/agent-skills --skill kibana-streams
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summary

Read stream metadata, settings, queries, significant events, and attachments, and manage stream lifecycle (enable,

  • disable, resync) via the Kibana Streams REST API. Streams are an experimental way to manage data in Kibana — expect API
  • and behavior changes. This skill covers read operations and lifecycle only; create, update, delete, fork, and
  • other mutating operations may be added in a later version.
skill.md

Kibana Streams

Read stream metadata, settings, queries, significant events, and attachments, and manage stream lifecycle (enable, disable, resync) via the Kibana Streams REST API. Streams are an experimental way to manage data in Kibana — expect API and behavior changes. This skill covers read operations and lifecycle only; create, update, delete, fork, and other mutating operations may be added in a later version.

For detailed endpoints and parameters, see references/streams-api-reference.md.

When to use

  • Listing all streams or getting a single stream's definition and metadata
  • Reading a stream's ingest or query settings
  • Listing a stream's queries
  • Reading significant events for a stream
  • Listing attachments (dashboards, rules, SLOs) linked to a stream
  • Enabling, disabling, or resyncing streams

Prerequisites

Item Description
Kibana URL Kibana endpoint (e.g. https://localhost:5601 or a Cloud deployment URL)
Authentication API key or basic auth (see the elasticsearch-authn skill)
Privileges read_stream for read operations; manage_stream for lifecycle APIs

Use the space-scoped path /s/{space_id}/api/streams when operating in a non-default space. For role configuration (Kibana feature privileges and Elasticsearch-level permissions), refer to Streams required permissions.

API base and headers

  • Base path: GET or POST to <kibana_url>/api/streams (or /s/<space_id>/api/streams for a space).
  • Read operations: Typically do not require extra headers; follow the official API docs for each endpoint.
  • Lifecycle operations: POST /api/streams/_disable, _enable, and _resync are mutating — send kbn-xsrf: true (or equivalent) as required by your Kibana version.

Operations (read + lifecycle)

Read

Operation Method Path
Get stream list GET /api/streams
Get a stream GET /api/streams/{name}
Get ingest stream settings GET /api/streams/{name}/_ingest
Get query stream settings GET /api/streams/{name}/_query
Get stream queries GET /api/streams/{name}/queries
Read significant events GET /api/streams/{name}/significant_events
Get stream attachments GET /api/streams/{streamName}/attachments

Lifecycle

Operation Method Path
Disable streams POST /api/streams/_disable
Enable streams POST /api/streams/_enable
Resync streams POST /api/streams/_resync

Path parameters: {name} and {streamName} are the stream identifier (same value; the API docs use both names).

Lifecycle and retention (ingest settings)

Ingest settings (GET /api/streams/{name}/_ingest) expose two separate lifecycle areas:

  • Stream lifecycle (ingest.lifecycle) — Controls how long the stream's data is retained. Use lifecycle.dsl.data_retention (e.g. "30d") for explicit retention, or lifecycle.inherit for child streams. This is what users usually mean when they ask to "set retention", "update retention", or "change the stream's retention".
  • Failure store lifecycle (ingest.failure_store.lifecycle) — Controls retention of failed documents only (documents that did not process successfully). Users rarely need to change this unless they explicitly mention the failure store or failed-document retention.

When a user asks to set or update retention, target the stream's main lifecycle (lifecycle.dsl.data_retention), not the failure store, unless they specifically ask about failure store or failed documents.

Examples

List streams

curl -X GET "${KIBANA_URL}/api/streams" \
  -H "Authorization: ApiKey <base64-api-key>"

Get a single stream

curl -X GET "${KIBANA_URL}/api/streams/my-stream" \
  -H "Authorization: ApiKey <base64-api-key>"

Get stream queries

curl -X GET "${KIBANA_URL}/api/streams/my-stream/queries" \
  -H "Authorization: ApiKey <base64-api-key>"

Get significant events or attachments

# Significant events
curl -X GET "${KIBANA_URL}/api/streams/my-stream/significant_events" \
  -H "Authorization: ApiKey <base64-api-key>"

# Attachments (dashboards, rules, SLOs linked to the stream)
curl -X GET "${KIBANA_URL}/api/streams/my-stream/attachments" \
  -H "Authorization: ApiKey <base64-api-key>"

Disable, enable, or resync streams

# Disable streams (request body per API docs) — deletes wired stream data; warn and confirm before proceeding
curl -X POST "${KIBANA_URL}/api/streams/_disable" \
  -H "Authorization: ApiKey <base64-api-key>" \
  -H "kbn-xsrf: true" \
  -H "Content-Type: application/json" \
  -d '{}'

# Enable streams
curl -X POST "${KIBANA_URL}/api/streams/_enable" \
  -H "Authorization: ApiKey <base64-api-key>" \
  -H "kbn-xsrf: true" \
  -H "Content-Type: application/json" \
  -d '{}'

# Resync streams
curl -X POST "${KIBANA_URL}/api/streams/_resync" \
  -H "Authorization: ApiKey <base64-api-key>" \
  -H "kbn-xsrf: true" \
  -H "Content-Type: application/json" \
  -d '{}'

Check the Streams API operation pages for request/response bodies (e.g. request body for _disable/_enable/_resync if required).

Guidelines

  • When the user asks to set or update retention, assume they mean the stream's data retention (ingest.lifecycle / lifecycle.dsl.data_retention). Do not change only the failure store retention unless they explicitly ask about the failure store or failed documents.
  • Other mutating operations (create, update, delete, fork, bulk query management, attachment management, and more) are not supported by this skill. See references/streams-api-reference.md for the full list of deferred operations.
  • Disabling streams can lead to data loss for wired streams. The disable API deletes wired stream data (classic stream data is preserved). Before calling disable, warn the user and confirm they understand the risk (and have backed up or no longer need the data).
  • Prefer read operations when the user only needs to inspect stream state; use lifecycle APIs when they need to enable, disable, or resync streams.
how to use kibana-streams

How to use kibana-streams on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add kibana-streams
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/elastic/agent-skills --skill kibana-streams

The skills CLI fetches kibana-streams from GitHub repository elastic/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/kibana-streams

Reload or restart Cursor to activate kibana-streams. Access the skill through slash commands (e.g., /kibana-streams) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.658 reviews
  • Sofia Smith· Dec 28, 2024

    Solid pick for teams standardizing on skills: kibana-streams is focused, and the summary matches what you get after install.

  • Maya Verma· Dec 24, 2024

    kibana-streams reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Alexander Bansal· Dec 24, 2024

    Useful defaults in kibana-streams — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Amelia Torres· Dec 20, 2024

    kibana-streams is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Maya Gupta· Dec 16, 2024

    kibana-streams fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Dec 8, 2024

    Registry listing for kibana-streams matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Daniel Kapoor· Dec 8, 2024

    We added kibana-streams from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Dhruvi Jain· Nov 27, 2024

    kibana-streams reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ama Rao· Nov 27, 2024

    Useful defaults in kibana-streams — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Sofia Anderson· Nov 19, 2024

    kibana-streams has been reliable in day-to-day use. Documentation quality is above average for community skills.

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