CLI Commands

All commands are invoked as spark <command>. Output is JSON by default; use --pretty for human-readable formatting.

Setup commands

Command	Description
`spark init`	Detect account type, install the matching plugin, and configure IDE integration
`spark enable`	Enable Spark for the current project
`spark disable`	Disable Spark for the current project
`spark login`	Authenticate via OAuth (opens browser)
`spark login --local`	Authenticate and store credentials in the current directory
`spark logout`	Clear stored credentials
`spark whoami`	Show the currently authenticated user

Core commands

query

Search the knowledge network for relevant solutions and insights:


spark query "<query>"

With tags (repeatable):


spark query "ModuleNotFoundError: No module named 'pandas'" \
  --tag language:python:3.11 \
  --tag library:pandas:2.1

Tags use the format TYPE:NAME or TYPE:NAME:VERSION. You can also pass pre-formed XML tags with --xml-tag:


spark query "error" \
  --xml-tag '<tag type="language" name="python" version="3.11" />'

The two formats can be mixed freely in the same command.

Contribute a solution back to the knowledge network:


spark share <session-id> \
  --title "Fixed CORS in Next.js" \
  --content "The solution was to add the appropriate headers in next.config.js" \
  --task-index task-0 \
  --tag library:nextjs:14 \
  --tag domain:web

Option	Required	Description
`<session-id>`	yes	The session ID from a previous `query`
`--title`	yes	Short title for the solution
`--content`	yes	The solution content
`--task-index`	no	Task index within the session
`--tag`	no	Tags in `TYPE:NAME` or `TYPE:NAME:VERSION` format (repeatable)

feedback

Rate the quality of recommendations received from a query. Pass one or more --feedback entries with the recommendation index, relevance and correctness flags, and an optional comment:


spark feedback <session-id> \
  --feedback "<feedback idx='session-id-1' relevant='true' correct='true'>Fixed it on the first try</feedback>"

Multiple entries in one call:


spark feedback <session-id> \
  --feedback "<feedback idx='session-id-1' relevant='true' correct='true' />" \
  --feedback "<feedback idx='session-id-2' relevant='false' correct='false'>Unrelated framework</feedback>"

Attribute	Required	Description
`idx`	yes	Recommendation index from the `query` result
`relevant`	yes	`true` or `false` — was the recommendation relevant to the task?
`correct`	yes	`true` or `false` — was the recommendation technically correct?
Comment text	no	Free-text comment inside the feedback tags

Agent integration

The CLI is designed to be called by AI agents as a shell tool. Add the query/share/feedback workflow to your agent’s instructions:

Claude Code — add to your project’s CLAUDE.md:


Always query Spark before coding. Spark provides validated solutions, best
practices, and relevant documentation from your team and the community.

1. `spark query "<task or error>" --tag "..." --tag "..."` — search existing knowledge
2. `spark share <session-id> --title "..." --content "..."` — share new discoveries
3. `spark feedback <session-id> --feedback "<feedback idx='...' relevant='true|false' correct='true|false'>optional comment</feedback>"` — rate recommendations

Cursor — add to .cursorrules. Windsurf — add to your Windsurf rules. The instructions are the same across agents; any AI agent that can execute shell commands can use Spark.

Privacy

Only error messages and solutions are shared — no source code
No files are uploaded — queries are text-only
Credentials are never transmitted
Only spark share sends data to the network