Perform day-2 operations on Elastic Cloud Serverless projects using the Serverless REST API.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncloud-manage-projectExecute the skills CLI command in your project's root directory to begin installation:
Fetches cloud-manage-project from elastic/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate cloud-manage-project. Access via /cloud-manage-project in your agent's command palette.
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.
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Perform day-2 operations on Elastic Cloud Serverless projects using the Serverless REST API.
EC_API_KEY is configured. If not, run cloud-setup skill first.403 Forbidden), stop and ask the user to
verify the provided API key permissions.cloud-setup is unavailable)If this skill is installed standalone and cloud-setup is not available, instruct the user to configure Cloud
environment variables manually before running commands. Never ask the user to paste API keys in chat.
| Variable | Required | Description |
|---|---|---|
EC_API_KEY |
Yes | Elastic Cloud API key used for project management operations. |
EC_BASE_URL |
No | Cloud API base URL (default: https://api.elastic-cloud.com). |
Note: If
EC_API_KEYis missing, or the user does not have a Cloud API key yet, direct the user to generate one at Elastic Cloud API keys, then configure it locally using the steps below.
Preferred method (agent-friendly): create a .env file in the project root:
EC_API_KEY=your-api-key
EC_BASE_URL=https://api.elastic-cloud.com
All cloud/* scripts auto-load .env from the working directory.
Alternative: export directly in the terminal:
export EC_API_KEY="<your-cloud-api-key>"
export EC_BASE_URL="https://api.elastic-cloud.com"
Terminal exports may not be visible to sandboxed agents running in separate shell sessions, so prefer .env when using
an agent.
.elastic-credentials file instead. The admin password must
never appear in chat history, thinking traces, or agent output — even when using it to create an API key, pass it
directly via shell variable substitution without echoing..elastic-credentials automatically. The password is redacted from stdout. Never read or display the contents of
.elastic-credentials in chat.admin password saved by create-project and
reset-credentials exists solely to bootstrap a scoped API key — never use it for direct Elasticsearch operations.
load-credentials excludes admin credentials by default; pass --include-admin only for key creation.ELASTICSEARCH_API_KEY is set. If
only admin credentials are available, create a scoped API key via elasticsearch-authn. If that skill is not
installed, ask the user to install it or create the key manually in Kibana > Stack Management > API keys.--type and --id (except list, which only needs
--type).EC_API_KEY) for project management operations
(list, get, update, delete). Elasticsearch operations require a separate Elasticsearch API key
(ELASTICSEARCH_API_KEY) that authenticates against the project's Elasticsearch endpoint. Do not confuse the two.Use this workflow when the user asks to query or manage a project the agent did not create in the current session. It resolves the project, saves its endpoints, and ensures working Elasticsearch credentials before proceeding.
This workflow only applies to Elastic Cloud Serverless projects. If the user's Elasticsearch instance is self-managed or Elastic Cloud Hosted, this skill does not apply — skip it and proceed with the relevant skill directly. If unsure, ask the user: "Is your Elasticsearch instance an Elastic Cloud Serverless project?"
Connect to Existing Project:
- [ ] Step 1: Resolve the project
- [ ] Step 2: Get project details and load credentials
- [ ] Step 3: Acquire Elasticsearch credentials
Ask the user for the project name if not already provided. Infer the project type from the user's request:
| User says | --type |
|---|---|
| "search project", "elasticsearch project", vector search | elasticsearch |
| "observability project", "o11y", logs, metrics, traces, APM | observability |
| "security project", "SIEM", detections, endpoint protection | security |
If the type is ambiguous, list all three types to find the project.
python3 skills/cloud/manage-project/scripts/manage-project.py list \
--type elasticsearch
Match the user's reference (name, partial name, or alias) against the list results. If multiple projects match or none match, present the candidates and ask the user to pick.
Once a single project is identified, check whether .elastic-credentials already has entries for this project (from a
previous session). If so, load them with load-credentials:
eval $(python3 skills/cloud/manage-project/scripts/manage-project.py load-credentials \
--name "<project-name>")
This sets all saved environment variables for the project — endpoints and any previously created Elasticsearch API keys
— in a single command. Admin credentials (ELASTICSEARCH_USERNAME/ELASTICSEARCH_PASSWORD) are intentionally excluded.
Later sections for the same project automatically overwrite earlier values, so the most recent credentials always win.
If load-credentials reports no matching entries, fetch the project details from the API and export endpoints manually:
python3 skills/cloud/manage-project/scripts/manage-project.py get \
--type elasticsearch \
--id <project-id>
Then export the endpoint URLs from the response. The available endpoints depend on the project type.
