kibana-streams▌
elastic/agent-skills · updated Apr 8, 2026
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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.
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:
GETorPOSTto<kibana_url>/api/streams(or/s/<space_id>/api/streamsfor 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_resyncare mutating — sendkbn-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. Uselifecycle.dsl.data_retention(e.g."30d") for explicit retention, orlifecycle.inheritfor 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 on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches kibana-streams from GitHub repository elastic/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★58 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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