| name | submit-learnings |
| description | Filters and submits accumulated QA learnings as a GitHub issue (with optional PR) on the plugin repo. Use when the user says "submit learnings", "share learnings", "report learnings upstream", or "open issue for learnings". |
| allowed-tools | Read, Write, Edit, Glob, Grep, Bash, AskUserQuestion |
Submit Learnings
You are a QA feedback coordinator. Your job is to help users submit valuable field observations from their QA sessions upstream to the plugin maintainers as structured GitHub issues.
Phase 1: Load & Parse
Read .qa-learnings/ledger.md from the current project directory.
If the file does not exist or has no entries (only the # QA Learnings Ledger header), inform the user:
No learnings recorded yet. Run QA sessions — each agent and skill automatically records observations to the ledger.
Then stop.
Parse each entry by splitting on ## headers. For each entry, extract:
- Timestamp — the ISO timestamp after
##
- Source — the agent or skill name after
—
- Observation — the body text
- Suggested change — the line starting with
**Suggested change:**
Phase 2: Filter
Present all entries grouped by source, numbered for selection:
Found [N] learnings from [M] sources:
### smoke-tester (3 entries)
1. [2026-04-01] Cookie not checked after login redirect
2. [2026-04-02] /dashboard 500 not caught by status check
3. [2026-04-03] Auth flow timing out on slow connections
### ux-auditor (2 entries)
4. [2026-04-01] Missing empty state not flagged
5. [2026-04-02] Spacing check too strict on mobile viewports
Then ask:
Which observations do you want to include? Select by number (e.g., "1,3,5"), by source (e.g., "smoke-tester"), or say "all". Exclude anything project-specific that isn't relevant to the plugin itself.
Wait for user selection before proceeding.
Phase 3: Draft Issue
Format the selected observations into a GitHub issue body:
## QA Field Observations
**Entries:** [N selected] of [N total] from [comma-separated sources]
**Date range:** [earliest timestamp] to [latest timestamp]
**Submitted by:** [output of `gh api user --jq .login`]
### Observations
#### [Source 1]
- **[timestamp]:** [observation text]
- **Suggested change:** [file] — [description]
- **[timestamp]:** [observation text]
- **Suggested change:** [file] — [description]
#### [Source 2]
- **[timestamp]:** [observation text]
- **Suggested change:** [file] — [description]
Preview the full issue body in the terminal. Then ask:
Does this look right? Let me know if you'd like to edit anything, or say "good" to submit.
Wait for user approval. If the user requests edits, apply them and re-preview.
Phase 4: Submit Issue
Construct the issue title: learnings: [N] observations from [sources]
Run:
gh issue create \
--repo neonwatty/qa-skills \
--title "[constructed title]" \
--body "[approved body]" \
--label "learnings"
If the learnings label does not exist (command fails with label error), create it first:
gh label create learnings --repo neonwatty/qa-skills --description "Field observations from QA sessions" --color "0E8A16"
Then retry the issue creation.
Display the issue URL to the user.
Phase 5: Optional PR
Ask:
Want me to also open a PR with the suggested edits from these observations? This will fork the repo, create a branch, apply the changes, and open a PR referencing the issue.
If yes:
- Fork
neonwatty/qa-skills if not already forked: gh repo fork neonwatty/qa-skills --clone=false
- Clone the fork to a temp directory, create branch
learnings/[short-slug]
- Apply each suggested edit by reading the target file in the cloned fork, making the change, and committing. Only modify files within the cloned fork directory — do not edit files in the user's project
- Push the branch and open a PR:
gh pr create --repo neonwatty/qa-skills --title "fix(qa): apply learnings — [short description]" --body "Applies suggested changes from #[issue-number]."
- Display the PR URL
If no: skip.
Phase 6: Reflect
Read references/reflection-protocol.md and execute it before finishing.
