Update test results directory structure and enhance Docker configurations

- Modified `.gitignore` to reflect the new path for test results.
- Updated `docker-compose.test.yml` to mount the correct test results directory.
- Adjusted `Dockerfile.test` to set the `PYTHONPATH` and ensure test results are saved in the updated location.
- Added `boto3` and `netron` to `requirements-test.txt` to support new functionalities.
- Updated `pytest.ini` to include the new `pythonpath` for test discovery.

These changes streamline the testing process and ensure compatibility with the updated directory structure.

.cursor/skills/autopilot/protocols.md

@@ -46,9 +46,8 @@ Rules:
 2. Always include a recommendation with a brief justification
 3. Keep option descriptions to one line each
 4. If only 2 options make sense, use A/B only — do not pad with filler options
-5. Play the notification sound (per `human-attention-sound.mdc`) before presenting the choice
-6. Record every user decision in the state file's `Key Decisions` section
-7. After the user picks, proceed immediately — no follow-up confirmation unless the choice was destructive
+5. Play the notification sound (per `.cursor/rules/human-attention-sound.mdc`) before presenting the choice
+6. After the user picks, proceed immediately — no follow-up confirmation unless the choice was destructive
 
 ## Work Item Tracker Authentication
 
@@ -124,16 +123,12 @@ Skill execution → FAILED
   │
   ├─ retry_count < 3 ?
   │    YES → increment retry_count in state file
-  │         → log failure reason in state file (Retry Log section)
   │         → re-read the sub-skill's SKILL.md
   │         → re-execute from the current sub_step
   │         → (loop back to check result)
   │
   │    NO (retry_count = 3) →
   │         → set status: failed in Current Step
-  │         → add entry to Blockers section:
-  │             "[Skill Name] failed 3 consecutive times at sub_step [M].
-  │              Last failure: [reason]. Auto-retry exhausted."
   │         → present warning to user (see Escalation below)
   │         → do NOT auto-retry again until user intervenes
 ```
@@ -143,18 +138,14 @@ Skill execution → FAILED
 1. **Auto-retry immediately**: when a skill fails, retry it without asking the user — the failure is often transient (missing user confirmation in a prior step, docker not running, file lock, etc.)
 2. **Preserve sub_step**: retry from the last recorded `sub_step`, not from the beginning of the skill — unless the failure indicates corruption, in which case restart from sub_step 1
 3. **Increment `retry_count`**: update `retry_count` in the state file's `Current Step` section on each retry attempt
-4. **Log each failure**: append the failure reason and timestamp to the state file's `Retry Log` section
-5. **Reset on success**: when the skill eventually succeeds, reset `retry_count: 0` and clear the `Retry Log` for that step
+4. **Reset on success**: when the skill eventually succeeds, reset `retry_count: 0`
 
 ### Escalation (after 3 consecutive failures)
 
 After 3 failed auto-retries of the same skill, the failure is likely not user-related. Stop retrying and escalate:
 
-1. Update the state file:
-   - Set `status: failed` in `Current Step`
-   - Set `retry_count: 3`
-   - Add a blocker entry describing the repeated failure
-2. Play notification sound (per `human-attention-sound.mdc`)
+1. Update the state file: set `status: failed` and `retry_count: 3` in `Current Step`
+2. Play notification sound (per `.cursor/rules/human-attention-sound.mdc`)
 3. Present using Choose format:
 
 ```
@@ -215,9 +206,8 @@ When executing a sub-skill, monitor for these signals:
 
 If the same autopilot step fails 3 consecutive times across conversations:
 
-- Record the failure pattern in the state file's `Blockers` section
 - Do NOT auto-retry on next invocation
-- Present the blocker and ask user for guidance before attempting again
+- Present the failure pattern and ask user for guidance before attempting again
 
 ## Context Management Protocol
 
@@ -308,7 +298,4 @@ For steps that produce `_docs/` artifacts (problem, research, plan, decompose, d
 
 On every invocation, before executing any skill, present a status summary built from the state file (with folder scan fallback). Use the Status Summary Template from the active flow file (`flows/greenfield.md` or `flows/existing-code.md`).
 
-For re-entry (state file exists), also include:
-- Key decisions from the state file's `Key Decisions` section
-- Last session context from the `Last Session` section
-- Any blockers from the `Blockers` section
+For re-entry (state file exists), cross-check the current step against `_docs/` folder structure and present any `status: failed` state to the user before continuing.