feedback

name	feedback
description	Save SDLC workflow feedback proactively. MUST trigger when the user corrects SDLC behavior ("don't generate tests like that", "always use this pattern", "that's not how I want specs written") or confirms a non-obvious approach worked ("yes exactly", "perfect"). Also trigger on explicit requests: "save this feedback", "show my feedback", "clear feedback", "workflow preferences", "sdlc settings", "consolidate feedback", "bake in my preferences". Also the graduation target for durable loop signs from .sdlc/signs.md. Feedback persists across sessions and is loaded by the sdlc-loop, BDD, TDD, and beads skills.
args	[{"name":"action","description":"Action to take: save, show, clear, or consolidate","required":false}]
user-invokable	true
effort	low
allowed-tools	["Bash","Read","Edit"]

Autonomous SDLC Feedback Manager

Persist feedback about SDLC workflow preferences across sessions. Stored feedback is automatically loaded by the sdlc-loop, BDD, TDD, and beads skills, ensuring workflow preferences carry forward.

Actions

Save Feedback

When the user provides feedback on SDLC workflow behavior, save it:

echo '{"category": "<category>", "feedback": "<what the user said>", "context": "<optional context>"}' | \
  python ${CLAUDE_PLUGIN_ROOT}/scripts/feedback_manager.py autonomous-sdlc save-feedback

Categories: spec_writing, test_generation, tdd_workflow, bdd_workflow, verification, beads_workflow, loop_behavior, general

Examples:

• "BDD specs should use business language, not technical" → {"category": "spec_writing", "feedback": "Write BDD scenarios in business domain language — avoid implementation details like class names or API endpoints"}
• "Don't generate integration tests unless I ask" → {"category": "test_generation", "feedback": "Default to unit tests only — only generate integration tests when explicitly requested"}
• "Verification should check for type errors" → {"category": "verification", "feedback": "Always include mypy/pyright type checking in the verification stack"}
• "Use pytest fixtures over setup methods" → {"category": "tdd_workflow", "feedback": "Prefer pytest fixtures over setUp/tearDown class methods for test setup"}
• "Keep beads issues concise" → {"category": "beads_workflow", "feedback": "Beads issue descriptions should be 2-3 sentences maximum — link to specs for detail"}
• "Red-green-refactor cycles should be smaller" → {"category": "tdd_workflow", "feedback": "Each TDD cycle should touch at most one function — break larger changes into multiple cycles"}

Show Feedback

Display all stored feedback:

python ${CLAUDE_PLUGIN_ROOT}/scripts/feedback_manager.py autonomous-sdlc show-feedback

Present as a readable list grouped by category.

Clear Feedback

Clear all feedback or feedback for a specific category:

# Clear all
python ${CLAUDE_PLUGIN_ROOT}/scripts/feedback_manager.py autonomous-sdlc clear-feedback

# Clear only test_generation feedback
python ${CLAUDE_PLUGIN_ROOT}/scripts/feedback_manager.py autonomous-sdlc clear-feedback test_generation

Consolidate Feedback

Graduate stable feedback into the actual SKILL.md files, making corrections permanent. This is a Claude-driven operation — no script needed.

When to consolidate: When the user says "update the plugin based on feedback", "consolidate feedback", "bake in my preferences", or "graduate feedback into the skill".

Process:

1. Load all stored feedback:

python ${CLAUDE_PLUGIN_ROOT}/scripts/feedback_manager.py autonomous-sdlc show-feedback

2. Read the target SKILL.md files:

   • ${CLAUDE_PLUGIN_ROOT}/skills/sdlc-loop/SKILL.md
   • ${CLAUDE_PLUGIN_ROOT}/skills/bdd-spec/SKILL.md
   • ${CLAUDE_PLUGIN_ROOT}/skills/bdd-generate/SKILL.md
   • ${CLAUDE_PLUGIN_ROOT}/skills/tdd-workflow/SKILL.md
   • ${CLAUDE_PLUGIN_ROOT}/skills/beads-workflow/SKILL.md

3. For each feedback entry, determine if it should be consolidated:

   • Consolidate: Universal preferences, repeated corrections, style rules that always apply
   • Keep as runtime feedback: Situational preferences, context-dependent corrections, temporary focus areas

4. Present a consolidation plan to the user:

   ## Consolidation Plan
   
   **Will bake into SKILL.md** (permanent):
   - [feedback] → edit [file]: [what will change]
   
   **Will keep as runtime feedback** (situational):
   - [feedback] → reason: [why it stays runtime]
   
   Proceed?
   

5. On approval:

   • Edit the target SKILL.md files using the Edit tool
   • Clear only the graduated feedback entries:

   python ${CLAUDE_PLUGIN_ROOT}/scripts/feedback_manager.py autonomous-sdlc clear-feedback <category>
   

   • Keep non-graduated entries untouched

6. Report what changed and what remains as runtime feedback.

How Feedback is Used

When autonomous-sdlc skills run, they load relevant feedback entries:

• spec_writing feedback → loaded by bdd-spec to guide scenario style and language
• test_generation feedback → loaded by bdd-generate to shape test output
• tdd_workflow feedback → loaded by tdd-workflow to adjust cycle size and patterns
• bdd_workflow feedback → loaded by bdd-spec and bdd-generate for process preferences
• verification feedback → loaded by the sdlc-loop VERIFY state to adjust gate strictness
• beads_workflow feedback → loaded by beads-workflow for issue management style
• loop_behavior feedback → loaded by sdlc-loop every iteration (budgets, escalation taste, decision style)
• general feedback → applied to all SDLC skills

This ensures the user never has to repeat the same workflow preference twice.

Signs: Loop Guardrails

During a loop, recurring mistakes are recorded as one-line signs in the project's .sdlc/signs.md ("Sign: don't assume the helper exists — grep first"). Signs are project-local and replayed at every iteration's orient step.

When a sign is durable and project-independent, graduate it here:

echo '{"category": "loop_behavior", "feedback": "<the sign, generalized>"}' | \
  python ${CLAUDE_PLUGIN_ROOT}/scripts/feedback_manager.py autonomous-sdlc save-feedback

Signs follow the same lifecycle as other feedback: accumulate → recur → consolidate into SKILL.md.