All project types:
export ELASTICSEARCH_URL="<elasticsearch_endpoint>"
export KIBANA_URL="<kibana_endpoint>"
Observability projects (additional):
export APM_URL="<apm_endpoint>"
export INGEST_URL="<ingest_endpoint>"
Security projects (additional):
export INGEST_URL="<ingest_endpoint>"
If load-credentials set ELASTICSEARCH_API_KEY, verify the credentials work:
curl -H "Authorization: ApiKey ${ELASTICSEARCH_API_KEY}" \
"${ELASTICSEARCH_URL}/_security/_authenticate"
Confirm the response contains a valid username and "authentication_type": "api_key" before proceeding. If
verification succeeds, skip the rest of this step.
If no credentials were loaded, or verification fails, ask the user: "Do you have an existing Elasticsearch API key for this project?"
If yes — have the user add it to .elastic-credentials (see "Credential file format"). Do not accept keys in chat.
Reload and verify:
eval $(python3 skills/cloud/manage-project/scripts/manage-project.py load-credentials \
--name "<project-name>")
curl -H "Authorization: ApiKey ${ELASTICSEARCH_API_KEY}" \
"${ELASTICSEARCH_URL}/_security/_authenticate"
If no — follow this recovery path:
Confirm with the user, then reset the admin bootstrap credentials:
python3 skills/cloud/manage-project/scripts/manage-project.py reset-credentials \
--type elasticsearch \
--id <project-id>
The new password is saved to .elastic-credentials with the project name in the header. Direct the user to that file
— do not display its contents.
Load credentials with --include-admin so the admin password is available for API key creation:
eval $(python3 skills/cloud/manage-project/scripts/manage-project.py load-credentials \
--name "<project-name>" --include-admin)
Use the admin credentials to create a scoped Elasticsearch API key via elasticsearch-authn if available. If that
skill is not installed, ask the user to install it or create the key manually in Kibana > Stack Management > API
keys. Scope the key to only the privileges the user needs.
After creating the API key, save it to .elastic-credentials using the project-specific header format (see
"Credential file format" below). Then reload without --include-admin to drop admin credentials from the
environment and verify:
eval $(python3 skills/cloud/manage-project/scripts/manage-project.py load-credentials \
--name "<project-name>")
curl -H "Authorization: ApiKey ${ELASTICSEARCH_API_KEY}" \
"${ELASTICSEARCH_URL}/_security/_authenticate"
Confirm the response shows a valid username and "authentication_type": "api_key" before proceeding.
See references/credential-file-format.md for the full format specification.
eval $(python3 skills/cloud/manage-project/scripts/manage-project.py load-credentials \
--name "<project-name>")
Or by project ID:
eval $(python3 skills/cloud/manage-project/scripts/manage-project.py load-credentials \
--id <project-id>)
Parses .elastic-credentials, merges all sections for the matching project, and prints export statements. Admin
credentials (ELASTICSEARCH_USERNAME/ELASTICSEARCH_PASSWORD) are excluded by default — only endpoints and API keys
are exported. Add --include-admin when you need admin credentials to create an API key.
python3 skills/cloud/manage-project/scripts/manage-project.py list \
--type elasticsearch
Use --type observability or --type security to list other project types.
python3 skills/cloud/manage-project/scripts/manage-project.py get \
--type elasticsearch \
--id <project-id>
python3 skills/cloud/manage-project/scripts/manage-project.py update \
--type elasticsearch \
--id <project-id> \
--name "new-project-name"
Only the fields provided are updated (PATCH semantics). Supported fields: --name, --alias, --tag,
--search-power, --boost-window, --max-retention-days, --default-retention-days.
The alias is an RFC-1035 domain label (lowercase alphanumeric and hyphens, max 50 chars) that becomes part of the project's endpoint URLs. Changing the alias changes all endpoint URLs, which breaks existing clients pointing to the old URLs. Warn the user about this before applying.
python3 skills/cloud/manage-project/scripts/manage-project.py update \
--type elasticsearch \
--id <project-id> \
--alias "prod-search"
Tags are key-value metadata pairs for team tracking, cost attribution, and organization. Pass --tag KEY:VALUE for each
tag. Multiple tags can be set in a single update.
python3 skills/cloud/manage-project/scripts/manage-project.py update \
--type elasticsearch \
--id <project-id> \
--tag env:prod \
--tag team:search
Tags are sent as metadata.tags in the API request. Setting tags replaces all existing tags on the project — include
any existing tags the user wants to keep.
For Elasticsearch projects, two fields control query performance and data caching in the Search AI Lake. Ingested data is stored in cost-efficient general storage. A cache layer on top provides faster search speed for recent and frequently queried data — this cached data is considered search-ready.
| Flag | Range | Description |
|---|---|---|
--search-power |
28–3000 | Query performance level. Higher values improve performance but increase cost |
--boost-window |
1–180 | Days of data eligible for boosted caching (default: 7) |
Search Power controls the speed of searches by provisioning more or fewer query resources. Common presets (matching the Cloud UI):
| Value | Preset | BImplementation GuidePrerequisites
Time Estimate 15-45 minutes depending on use case complexity Steps
Common Pitfalls
Best Practices✓ Do
✗ Don't
💡 Pro Tips
When to Use This✓ Use when Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement. ✗ Avoid when Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion. Learning Path
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