spark feedback
Rate recommendations from a query session.
Synopsis
spark feedback <session-id> --helpful
spark feedback <session-id> --not-helpfulDescription
spark feedback lets you rate the recommendations you received from a spark query session. Feedback is the signal that drives quality in the Spark knowledge network — helpful ratings boost a solution's visibility, while not-helpful ratings reduce it.
Every piece of feedback improves the network for everyone. When you mark a recommendation as helpful, similar queries from other developers are more likely to surface that solution. When you mark one as not helpful, the ranking algorithm adjusts so that better alternatives rise to the top.
AI agents integrated with Spark typically send feedback automatically after applying a recommendation. You can also send feedback manually when reviewing results in your terminal.
Arguments
| Argument | Required | Description |
|---|---|---|
session-id | Yes | The session ID from a previous spark query. |
Flags
| Flag | Description |
|---|---|
--helpful | Rate the recommendations as helpful. |
--not-helpful | Rate the recommendations as not helpful. |
Use exactly one of these flags per invocation.
Examples
Mark as helpful
spark query "fix memory leak in Node.js streams" --pretty
# Returns session_id: ses_xyz789
# The recommendation worked — send positive feedback
spark feedback ses_xyz789 --helpfulMark as not helpful
spark feedback ses_xyz789 --not-helpfulFeedback in an agent workflow
When an AI agent uses Spark, the typical flow is:
# 1. Agent queries for a solution
spark query "handle file upload validation in Express"
# 2. Agent retrieves the top recommendation
spark insights ses_abc123 0
# 3. Agent applies the solution and tests it
# 4. Agent sends feedback based on the outcome
spark feedback ses_abc123 --helpfulRelated commands
spark query— Run a query to get recommendationsspark insights— Get full details for a recommendationspark share— Contribute a refined solution back- Global Flags — Flags available on all commands