From sdlc-wizard-cowork
Collects user feedback, bug reports, feature requests, and SDLC pattern discoveries with opt-in privacy scanning.
How this skill is triggered — by the user, by Claude, or both
Slash command
/sdlc-wizard-cowork:feedback [optional: bug | feature | pattern | improvement][optional: bug | feature | pattern | improvement]The summary Claude sees in its skill listing — used to decide when to auto-load this skill
$ARGUMENTS
$ARGUMENTS
Help users contribute back to the SDLC wizard: bug reports, feature requests, pattern sharing, and SDLC improvements. Privacy-first — never scan without explicit permission.
NEVER scan the user's repo without explicit consent. Always ask first:
"I can scan your SDLC setup to identify what you've customized vs wizard defaults. This helps me create a more specific report. May I scan? (Only file names and SDLC config are read — no source code, secrets, or business logic.)"
What IS scanned (with permission):
What is NEVER scanned:
SDLC.md metadata)Use gh issue create on the wizard repo:
gh issue create \
--repo BaseInfinity/claude-sdlc-wizard \
--title "[feedback-type]: Brief description" \
--body "$(cat <<'EOF'
## Feedback Type
bug / feature / pattern / improvement
## Description
[User's description]
## Context
- Wizard version: [from SDLC.md metadata]
- Setup type: [detected stack if permission granted]
## Evidence (if pattern sharing)
[What the user customized and why it worked]
---
Submitted via `/feedback` skill
EOF
)"
gh issue list --repo BaseInfinity/claude-sdlc-wizard --search "keywords" before creatingnpx claudepluginhub baseinfinity/claude-sdlc-wizard --plugin sdlc-wizard-cowork2plugins reuse this skill
First indexed Jul 15, 2026
Collects user feedback, bug reports, feature requests, and SDLC pattern discoveries with opt-in privacy scanning.
Captures, reviews, and files bug reports or feedback as GitHub issues under the user's own account, with sanitization and consent gate.
Files a feedback issue against the SDD plugin repo when a skill causes significant friction like contradictory instructions, tool failures, or ambiguous docs. Shows the proposed body for user approval.